Patent Publication Number: US-11649981-B2

Title: Systems and methods for improving building control systems via command compensation

Description:
BACKGROUND 
     The present disclosure relates generally to a building control system and more particularly to a temperature control system optimizing the flow from the output of a valve based on command compensation. 
     Consistent fluid flow (e.g., water flow) in control valves can be important to maintain desirable temperature conditions in HVAC systems. Fluid (e.g., water) may need to be utilized as a medium of heat transfer inside of heating, ventilating, or air conditioning (HVAC) piping to allow for heating or cooling of air supplied by an air handling unit, thereby adjusting the temperature of a building zone. Controlling the temperature and rate at which water flows through the piping can be important for maintaining stable temperatures within a building zone. However in some instances, the valves cannot maintain the desired water flow when pressure disturbances arise. 
     SUMMARY 
     One implementation of the present disclosure is a temperature control system for use with a flow sensor associated with a valve and an actuator coupled to the valve. The temperature control system includes a first controller and a second controller. The first controller is configured to provide a flow rate setpoint for the second controller and a first flow command for the second controller. The second controller is configured to monitor fluid flow through the valve, generate a second flow command, and provide a control signal for the actuator in response to a weighted value of the first flow command. The first flow command and second flow command are related to reliability of the flow sensor. 
     In some embodiments, providing the control signal for the actuator in response to the weighted value of the first flow command includes providing the control signal for the actuator in response to the weighted value of the first flow command or in response to the weighted value of the second flow command or both. 
     In some embodiments, providing the control signal for the actuator in response to the weighted value of the first flow command includes partially receiving the first flow command from the first controller as a portion of the control signal such that the weight of the first flow command is substantially zero when the flow sensor is consistently reliable and providing a feedback signal from second controller as a portion of the control signal such that the weight of the feedback signal is substantially zero when the flow sensor is consistently unreliable, wherein the feedback signal comprises flow rate measurements to act as feedback from the flow sensor to the second controller. 
     In some embodiments, providing the control signal for the actuator in response to the weighted value of the first flow command includes operating reliably when the flow sensor is providing accurate readings to the second controller substantially more frequently than when the flow sensor is providing inaccurate readings to the second controller in a predetermined time period. It further includes operating unreliably when the flow sensor is providing inaccurate readings to the second controller substantially more frequently than when the flow sensor is providing accurate readings to the second controller in a predetermined time period. 
     In some embodiments providing the control signal for the actuator in response to the weighted value of the first flow command comprises weighting the first flow command by a scaling factor, wherein the scaling factor is based on a reliability of the flow sensor and is a constant value when the flow sensor is consistently reliable or unreliable. 
     In some embodiments, providing the control signal for the actuator in response to the weighted value of the first flow command comprises averaging, with a moving average filter, a plurality of measurements from the flow sensor to determine if the flow sensor is consistently reliable or unreliable. 
     In some embodiments, providing the control signal for the actuator in response to the weighted value of the first flow command comprises receiving, in a building zone, the flow rate setpoint for the second controller, the second controller configured to reach the flow setpoint by adjusting the water flow through the valve. 
     In some embodiments, the actuator, the second controller, and the flow sensor are configured to operate within a single actuator assembly. 
     Another implementation of the present disclosure is a temperature control device. The temperature control device includes a flow sensor configured to monitor flow through a valve, an actuator coupled to the valve, and a control system. The control system is configured to monitor fluid flow through the valve and combine a first flow command and a second flow command to generate a control signal. The first flow command and the second flow command are combined at least partially in response to reliability of the flow sensor. 
     In some embodiments, combining the first flow command and the second flow command to generate a control signal includes providing the first flow command from a first controller such that the weight of the first flow setpoint is substantially zero when the flow sensor is consistently reliable and providing a second flow command from a second controller such that the weight of the second flow command is substantially zero when the flow sensor is consistently unreliable. 
     In some embodiments, combining the first flow command and the second flow command to generate a control signal comprises combining the first flow command and the second flow command in a third controller. 
     In some embodiments, combining the first flow command and the second flow set command to generate a control signal includes operating reliably when the flow sensor is providing accurate readings to the control system substantially more frequently than when the flow sensor is providing inaccurate readings to the control system in a predetermined time period and operating unreliably when the flow sensor is providing inaccurate readings to the control system substantially more frequently than when the flow sensor is providing accurate readings to the control system in a predetermined time period. 
     In some embodiments, combining the first flow command and the second flow set command to generate a control signal comprises scaling the value of the first flow command and the second flow command such that the scaling of the first flow command and the second flow command is at least partially based on the reliability of the flow sensor. 
     In some embodiments, combining the first flow command and the second flow command to generate a control signal comprises averaging, with a moving average filter, a plurality of measurements from the flow sensor to determine if the flow sensor is consistently reliable or unreliable. 
     In some embodiments, the control system is further configured to generate the control signal to adjust the water flow through the valve. 
     In some embodiments, the actuator, the control system, and the flow sensor are configured to operate within a single actuator assembly. 
     Another implementation of the present disclosure is a method of controlling an actuator for a valve, where the valve controls fluid flow. The method includes receiving a first flow setpoint for the fluid flow from a first controller in response to temperature of an environment. The method further includes receiving a second flow setpoint from a second controller in response to an error value. The method further includes providing, via the second controller, a control signal to the actuator, wherein the control signal is provided using the first flow setpoint and the second flow setpoint, and a reliability of the flow sensor. 
     In some embodiments, providing the control signal to the actuator includes providing the first flow command from the first controller such that the weight of the first flow setpoint is substantially zero when the flow sensor is consistently reliable and providing the second flow command from the second controller such that the weight of the second flow setpoint is substantially zero when the flow sensor is consistently unreliable. 
     In some embodiments, providing the control signal to the actuator includes operating reliably when the flow sensor is providing accurate readings to the second controller substantially more frequently than when the flow sensor is providing inaccurate readings to the second controller in a predetermined time period and operating unreliably when the flow sensor is providing inaccurate readings to the second controller substantially more frequently than when the flow sensor is providing accurate readings to the second controller in a predetermined time period. 
     In some embodiments, receiving the second flow command in response to an error value comprises receiving the second flow setpoint in response to a different between the second flow setpoint and feedback from the flow sensor. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a drawing of a building equipped with a HVAC system, according to an exemplary embodiment. 
         FIG.  2    is a schematic of a waterside system which can be used as part of the HVAC system of  FIG.  1   , according to some embodiments. 
         FIG.  3    is a block diagram of an airside system which can be used as part of the HVAC system of  FIG.  1   , according to some embodiments. 
         FIG.  4    is a block diagram of a BMS which can be used in the building of  FIG.  1   , according to some embodiments. 
         FIG.  5    is a block diagram of a feedback control system which can be implemented in the waterside system of  FIG.  2   , according to some embodiments. 
         FIG.  6 A  is a block diagram of the outer loop of a feedback control system which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
         FIG.  6 B  is a block diagram of the inner loop a feedback control system which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
         FIG.  7 A  is a high-level block diagram of a feedback control system implementing command compensation which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
         FIG.  7 B  is a block diagram of a feedback control system implementing command compensation which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
         FIG.  7 C  is a graph of water flow versus time, which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
         FIG.  7 D  is a graph of water flow versus density, which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
         FIG.  8 A  is a flow diagram of a command compensation process which can be used as part of the flow control loop of  FIG.  7 A , according to some embodiments. 
         FIG.  8 B  is a flow diagram of a command compensation process which can be used as part of the flow control loop of  FIG.  7 A , according to some embodiments. 
         FIG.  9    is a graph illustrating a command compensation process which can be used as part of the flow control loop of  FIG.  7 A , according to some embodiments. 
         FIG.  10    is a graph illustrating the results of a command compensation process which can be used as part of the flow control loop of  FIG.  7 A , according to some embodiments. 
         FIG.  11    is a flow diagram of a process for implementing command compensation which can be used as part of the flow control loop of  FIG.  7 A , according to some embodiments. 
         FIG.  12    is a block diagram of a feedback control system implementing command compensation which can implemented in the feedback control system of  FIG.  5   , according to some embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     Overview 
     Referring generally to the FIGURES, a building control system with one or more controllers configured to optimize the water flow through piping within an HVAC system is shown. The HVAC system includes a means to regulate the flow based on temperature and a means to regulate flow based on the current water flow rate. When the required amount of water flowing through the HVAC system is smaller than what the sensor flow can read, the controller may not be able to adjust the valve positioning accordingly and the system performance can degrade. In some embodiments, a method of monitoring fluid flow when the sensor is unreliable is utilized. 
     In some embodiments, the system includes a flow controller configured to monitor the flow of water through a valve and a temperature controller configured to monitor the temperature of a building zone. The controllers are arranged such that the temperature controller determines the setpoint for the flow controller (i.e., a cascaded control system). To optimize the flow of the water through the HVAC system, the flow controller monitors and adjusts the flow rate by means of a flow sensor placed at or near a valve to achieve the setpoint set by the temperature controller. If the flow sensor is unreliable at certain times (e.g., providing no values, providing incorrect values), compensation actions can be provided in some embodiments. 
     Compensation action can be achieved by using a weighted linear combination of the commands from the controllers monitoring water flow through a water flow sensor and the commands of a controller monitoring temperature, wherein the linear combination of these commands is received by an actuator to adjust a valve in the HVAC system. The control system is configured to utilize this output command compensation such that the weighting of each part of the linear combination varies with the reliability of the flow sensor. 
     Building with HVAC System 
     Referring now to  FIG.  1   , a perspective view of a building  10  is shown. Building  10  is served by a building automation system (BAS). A BAS is, in general, a system of devices configured to control, monitor, and manage equipment in or around a building or building area. A BAS can include, for example, a HVAC system, a security system, a lighting system, a fire alerting system, any other system that is capable of managing building functions or devices, or any combination thereof. 
     The BAS that serves building  10  includes an HVAC system  100 . HVAC system  100  may include a plurality of HVAC devices (e.g., heaters, chillers, air handling units, pumps, fans, thermal energy storage, etc.) configured to provide heating, cooling, ventilation, or other services for building  10 . For example, HVAC system  100  is shown to include a waterside system  120  and an airside system  130 . Waterside system  120  may provide a heated or chilled fluid to an air handling unit of airside system  130 . Airside system  130  may use the heated or chilled fluid to heat or cool an airflow provided to building  10 . In some embodiments, waterside system  120  is replaced with a central energy plant such as central plant  200 , described with reference to  FIG.  2   . 
     Still referring to  FIG.  1   , HVAC system  100  is shown to include a chiller  102 , a boiler  104 , and a rooftop air handling unit (AHU)  106 . Waterside system  120  may use boiler  104  and chiller  102  to heat or cool a working fluid (e.g., water, glycol, etc.) and may circulate the working fluid to AHU  106 . In various embodiments, the HVAC devices of waterside system  120  may be located in or around building  10  (as shown in  FIG.  1   ) or at an offsite location such as a central plant (e.g., a chiller plant, a steam plant, a heat plant, etc.). The working fluid may be heated in boiler  104  or cooled in chiller  102 , depending on whether heating or cooling is required in building  10 . Boiler  104  may add heat to the circulated fluid, for example, by burning a combustible material (e.g., natural gas) or using an electric heating element. Chiller  102  may place the circulated fluid in a heat exchange relationship with another fluid (e.g., a refrigerant) in a heat exchanger (e.g., an evaporator) to absorb heat from the circulated fluid. The working fluid from chiller  102  and/or boiler  104  may be transported to AHU  106  via piping  108 . 
     AHU  106  may place the working fluid in a heat exchange relationship with an airflow passing through AHU  106  (e.g., via one or more stages of cooling coils and/or heating coils). The airflow may be, for example, outside air, return air from within building  10 , or a combination of both. AHU  106  may transfer heat between the airflow and the working fluid to provide heating or cooling for the airflow. For example, AHU  106  may include one or more fans or blowers configured to pass the airflow over or through a heat exchanger containing the working fluid. The working fluid may then return to chiller  102  or boiler  104  via piping  110 . 
     Airside system  130  may deliver the airflow supplied by AHU  106  (i.e., the supply airflow) to building  10  via air supply ducts  112  and may provide return air from building  10  to AHU  106  via air return ducts  114 . In some embodiments, airside system  130  includes multiple variable air volume (VAV) units  116 . For example, airside system  130  is shown to include a separate VAV unit  116  on each floor or zone of building  10 . VAV units  116  may include dampers or other flow control elements that can be operated to control an amount of the supply airflow provided to individual zones of building  10 . In other embodiments, airside system  130  delivers the supply airflow into one or more zones of building  10  (e.g., via air supply ducts  112 ) without using intermediate VAV units  116  or other flow control elements. AHU  106  may include various sensors (e.g., temperature sensors, pressure sensors, etc.) configured to measure attributes of the supply airflow. AHU  106  may receive input from sensors located within AHU  106  and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow through AHU  106  to achieve setpoint conditions for the building zone. 
     Central Plant and Control System 
     Referring now to  FIG.  2   , a block diagram of a central plant  200  is shown, according to an exemplary embodiment. In brief overview, central plant  200  may include various types of equipment configured to serve the thermal energy loads of a building or campus (i.e., a system of buildings). For example, central plant  200  may include heaters, chillers, heat recovery chillers, cooling towers, or other types of equipment configured to serve the heating and/or cooling loads of a building or campus. Central plant  200  may consume resources from a utility (e.g., electricity, water, natural gas, etc.) to heat or cool a working fluid that is circulated to one or more buildings or stored for later use (e.g., in thermal energy storage tanks) to provide heating or cooling for the buildings. In various embodiments, central plant  200  may supplement or replace waterside system  120  in building  10  or may be implemented separate from building  10  (e.g., at an offsite location). 
     Central plant  200  is shown to include a plurality of subplants  202 - 212  including a heater subplant  202 , a heat recovery chiller subplant  204 , a chiller subplant  206 , a cooling tower subplant  208 , a hot thermal energy storage (TES) subplant  210 , and a cold thermal energy storage (TES) subplant  212 . Subplants  202 - 212  consume resources from utilities to serve the thermal energy loads (e.g., hot water, cold water, heating, cooling, etc.) of a building or campus. For example, heater subplant  202  may be configured to heat water in a hot water loop  214  that circulates the hot water between heater subplant  202  and building  10 . Chiller subplant  206  may be configured to chill water in a cold water loop  216  that circulates the cold water between chiller subplant  206  building  10 . Heat recovery chiller subplant  204  may be configured to transfer heat from cold water loop  216  to hot water loop  214  to provide additional heating for the hot water and additional cooling for the cold water. Condenser water loop  218  may absorb heat from the cold water in chiller subplant  206  and reject the absorbed heat in cooling tower subplant  208  or transfer the absorbed heat to hot water loop  214 . Hot TES subplant  210  and cold TES subplant  212  may store hot and cold thermal energy, respectively, for subsequent use. 
     Hot water loop  214  and cold water loop  216  may deliver the heated and/or chilled water to air handlers located on the rooftop of building  10  (e.g., AHU  106 ) or to individual floors or zones of building  10  (e.g., VAV units  116 ). The air handlers push air past heat exchangers (e.g., heating coils or cooling coils) through which the water flows to provide heating or cooling for the air. The heated or cooled air may be delivered to individual zones of building  10  to serve the thermal energy loads of building  10 . The water then returns to subplants  202 - 212  to receive further heating or cooling. 
     Although subplants  202 - 212  are shown and described as heating and cooling water for circulation to a building, it is understood that any other type of working fluid (e.g., glycol, CO 2 , etc.) may be used in place of or in addition to water to serve the thermal energy loads. In other embodiments, subplants  202 - 212  may provide heating and/or cooling directly to the building or campus without requiring an intermediate heat transfer fluid. These and other variations to central plant  200  are within the teachings of the present invention. 
     Each of subplants  202 - 212  may include a variety of equipment configured to facilitate the functions of the subplant. For example, heater subplant  202  is shown to include a plurality of heating elements  220  (e.g., boilers, electric heaters, etc.) configured to add heat to the hot water in hot water loop  214 . Heater subplant  202  is also shown to include several pumps  222  and  224  configured to circulate the hot water in hot water loop  214  and to control the flow rate of the hot water through individual heating elements  220 . Chiller subplant  206  is shown to include a plurality of chillers  232  configured to remove heat from the cold water in cold water loop  216 . Chiller subplant  206  is also shown to include several pumps  234  and  236  configured to circulate the cold water in cold water loop  216  and to control the flow rate of the cold water through individual chillers  232 . 
     Heat recovery chiller subplant  204  is shown to include a plurality of heat recovery heat exchangers  226  (e.g., refrigeration circuits) configured to transfer heat from cold water loop  216  to hot water loop  214 . Heat recovery chiller subplant  204  is also shown to include several pumps  228  and  230  configured to circulate the hot water and/or cold water through heat recovery heat exchangers  226  and to control the flow rate of the water through individual heat recovery heat exchangers  226 . Cooling tower subplant  208  is shown to include a plurality of cooling towers  238  configured to remove heat from the condenser water in condenser water loop  218 . Cooling tower subplant  208  is also shown to include several pumps  240  configured to circulate the condenser water in condenser water loop  218  and to control the flow rate of the condenser water through individual cooling towers  238 . 
     Hot TES subplant  210  is shown to include a hot TES tank  242  configured to store the hot water for later use. Hot TES subplant  210  may also include one or more pumps or valves configured to control the flow rate of the hot water into or out of hot TES tank  242 . Cold TES subplant  212  is shown to include cold TES tanks  244  configured to store the cold water for later use. Cold TES subplant  212  may also include one or more pumps or valves configured to control the flow rate of the cold water into or out of cold TES tanks  244 . 
     In some embodiments, one or more of the pumps in central plant  200  (e.g., pumps  222 ,  224 ,  228 ,  230 ,  234 ,  236 , and/or  240 ) or pipelines in central plant  200  include an isolation valve associated therewith. Isolation valves may be integrated with the pumps or positioned upstream or downstream of the pumps to control the fluid flows in central plant  200 . In various embodiments, central plant  200  may include more, fewer, or different types of devices and/or subplants based on the particular configuration of central plant  200  and the types of loads served by central plant  200 . 
     Referring now to  FIG.  3   , a block diagram of an airside system  300  is shown, according to an example embodiment. In various embodiments, airside system  300  can supplement or replace airside system  130  in HVAC system  100  or can be implemented separate from HVAC system  100 . When implemented in HVAC system  100 , airside system  300  can include a subset of the HVAC devices in HVAC system  100  (e.g., AHU  106 , VAV units  116 , duct  112 , duct  114 , fans, dampers, etc.) and can be located in or around building  10 . Airside system  300  can operate to heat or cool an airflow provided to building  10  using a heated or chilled fluid provided by waterside system  200 . 
     In  FIG.  3   , airside system  300  is shown to include an economizer-type air handling unit (AHU)  302 . Economizer-type AHUs vary the amount of outside air and return air used by the air handling unit for heating or cooling. For example, AHU  302  can receive return air  304  from building zone  306  via return air duct  308  and can deliver supply air  310  to building zone  306  via supply air duct  312 . In some embodiments, AHU  302  is a rooftop unit located on the roof of building  10  (e.g., AHU  106  as shown in  FIG.  1   ) or otherwise positioned to receive both return air  304  and outside air  314 . AHU  302  can be configured to operate exhaust air damper  316 , mixing damper  318 , and outside air damper  320  to control an amount of outside air  314  and return air  304  that combine to form supply air  310 . Any return air  304  that does not pass through mixing damper  318  can be exhausted from AHU  302  through exhaust damper  316  as exhaust air  322 . 
     Each of dampers  316 - 320  can be operated by an actuator. For example, exhaust air damper  316  can be operated by actuator  324 , mixing damper  318  can be operated by actuator  326 , and outside air damper  320  can be operated by actuator  328 . Actuators  324 - 328  can communicate with an AHU controller  330  via a communications link  332 . Actuators  324 - 328  can receive control signals from AHU controller  330  and can provide feedback signals to AHU controller  330 . Feedback signals can include, for example, an indication of a current actuator or damper position, an amount of torque or force exerted by the actuator, diagnostic information (e.g., results of diagnostic tests performed by actuators  324 - 328 ), status information, commissioning information, configuration settings, calibration data, and/or other types of information or data that can be collected, stored, or used by actuators  324 - 328 . AHU controller  330  can be an economizer controller configured to use one or more control algorithms (e.g., state-based algorithms, extremum seeking control (ESC) algorithms, proportional-integral (PI) control algorithms, proportional-integral-derivative (PID) control algorithms, model predictive control (MPC) algorithms, feedback control algorithms, etc.) to control actuators  324 - 328 . 
     Still referring to  FIG.  3   , AHU  302  is shown to include a cooling coil  334 , a heating coil  336 , and a fan  338  positioned within supply air duct  312 . Fan  338  can be configured to force supply air  310  through cooling coil  334  and/or heating coil  336  and provide supply air  310  to building zone  306 . AHU controller  330  can communicate with fan  338  via communications link  340  to control a flow rate of supply air  310 . In some embodiments, AHU controller  330  controls an amount of heating or cooling applied to supply air  310  by modulating a speed of fan  338 . 
     Cooling coil  334  can receive a chilled fluid from waterside system  200  (e.g., from cold water loop  216 ) via piping  342  and can return the chilled fluid to waterside system  200  via piping  344 . Valve  346  can be positioned along piping  342  or piping  344  to control a flow rate of the chilled fluid through cooling coil  334 . In some embodiments, cooling coil  334  includes multiple stages of cooling coils that can be independently activated and deactivated (e.g., by AHU controller  330 , by BMS controller  366 , etc.) to modulate an amount of cooling applied to supply air  310 . 
     Heating coil  336  can receive a heated fluid from waterside system  200  (e.g., from hot water loop  214 ) via piping  348  and can return the heated fluid to waterside system  200  via piping  350 . Valve  352  can be positioned along piping  348  or piping  350  to control a flow rate of the heated fluid through heating coil  336 . In some embodiments, heating coil  336  includes multiple stages of heating coils that can be independently activated and deactivated (e.g., by AHU controller  330 , by BMS controller  366 , etc.) to modulate an amount of heating applied to supply air  310 . 
     Each of valves  346  and  352  can be controlled by an actuator. For example, valve  346  can be controlled by actuator  354  and valve  352  can be controlled by actuator  356 . Actuators  354 - 356  can communicate with AHU controller  330  via communications links  358 - 360 . Actuators  354 - 356  can receive control signals from AHU controller  330  and can provide feedback signals to controller  330 . In some embodiments, AHU controller  330  receives a measurement of the supply air temperature from a temperature sensor  362  positioned in supply air duct  312  (e.g., downstream of cooling coil  334  and/or heating coil  336 ). AHU controller  330  can also receive a measurement of the temperature of building zone  306  from a temperature sensor  364  located in building zone  306 . 
     In some embodiments, AHU controller  330  operates valves  346  and  352  via actuators  354 - 356  to modulate an amount of heating or cooling provided to supply air  310  (e.g., to achieve a setpoint temperature for supply air  310  or to maintain the temperature of supply air  310  within a setpoint temperature range). The positions of valves  346  and  352  affect the amount of heating or cooling provided to supply air  310  by cooling coil  334  or heating coil  336  and may correlate with the amount of energy consumed to achieve a desired supply air temperature. AHU controller  330  can control the temperature of supply air  310  and/or building zone  306  by activating or deactivating coils  334 - 336 , adjusting a speed of fan  338 , or a combination of both. 
     Still referring to  FIG.  3   , airside system  300  is shown to include a building management system (BMS) controller  366  and a client device  368 . BMS controller  366  can include one or more computer systems (e.g., servers, supervisory controllers, subsystem controllers, etc.) that serve as system level controllers, application or data servers, head nodes, or master controllers for airside system  300 , waterside system  200 , HVAC system  100 , and/or other controllable systems that serve building  10 . BMS controller  366  can communicate with multiple downstream building systems or subsystems (e.g., HVAC system  100 , a security system, a lighting system, waterside system  200 , etc.) via a communications link  370  according to like or disparate protocols (e.g., LON, BACnet, etc.). In various embodiments, AHU controller  330  and BMS controller  366  can be separate (as shown in  FIG.  3   ) or integrated. In an integrated implementation, AHU controller  330  can be a software module configured for execution by a processor of BMS controller  366 . 
     In some embodiments, AHU controller  330  receives information from BMS controller  366  (e.g., commands, setpoints, operating boundaries, etc.) and provides information to BMS controller  366  (e.g., temperature measurements, valve or actuator positions, operating statuses, diagnostics, etc.). For example, AHU controller  330  can provide BMS controller  366  with temperature measurements from temperature sensors  362  and  364 , equipment on/off states, equipment operating capacities, and/or any other information that can be used by BMS controller  366  to monitor or control a variable state or condition within building zone  306 . 
     Client device  368  can include one or more human-machine interfaces or client interfaces (e.g., graphical user interfaces, reporting interfaces, text-based computer interfaces, client-facing web services, web servers that provide pages to web clients, etc.) for controlling, viewing, or otherwise interacting with HVAC system  100 , its subsystems, and/or devices. Client device  368  can be a computer workstation, a client terminal, a remote or local interface, or any other type of user interface device. Client device  368  can be a stationary terminal or a mobile device. For example, client device  368  can be a desktop computer, a computer server with a user interface, a laptop computer, a tablet, a smartphone, a PDA, or any other type of mobile or non-mobile device. Client device  368  can communicate with BMS controller  366  and/or AHU controller  330  via communications link  372 . 
     Referring now to  FIG.  4   , a block diagram of a building management system (BMS)  400  is shown, according to an example embodiment. BMS  400  can be implemented in building  10  to automatically monitor and control various building functions. BMS  400  is shown to include BMS controller  366  and a plurality of building subsystems  428 . Building subsystems  428  are shown to include a building electrical subsystem  434 , an information communication technology (ICT) subsystem  436 , a security subsystem  438 , a HVAC subsystem  440 , a lighting subsystem  442 , a lift/escalators subsystem  432 , and a fire safety subsystem  430 . In various embodiments, building subsystems  428  can include fewer, additional, or alternative subsystems. For example, building subsystems  428  can also or alternatively include a refrigeration subsystem, an advertising or signage subsystem, a cooking subsystem, a vending subsystem, a printer or copy service subsystem, or any other type of building subsystem that uses controllable equipment and/or sensors to monitor or control building  10 . In some embodiments, building subsystems  428  include waterside system  200  and/or airside system  300 , as described with reference to  FIGS.  2  and  3   . 
     Each of building subsystems  428  can include any number of devices, controllers, and connections for completing its individual functions and control activities. HVAC subsystem  440  can include many of the same components as HVAC system  100 , as described with reference to  FIGS.  1 - 3   . For example, HVAC subsystem  440  can include a chiller, a boiler, any number of air handling units, economizers, field controllers, supervisory controllers, actuators, temperature sensors, and other devices for controlling the temperature, humidity, airflow, or other variable conditions within building  10 . Lighting subsystem  442  can include any number of light fixtures, ballasts, lighting sensors, dimmers, or other devices configured to controllably adjust the amount of light provided to a building space. Security subsystem  438  can include occupancy sensors, video surveillance cameras, digital video recorders, video processing servers, intrusion detection devices, access control devices (e.g., card access, etc.) and servers, or other security-related devices. 
     Still referring to  FIG.  4   , BMS controller  366  includes a communications interface  407  and a BMS interface  409 . Interface  407  can facilitate communications between BMS controller  366  and external applications (e.g., monitoring and reporting applications  422 , enterprise control applications  426 , remote systems and applications  444 , applications residing on client devices  448 , etc.) for allowing user control, monitoring, and adjustment to BMS controller  366  and/or subsystems  428 . Interface  407  can also facilitate communications between BMS controller  366  and client devices  448 . BMS interface  409  can facilitate communications between BMS controller  366  and building subsystems  428  (e.g., HVAC, lighting security, lifts, power distribution, business, etc.). 
     Interfaces  407 ,  409  can be or include wired or wireless communications interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wire terminals, etc.) for conducting data communications with building subsystems  428  or other external systems or devices. In various embodiments, communications via interfaces  407 ,  409  can be direct (e.g., local wired or wireless communications) or via a communications network  446  (e.g., a WAN, the Internet, a cellular network, etc.). For example, interfaces  407 ,  409  can include an Ethernet card and port for sending and receiving data via an Ethernet-based communications link or network. In another example, interfaces  407 ,  409  can include a Wi-Fi transceiver for communicating via a wireless communications network. In another example, one or both of interfaces  407 ,  409  can include cellular or mobile phone communications transceivers. In one embodiment, communications interface  407  is a power line communications interface and BMS interface  409  is an Ethernet interface. In other embodiments, both communications interface  407  and BMS interface  409  are Ethernet interfaces or are the same Ethernet interface. 
     Still referring to  FIG.  4   , BMS controller  366  is shown to include a processing circuit  404  including a processor  406  and memory  408 . Processing circuit  404  can be communicably connected to BMS interface  409  and/or communications interface  407  such that processing circuit  404  and the various components thereof can send and receive data via interfaces  407 ,  409 . Processor  406  can be implemented as a general purpose processor, an application specific integrated circuit (ASIC), one or more field programmable gate arrays (FPGAs), a group of processing components, or other suitable electronic processing components. 
     Memory  408  (e.g., memory, memory unit, storage device, etc.) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described in the present application. Memory  408  can be or include volatile memory or non-volatile memory. Memory  408  can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present application. According to an example embodiment, memory  408  is communicably connected to processor  406  via processing circuit  404  and includes computer code for executing (e.g., by processing circuit  404  and/or processor  406 ) one or more processes described herein. 
     In some embodiments, BMS controller  366  is implemented within a single computer (e.g., one server, one housing, etc.). In various other embodiments BMS controller  366  can be distributed across multiple servers or computers (e.g., that can exist in distributed locations). Further, while  FIG.  4    shows applications  422  and  426  as existing outside of BMS controller  366 , in some embodiments, applications  422  and  426  can be hosted within BMS controller  366  (e.g., within memory  408 ). 
     Still referring to  FIG.  4   , memory  408  is shown to include an enterprise integration layer  410 , an automated measurement and validation (AM&amp;V) layer  412 , a demand response (DR) layer  414 , a fault detection and diagnostics (FDD) layer  416 , an integrated control layer  418 , and a building subsystem integration later  420 . Layers  410 - 420  can be configured to receive inputs from building subsystems  428  and other data sources, determine optimal control actions for building subsystems  428  based on the inputs, generate control signals based on the optimal control actions, and provide the generated control signals to building subsystems  428 . The following paragraphs describe some of the general functions performed by each of layers  410 - 420  in BMS  400 . 
     Enterprise integration layer  410  can be configured to serve clients or local applications with information and services to support a variety of enterprise-level applications. For example, enterprise control applications  426  can be configured to provide subsystem-spanning control to a graphical user interface (GUI) or to any number of enterprise-level business applications (e.g., accounting systems, user identification systems, etc.). Enterprise control applications  426  can also or alternatively be configured to provide configuration GUIs for configuring BMS controller  366 . In yet other embodiments, enterprise control applications  426  can work with layers  410 - 420  to optimize building performance (e.g., efficiency, energy use, comfort, or safety) based on inputs received at interface  407  and/or BMS interface  409 . 
     Building subsystem integration layer  420  can be configured to manage communications between BMS controller  366  and building subsystems  428 . For example, building subsystem integration layer  420  can receive sensor data and input signals from building subsystems  428  and provide output data and control signals to building subsystems  428 . Building subsystem integration layer  420  can also be configured to manage communications between building subsystems  428 . Building subsystem integration layer  420  translate communications (e.g., sensor data, input signals, output signals, etc.) across a plurality of multi-vendor/multi-protocol systems. 
     Demand response layer  414  can be configured to optimize resource usage (e.g., electricity use, natural gas use, water use, etc.) and/or the monetary cost of such resource usage in response to satisfy the demand of building  10 . The optimization can be based on time-of-use prices, curtailment signals, energy availability, or other data received from utility providers, distributed energy generation systems  424 , from energy storage  427  (e.g., hot TES  242 , cold TES  244 , etc.), or from other sources. Demand response layer  414  can receive inputs from other layers of BMS controller  366  (e.g., building subsystem integration layer  420 , integrated control layer  418 , etc.). The inputs received from other layers can include environmental or sensor inputs such as temperature, carbon dioxide levels, relative humidity levels, air quality sensor outputs, occupancy sensor outputs, room schedules, and the like. The inputs can also include inputs such as electrical use (e.g., expressed in kWh), thermal load measurements, pricing information, projected pricing, smoothed pricing, curtailment signals from utilities, and the like. 
     According to an example embodiment, demand response layer  414  includes control logic for responding to the data and signals it receives. These responses can include communicating with the control algorithms in integrated control layer  418 , changing control strategies, changing setpoints, or activating/deactivating building equipment or subsystems in a controlled manner. Demand response layer  414  can also include control logic configured to determine when to utilize stored energy. For example, demand response layer  414  can determine to begin using energy from energy storage  427  just prior to the beginning of a peak use hour. 
     In some embodiments, demand response layer  414  includes a control module configured to actively initiate control actions (e.g., automatically changing setpoints) which minimize energy costs based on one or more inputs representative of or based on demand (e.g., price, a curtailment signal, a demand level, etc.). In some embodiments, demand response layer  414  uses equipment models to determine an optimal set of control actions. The equipment models can include, for example, thermodynamic models describing the inputs, outputs, and/or functions performed by various sets of building equipment. Equipment models can represent collections of building equipment (e.g., subplants, chiller arrays, etc.) or individual devices (e.g., individual chillers, heaters, pumps, etc.). 
     Demand response layer  414  can further include or draw upon one or more demand response policy definitions (e.g., databases, XML files, etc.). The policy definitions can be edited or adjusted by a user (e.g., via a graphical user interface) so that the control actions initiated in response to demand inputs can be tailored for the user&#39;s application, desired comfort level, particular building equipment, or based on other concerns. For example, the demand response policy definitions can specify which equipment can be turned on or off in response to particular demand inputs, how long a system or piece of equipment should be turned off, what setpoints can be changed, what the allowable set point adjustment range is, how long to hold a high demand setpoint before returning to a normally scheduled setpoint, how close to approach capacity limits, which equipment modes to utilize, the energy transfer rates (e.g., the maximum rate, an alarm rate, other rate boundary information, etc.) into and out of energy storage devices (e.g., thermal storage tanks, battery banks, etc.), and when to dispatch on-site generation of energy (e.g., via fuel cells, a motor generator set, etc.). 
     Integrated control layer  418  can be configured to use the data input or output of building subsystem integration layer  420  and/or demand response later  414  to make control decisions. Due to the subsystem integration provided by building subsystem integration layer  420 , integrated control layer  418  can integrate control activities of the subsystems  428  such that the subsystems  428  behave as a single integrated supersystem. In an example embodiment, integrated control layer  418  includes control logic that uses inputs and outputs from a plurality of building subsystems to provide greater comfort and energy savings relative to the comfort and energy savings that separate subsystems could provide alone. For example, integrated control layer  418  can be configured to use an input from a first subsystem to make an energy-saving control decision for a second subsystem. Results of these decisions can be communicated back to building subsystem integration layer  420 . 
     Integrated control layer  418  is shown to be logically below demand response layer  414 . Integrated control layer  418  can be configured to enhance the effectiveness of demand response layer  414  by enabling building subsystems  428  and their respective control loops to be controlled in coordination with demand response layer  414 . This configuration may advantageously reduce disruptive demand response behavior relative to conventional systems. For example, integrated control layer  418  can be configured to assure that a demand response-driven upward adjustment to the setpoint for chilled water temperature (or another component that directly or indirectly affects temperature) does not result in an increase in fan energy (or other energy used to cool a space) that would result in greater total building energy use than was saved at the chiller. 
     Integrated control layer  418  can be configured to provide feedback to demand response layer  414  so that demand response layer  414  checks that constraints (e.g., temperature, lighting levels, etc.) are properly maintained even while demanded load shedding is in progress. The constraints can also include setpoint or sensed boundaries relating to safety, equipment operating limits and performance, comfort, fire codes, electrical codes, energy codes, and the like. Integrated control layer  418  is also logically below fault detection and diagnostics layer  416  and automated measurement and validation layer  412 . Integrated control layer  418  can be configured to provide calculated inputs (e.g., aggregations) to these higher levels based on outputs from more than one building subsystem. 
     Automated measurement and validation (AM&amp;V) layer  412  can be configured to verify that control strategies commanded by integrated control layer  418  or demand response layer  414  are working properly (e.g., using data aggregated by AM&amp;V layer  412 , integrated control layer  418 , building subsystem integration layer  420 , FDD layer  416 , or otherwise). The calculations made by AM&amp;V layer  412  can be based on building system energy models and/or equipment models for individual BMS devices or subsystems. For example, AM&amp;V layer  412  can compare a model-predicted output with an actual output from building subsystems  428  to determine an accuracy of the model. 
     Fault detection and diagnostics (FDD) layer  416  can be configured to provide on-going fault detection for building subsystems  428 , building subsystem devices (i.e., building equipment), and control algorithms used by demand response layer  414  and integrated control layer  418 . FDD layer  416  can receive data inputs from integrated control layer  418 , directly from one or more building subsystems or devices, or from another data source. FDD layer  416  can automatically diagnose and respond to detected faults. The responses to detected or diagnosed faults can include providing an alert message to a user, a maintenance scheduling system, or a control algorithm configured to attempt to repair the fault or to work-around the fault. 
     FDD layer  416  can be configured to output a specific identification of the faulty component or cause of the fault (e.g., loose damper linkage) using detailed subsystem inputs available at building subsystem integration layer  420 . In other example embodiments, FDD layer  416  is configured to provide “fault” events to integrated control layer  418  which executes control strategies and policies in response to the received fault events. According to an example embodiment, FDD layer  416  (or a policy executed by an integrated control engine or business rules engine) can shut-down systems or direct control activities around faulty devices or systems to reduce energy waste, extend equipment life, or assure proper control response. 
     FDD layer  416  can be configured to store or access a variety of different system data stores (or data points for live data). FDD layer  416  can use some content of the data stores to identify faults at the equipment level (e.g., specific chiller, specific AHU, specific terminal unit, etc.) and other content to identify faults at component or subsystem levels. For example, building subsystems  428  can generate temporal (i.e., time-series) data indicating the performance of BMS  400  and the various components thereof. The data generated by building subsystems  428  can include measured or calculated values that exhibit statistical characteristics and provide information about how the corresponding system or process (e.g., a temperature control process, a flow control process, etc.) is performing in terms of error from its setpoint. These processes can be examined by FDD layer  416  to expose when the system begins to degrade in performance and alert a user to repair the fault before it becomes more severe. 
     Feedback Control System 
     Turning now to  FIG.  5   , a block diagram of an actuator device  502  within a feedback control system  500  is shown. In some embodiments, the feedback control system  500  is a cascaded feedback control system. In some embodiments, a primary controller (e.g., controller  504 ) generates a control signal that serves as the setpoint for a secondary controller (e.g., flow/velocity feedback controller  530 ). Outer control loop  550  is shown to include zone temperature controller  524 , actuator  502 , and controller  504  in series with feedback from measured zone temperature data  510 . In some embodiments, outer control loop  550  includes an inner control loop configured to modulate fluid flow from valve  546  based on feedback from flow sensor  548 , as shown as inner control loop  560 . In some embodiments, feedback control system  500  is a component or subsystem of waterside system  200 , as described with reference to  FIG.  2   . In other embodiments, feedback control system  500  is a component or subsystem of HVAC system  100 , airside system  300 , or BMS  400 , as described with reference to  FIGS.  1 - 4   . 
     Feedback control system  500  may include, among other components, actuator  502 , controller  504 , building zone  506 , zone temperature controller  524 , and valve  546 . In some embodiments, controller  504  is a primary controller for the components of an HVAC system (e.g., HVAC system  100 ) within the outer control loop of feedback control system  500 . In other embodiments, controller  504  is a thermostat or a BMS controller (e.g., for BMS  400 ). In still further embodiments, controller  504  is a user device configured to run a building management application (e.g., a mobile phone, a tablet, a laptop). Controller  504  may receive data from temperature sensor  508 . Temperature sensor  508  may be any type of sensor or device configured to measure an environmental condition (e.g., temperature) of a building zone  506 . Building zone  506  may be any subsection of a building (e.g., a room, a block of rooms, a floor, etc.). 
     Controller  504  is shown to include a digital filter  512 , a wireless communications interface  518 , and a comparator  520 . Measured zone temperature data  510  from temperature sensor  508  may be received as an input signal to digital filter  512 . Digital filter  512  may be configured to convert the measured zone temperature data  510  into a measured zone temperature feedback signal  514  that may be provided as an input to comparator  520 . In some embodiments, digital filter  512  is a first order low pass filter. In other embodiments, digital filter  512  may be a low pass filter of a different order or a different type of filter. 
     Controller  504  is further shown to include wireless communications interface  518 . In some embodiments, wireless communications interface  518  may communicate data from controller  504  to communications interface  552  of actuator device  502 . In other embodiments, communications interfaces  518  and  552  may communicate with other external systems or devices. Communications via interface  518  may be direct (e.g., local wireless communications) or via a communications network (e.g., a WAN, the Internet, a cellular network). For example, interfaces  518  and  552  may include a Wi-Fi transceiver for communicating via wireless communications network. In another example, one or both interfaces  518  and  552  may include cellular or mobile phone communications transceivers. In some embodiments, multiple controllers and smart actuator devices may communicate using a mesh topology. In other embodiments, communications interfaces  518  and  552  may be configured to transmit smart actuator device data (e.g., a fault status, an actuator and/or valve position) to an external network. In still further embodiments, communications interfaces  518  and  552  are connected via a wired, rather than wireless, network. 
     Comparator  520  may be configured to compare the measured zone temperature feedback signal  514  output from digital filter  512  with a zone temperature setpoint value  516 . Comparator  520  may then output a temperature error signal  522  that is received by zone temperature controller  524 . Comparator  520  may be a discrete electronics part or implemented as part of controller  504 . If comparator  520  determines that the zone temperature feedback signal  514  is higher than the zone temperature setpoint value  516  (i.e., building zone  506  is hotter than the setpoint value), zone temperature controller  524  may output a control signal that causes actuator device  502  to modify the flow rate through coil  550  such that cooling to building zone  506  is increased. If comparator  520  determines that the zone temperature feedback signal  514  is lower than the zone temperature setpoint value  516  (i.e., building zone  506  is cooler than the setpoint value), zone temperature controller  524  may output a control signal that causes actuator device  502  to modify the flow rate through coil  550  such that heating to building zone  506  is increased. 
     In various embodiments, zone temperature controller  524  is a pattern recognition adaptive controller (PRAC), a model recognition adaptive controller (MRAC), or another type of tuning or adaptive feedback controller. Adaptive control is a control method in which a controller may adapt to a controlled system with associated parameters which vary, or are initially uncertain. Zone temperature controller  524  may be incorporated fully into controller  504 . In some embodiments, zone temperature controller  524  is similar or identical to the adaptive feedback controller described in U.S. Pat. No. 8,825,185, granted on Sep. 2, 2014, the entirety of which is herein incorporated by reference. 
     Still referring to  FIG.  5   , actuator device  502  is shown to include a flow/velocity span block  526 , a flow/velocity feedback controller  530 , a valve actuator  540 , and a communications interface  552 . Zone temperature error  522  output from comparator  520  may be transmitted to actuator  502  via zone temperature controller  524 . In some embodiments, zone temperature error may also be received by flow/velocity feedback controller  530 . This may be done for more controlling based on the temperature measurements from temperature sensor  508 . The functionality and operation of receiving both zone temperature error  522  and flow rate velocity feedback  532  at flow/velocity feedback controller  530  is described in greater detail below, with reference to  FIGS.  7 - 11   . Flow/velocity span block  526  may be configured to enforce allowable maximum and minimum flow range limits on the received zone temperature error  522 . For example, a technician installing the components of cascaded control system  500  or an administrator of HVAC system  100  may input a maximum and/or a minimum flow range limit for the flow/velocity span block  526 . In some embodiments, the flow range limits are transmitted via mobile device (e.g., a smart phone, a table) and are received via communications interface  552  of actuator device  502 . In other embodiments, the flow range limits are transmitted to interface  552  via wired network. The maximum and/or minimum flow range limits may be utilized in the calibration process of a flow rate sensor. 
     Flow/velocity feedback controller  530  is configured to receive a flow rate/velocity setpoint signal  528  from flow/velocity span block  526  and a flow rate/velocity feedback signal  532  from digital filter  538 . The combination of these signals being received at flow/velocity feedback controller  530  is described in greater detail in  FIGS.  6 - 11   . Flow/velocity feedback controller  530  is further configured to output a command signal (e.g., valve command  570 ) to valve actuator  540 . Valve command  570  may be improved by means of command compensation, as discussed in greater detail below. In an exemplary embodiment, flow/velocity feedback controller  530  is a proportional variable deadband controller (PVDC) configured to implement a proportional variable deadband control technique. In other embodiments, the flow/velocity feedback controller  530  is a pattern recognition adaptive controller (PRAC), a model recognition adaptive controller (MRAC), or another type of tuning or adaptive feedback controller. In other embodiments, flow/velocity feedback controller  530  operates using state machine or proportional-integral-derivative (PID) logic. 
     Flow/velocity feedback controller  530  may be configured to output an actuator control signal (e.g., a DC signal, an AC signal) to valve actuator  540 . For example, valve actuator  540  may be a linear actuator (e.g., a linear proportional actuator), a non-linear actuator, a spring return actuator, or a non-spring return actuator. Valve actuator  540  may include a drive device coupled to valve  546  and configured to rotate a shaft of valve  546 . In various embodiments, valve  546  may be a 2-way or 3-way two position electric motorized valve, a ball isolation valve, a floating point control valve, an adjustable flow control device, or a modulating control valve. 
     Still referring to  FIG.  5   , feedback control system  500  is further shown to include a flow rate sensor  548 . Flow rate sensor  548  may be any desired style of flow rate sensor. For example, in various embodiments, flow rate sensor  548  may be an ultrasonic transducer flow sensor, a heated thermistor flow sensor, or a vortex-shedding flowmeter. In some embodiments, flow rate sensor  548  may be disposed upstream of valve  546  to measure the flow rate and/or velocity of fluid entering valve  546 . In other embodiments, flow rate sensor  548  may be disposed downstream of valve  546  to measure the flow rate and/or velocity of fluid exiting valve  546 . Once collected, measured flow rate and/or velocity data  542  from flow rate sensor  548  may be provided to flow/velocity feedback controller  530  of actuator device  502 . 
     Fluid (e.g., water, water/glycol solution) that passes through valve  546  may flow through coil  550 . In some embodiments, valve  546  is used to modulate an amount of heating or cooling provided to the supply air for building zone  506 . In various embodiments, coil  550  may be used to achieve zone setpoint temperature  516  for the supply air of building zone  506  or to maintain the temperature of supply air for building zone  506  within a setpoint temperature range. The position of valve  546  may affect the amount of heating or cooling provided to supply air via coil  550  and may correlate with the amount of energy consumed to achieve a desired supply air temperature. 
     It will be appreciated that system  500  as shown in  FIG.  5    is merely one example of a feedback control system in which the control techniques described herein can be implemented and that such techniques are applicable to a variety of different systems. For example, the control device responsible for transmitting control signals to valve actuator  540  (e.g., flow/velocity feedback controller) may be an external controller (i.e., outside of actuator  502 ). In some embodiments, both feedback signals from measured zone temperature  510  and measured flow rate/velocity  542  are received by an external controller, such as controller  504 . 
     Referring now to  FIGS.  6 A-B , high-level block diagrams of feedback control system  500  are depicted.  FIG.  6 A  is shown to depict a high-level diagram of the outer loop of feedback control system  500  as depicted in  FIG.  5    and  FIG.  6 B  is shown to depict a high-level diagram of the inner loop of feedback control system  500 , as shown in  FIG.  5   . 
     Command Compensation 
     Referring now to  FIG.  7 A , a high-level block diagram of flow control loop  700  is shown. In some embodiments, flow control loop  700  can be fully incorporated in system  500 . In various embodiments, the high-level functionality and configurations of elements can be incorporated into various embodiments of other systems or loops as described herein (e.g., system  500 , system  520 , flow control loop  700  as shown in  FIG.  12   , etc.). Loop  700  is shown to include first controller  524  and second controller  530 . First controller  524  and second controller  530  are referred to at a high level and may be referred to a temperature controller (e.g., zone temperature controller  524 , controller  504 , etc.) or flow/velocity feedback controller  530 , respectively. Loop  700  is shown to further include valve  546  and flow sensor  548 . Second controller  530  is shown to include command compensation block  702 , flow command generator  704 , and valve actuator  540 . Command compensation block  702  may be responsible for combining the flow commands from the first controller  524  and second controller  530  and is described in greater detail below. Flow command generator may include any processing component within a controller (e.g., second controller  530 ) responsible for generating a flow command (e.g., second flow command as shown in  FIG.  7 A ). In some embodiments, generating the flow command is based on flow rate data provided by flow sensor  548 . Second controller  530  is shown to include comparator  706 . Comparator  706  may be identical or substantially similar to comparator  520 . In some embodiments, comparator  706  takes in the flow rate setpoint form first controller  524  and the flow rate data from flow sensor  548  and generators a second flow command for command compensation block  702 . Details regarding various embodiments of the system shown in  FIG.  7 A  are detailed below. 
     Referring now to  FIG.  7 B , a flow control loop  700  including command compensation is shown. Flow control loop  700  may be incorporated fully into system  500 . Flow control loop  700  includes command compensation block  702  and which may act as a subsystem of flow/velocity feedback controller  530 . Command compensation block  702  is shown to be a signal processing block that inputs a combination of signals from zone temperature controller  524  and flow sensor  548 . In some embodiments, the functionality of command compensation block  702  is performed by flow/velocity feedback controller  530 . In other embodiments, command compensation block  702  is performed by an external controller, such as controller  504 . Command compensation block  702  can be performed by any controller within flow control loop  700 , and may be performed by a control device not shown in  FIG.  7 B . In the exemplified embodiment, command compensation block  702  inputs a linear combination of commands such that:
 
 û   v =αμ f +(1−α)μ v   (1)
 
Where u v  is the valve command  570 , û v  is the compensated valve command  706 , μ f  is the flow/velocity command  704  from the zone temperature controller  524 , and α is a scaling factor that ranges between 0 and 1.
 
     In some embodiments, the variable α is a parameter that allows for transitioning from using valve command  570  exclusively when we have reliable measurements from flow sensor  548  to incorporating flow/velocity command  704  when there are unreliable sensor readings from flow sensor  548 . In some embodiments, flow/velocity command  704  is incorporated into command compensation block  702  when the sensor experiences a fault. For example, a value of α=0 would allow valve actuator  540  to receive valve command  570  (e.g., no added command compensation); this case would happen when the flow readings from flow sensor  548  are measurable. Conversely, a value of α=1 would allow valve actuator  540  to only receive flow/velocity command  704  from zone temperature controller  524 ; this would be the case in the event of sensor faults, or when the flow rate is in the non-measureable region for an extended period of time; for these cases it is very easy to select the value of α. In another example, flow α=0.5 may allow valve actuator  540  to receive both valve command  570  and flow/velocity command  704  of equal or similar weight. 
     In some embodiments, the flow rate can become volatile. The flow rate may become volatile such that flow sensor  548  is measuring readable and unreadable flow rates within a short period of time, switching the value of α between 0 and 1 may create stability problems. For example, flow sensor  548  may measure the flow rate as 1.2 gallons per minute (gpm), which at or near the actual flow rate of the water (e.g., actual flow rate is 1.29 gpm). After a short period of time (e.g., &lt;2 seconds), flow sensor  548  may measure the flow rate as 0.0 gpm. The actual flow rate of the water may not be 0.0 gpm in this instance (e.g., actual flow rate may be 0.6 gpm), but the flow rate is below the minimum specifications of flow sensor  548  and therefore is measured at a value of 0.0 gpm. In other embodiments, the flow rate did not drop to 0.6 gpm but rather 1.25 gpm. In this exemplary embodiment, flow sensor  548  still measured the flow rate as 0.0 gpm, but this time the error was due to a sensor malfunction. For these and similar situations, implementing a value of α in between 0 and 1 may be beneficial. 
     Therefore, there may be at least two situations where a can be calculated: during normal operation (e.g., valve actuator  540  receiving valve command  570  as shown in  FIG.  6 B ), and the extreme cases (e.g., valve actuator  540  receiving compensated valve command  706  as shown in  FIG.  7 B ). Both situations may be differentiated since the value of α is calculated differently for each case. In order to ease differentiation, the parameter α will have a different name for each case. For example, under normal operation, the parameter will be called  13 , and during extreme cases it will be called γ. The value of γ will be calculated with an exponentially weighted moving average (EWMA) that moves between 0 and 1. The EWMA uses the token value a calculated at each sample time as 
                   α   =     {           1   ,     if   ⁢           y   f     ⁢         is   ⁢         unreliable                 0   ,     if   ⁢           y   f     ⁢         is   ⁢         reliable                       (   2   )               
and the parameter γ is updated as
 
     
       
         
           
             
               
                 
                   γ 
                   = 
                   
                     γ 
                     + 
                     
                       
                         1 
                         
                           T 
                           γ 
                         
                       
                       ⁢ 
                       
                         ( 
                         
                           α 
                           - 
                           γ 
                         
                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
     The time constant T γ  may be set to a time value (e.g., one day) in order to respond when flow sensor  548  is unable to measure the flow rate, when the sensor faults, or when the sensor starts reading flow again after not reading it for a period of time (e.g., more than 1 min., more than 10 min., etc.). 
     Referring now to  FIGS.  7 B-C  flow may be volatile, and flow readings from flow sensor  548  may vary greatly within a short period of time. In such an exemplary embodiment, β is used to represent α. The value of β is calculated from the portion of flow measured by the sensor. This portion depends on the flow profile and the minimum readable flow. Graph  710  of  FIG.  7 C  shows the profile of water flow through a valve controlled with perfect sensing (e.g., all values are being accurately read by flow sensor  548 ). 
     Graph  720  of  FIG.  7 D  shows a distribution of the water flow in valve  546  in an exemplary embodiment. The vertical lines in Graph  2  show the cumulative probability for several flow values. The cumulative probability for a given value gives the probability that the water flow is lower than that value, and this may be the same as the portion of the flow levels that cannot be measured. For example, a sensor with y min =0 gpm will have any water flow level be read by flow sensor  548 , making β=0. For y min =0:6 gpm, 20:52% of the water flow will not be read; thus, β=0:2052. For y min =1:2 gpm, β=0:4684; for y min =2:4 gpm, β=0:9936, and for y min =6 gpm, β=1. 
     In a general exemplary embodiment, a represents the weight for the combined control commands, β represents a parameter proportional to the flow in the non-measureable region, and γ represents the consistency of sensing. For example, a may begin at a value of zero when flow readings are reliable. As unreliable readings begin to get received by flow sensor  548 , the values of β and γ may begin to increase. In some embodiments, the β value is determined based on a cumulative probability (e.g., EWMA filter) for how much flow is in the non-measureable region. This β value may be a general proportion and may not change significantly over a long period of time (e.g., 1 day). When γ increases/decreases and reaches a value near 0 or 1, this may be representative of the consistency of readings received by flow sensor  548 . When the value for γ is near 0 or 1 (e.g., γ&gt;0.99; or γ&lt;1 0.01), the value of α may switch to the value of γ, as γ is now indicative of a consistently reliable or consistently unreliable flow rate. When the value for γ is not near 0 or 1, the flow rate measurements are not consistently reliable or consistently unreliable, and the value of alpha may equal the value of β. 
     In some embodiments, output compensation block  702  may be implemented within a processing circuit of flow/velocity feedback controller  530  as an algorithm. Pseudocode that may be implemented in such an algorithm is shown below.
         /*   Variables   y f : Flow sensor output   uf: Flow command   uv: Valve command   v: Compensated valve command   α: Weight for control commands   β: Proportion of .ow in non-measurable region   γ: Value that determines extreme sensing condition   τ α : Time constant of EWMA filter for α   τ β : Time constant of EWMA filter for β   τ γ : Time constant of EWMA filter for γ   α: Binomial token with values of 0 or 1   θ: Binomial token with values of β or γ   */   Initialization   α=0   β=0   γ=0   Command compensation   if y f  is unreliable then:       

                                                    a = 1               else               a = 0               end if                                   β   =     β   +       1     τ   β       ⁢     (     α   -   β     )                                                 γ   =     γ   +       1     τ   γ       ⁢     (     α   -   γ     )                                         if γ ≥ 0:99; or γ ≤ 0:01 then               θ = γ               else               θ = β               end if                                   α   =     α   +       1   τ     *     α   ⁡   (     θ   -   a     )                                         û f  = αu f  + (1 − a)u v                          
Command Compensation Process
 
     Referring now to  FIGS.  8 A-B , a flow diagram of a process for optimizing the command compensation is shown, according to an exemplary embodiment. Process  800  can be initiated by various controllers in a building system. In some embodiments, process  800  is performed within a processing circuit of flow/velocity feedback controller  530 . 
     Referring now to  FIG.  8 A , an exemplary embodiment of process  800  is shown.  FIG.  8 A  may be a detailed representation of process  800 . Process  800  is shown to include clearing data (step  802 ). In some embodiments, process  800  clears any and all variables (e.g., variables, parameters, token parameters, etc.) before implementing command compensation. Process  800  includes determining if the sensor is reliable (step  804 ). This step may determine if flow sensor  548  is receiving reliable flow measurements. The purpose of the command compensation may be to produce a linearly combined signal to send to valve actuator  540  that represents the necessary amount of flow compensation required, based upon the reliability of the flow sensor  548  over a given period of time. As such, sensor reliability may need to be continuously tested (e.g., tested in real-time) to ensure reliability is consistently and, if not, adjust accordingly. In some embodiments, reliability is determined by maintaining a certain rate of accurate readings over a given period of time. For example, flow sensor  548  receiving a flow reading of −5.4 gpm, 0.0 gpm, or 1,000 gpm may be considered unreliable. Further detail on reliability is discussed in greater detail below. 
     Process  800  is shown to include determining that flow sensor  548  is unreliable (step  806 ). When flow sensor  548  receives an unreliable measurement (e.g., 0.0 gpm, 5000 gpm, etc.), a token placeholder (e.g., “a”) may be incremented to a value of 1. The token parameter may not be used directly in the command compensation and is only responsible for adjusting the result of the EWMA filter. Process  800  is shown to include determining that flow sensor  548  is reliable (step  808 ). When flow sensor  548  receives a reliable measurement, a token parameter (e.g., “a”) the value for the token placeholder may remain at zero. The token parameter may not be used directly in the command compensation and is only responsible for helping in calculating results from the EWMA filters. 
     Process  800  is shown to include implementing an EWMA for β and γ (step  810 ). In some embodiments, if sensor  548  is reading most of the flow samples by a significant majority or almost none of the flow samples by a significant majority, the optimal scaling factor for a would be 0 or 1, respectively. In some embodiments, a “significant majority” can vary and will depend on the purpose of the implemented system. Since the γ value is a weighted average of previous recordings that indicates the reliability of the sensor, a cutoff point may need to be established to determine the point at which switching the value of α to 0 or 1 when the sensor is significantly reading all or none of the values, respectively, is ideal. In some embodiments, a cutoff point is established with the variable θ shown below: 
                   θ   =     {           1   ,       if   ⁢         γ     ≥   0.99                 0   ,       if   ⁢         γ     ≤   0.01                 β   ,   otherwise                     (   4   )               
Using the token parameter θ to scale α allows the command compensation to output the optimal control signals to valve actuator  540  when dealing in the extreme cases of consistent reliability or consistent unreliability. The use of token parameter θ is described in greater detail below. The EWMA filter responsible for averaging β values may include the equation shown below. The equation for averaging γ values may look similar. After the token parameter has been adjusted, an EWMA for each β and γ may need to be implemented and average based on a new data set (e.g., original set+1), and adjust β and γ accordingly.
 
     
       
         
           
             
               
                 
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     Process  800  is shown to include determining if γ≥0.99 or ≤0.11 (step  812 ). In some embodiments, if γ is greater than 0.99 or less 0.01, this is indicative of consistently reliable or consistently unreliable measurements. The bounds for consistency (e.g., 0.01 and 0.99) may not always be 0.01 and 0.99 and may be higher/lower. For example, the bounds for γ may be 0.10 and 0.90. 
     Process  800  is shown to include determining that γ is not outside of the bounds for consistency (step  814 ). In this step, a second token parameter may be introduced that takes the value of either β or γ. When γ is not outside the bounds for consistency, a second token parameter (e.g., θ) takes on the value of γ. Process  800  is shown to include determining that γ is outside of the bounds for consistency (step  814 ). In this step, θ takes on the value of β. 
     Process  800  is shown to include implementing an EWMA for a (step  818 ). The value of θ is incorporated in the EWMA to incrementally move the value of α towards a more proportional and accurate value. Process  800  is shown to include compensating the command signal to valve actuator  540  using the α value as the weight for the combined control signals (step  820 ). Once the value of α has been determined, valve command  570  is compensated with flow velocity command  704  and proportionally weighted based on the value of α. 
     Referring now to  FIG.  8 B , an exemplary embodiment of process  800  is shown.  FIG.  8 B  shows a high-level representation of process  800 , which is described in greater detail in  FIG.  8 A . Process  800  is shown to include determining whether flow sensor  548  is reliable (step  850 ). 
     Process  800  is shown to include setting the parameter values (step  852 ). In some embodiments, parameter values may refer to scaling factors (e.g., a) for the linear combination of signals from one or more controllers in the command compensation block  702 . In other embodiments, parameter values may refer to placeholder variables (e.g., a, Θ, etc.) that indirectly scale the linear combination of signals. In the exemplified embodiment, observation at a single instance in time may appear evident that the flow sensor  548  is either working reliably or unreliably. When flow sensor  548  is observed over a period of time (e.g., 1 day), the rate at which the sensor is reliable can change over time. This may be due to environmental conditions (e.g., pressure changes in the water, flow sensor noise, building disturbances, set point error, etc.). As such, a process may be implemented to compensate for these changes. In some embodiments, step  852  initializes three variables: α, β, and γ, wherein a represents the scaling factor shown in Equation (1), β represents a parameter proportional to the flow in the non-measureable region, and γ represents the consistency of sensing. Upon determining whether the sensor is reliable or unreliable, α may be set to 1 or 0, respectively. 
     Process  800  is shown to include implementing an averaging process (step  854 ). Command compensation may be implemented in real-time, and samples (e.g., flow readings) may be taken by at a certain time interval. In some embodiments, exponentially weighted moving averages (EWMA) may be implemented wherein the weighting decreases exponentially with each previous sample. Equations for this process can be shown below: 
                   β   =     β   +       1     T   β       ⁢     (     a   -   β     )                 (   6   )                           γ   =     γ   +       1     T   γ       ⁢     (     a   -   γ     )                 (   7   )               
In some embodiments, T y  and T β  can be shown to represent a time variable. In one example, the time interval for T γ  is relatively small to T β , as the γ value needs to be updated through a EWMA at a rate fast enough to give accurate readings on the reliability of the sensor. For example, T y  may be set at 60 seconds while T β  is set at 1 day. However T β  represents the general proportion of flow in the non-measurable region and may not need to change as quickly. Due to the continuous-time nature of the command compensation, samples are being taken at a certain time interval. In some embodiments, exponentially weighted moving averages (EWMA) may be implemented wherein the weighting decreases exponentially with each previous sample. An equation for this process can be shown below:
 
                   α   =     α   +       1     T   α       ⁢     (     θ   -   α     )                 (   8   )               
Where T α  represents a time interval small enough to achieve accurate values from the EWMA (e.g., 1 minute).
 
     Process  800  is shown to include updating the value for a (step  856 ). In some embodiments, α is updated by implementation of an EWMA filter based on the value of θ. Process  800  is shown to include compensating the command signal using the value of α as the weight for the combined control signals (step  858 ). Once the value of α has been determined, valve command  570  is compensated with flow velocity command  704  and proportionally weighted based on the value of α. 
     Command Compensation Solutions 
     Referring now to  FIG.  9   , a graph  900  showing the variations of scaling factors for command compensation block  702  is shown, according to an exemplary embodiment. Graph  900  is shown to include vertical axis  902  and horizontal axis  904 . Vertical axis  902  shows the magnitude of the variables α, β, and γ, on a scale from 0 to 1. Horizontal axis  904  shows a time axis in seconds. Graph  900  is shown to include first time  912 , second time  914 , and time interval  920  on horizontal axis  904 . First time  912  and second time  914  are arbitrary times for the exemplified embodiment, and time interval  965  between them may be established at any rate. In some embodiments, graph  900  may show the variations of one or all scaling factors processed in the command compensation block  702 . 
     Graph  900  is shown to include α line  906 , β line  908 , and γ line  910 . Line  906  represents the change in the α scaling factor over the time interval  965 . Line  908  represents the change in the θ scaling factor over the time interval  965 . Line  910  represents the change in the γ scaling factor over the time interval  920 . Graph  900  is also shown to include lower cutoff value  916  and upper cutoff value  918 . Lower cutoff value  916  represents the point at which a will switch to a value of 0 when the lower cutoff value  916  is reached by γ. Upper cutoff value  918  represents the point at which a will switch to a value of 1 when the upper cutoff value  918  is reached by γ. 
     In some embodiments, graph  900  represents a time-varying representation of how the three scaling factors in command compensation block  702  change over time. In one example, flow sensor  610  may be operating reliably prior to first time  912 . At or around first time  912 , flow sensor  548  begins to malfunction, resulting in an increase in γ. When this occurs, a may switch from the value of 0, representing reliability, to the value of 0 after passing the lower cutoff value  916 . The α value may not directly jump to the value of 1, as a constant switch between 0 and 1 can cause issues in the zone temperature controller  524  or flow controller  604  or both. Instead, the α value will remain at the 0 value until γ reaches the upper cutoff value  918 . At this point, the system has been operating unreliably for a significant amount of time and the α value will switch to 1. The values of α, β, and γ may be calculated by means of EWMA&#39;s. This may be especially true for the value of γ, as a weighted average of this value indicated how reliable or unreliable the system has been over time interval  965 , allowing the α value to be optimized in the extreme cases. 
     Still referring to  FIG.  9   , the performance of the command compensation algorithm may be tested with a simulation of building zone  506 . In some embodiments, the system is perturbed with setpoint changes in zone temperature, pressure changes in the control valve (e.g., valve  546 ) and disturbances in the building caused by changes in occupancy. The performance of the system may be evaluated first when flow sensor  548  can measure any amount of flow (y min =0 gpm), and then it is compared to how it changes for different values of y min . 
     In an exemplary embodiment, the values of y min  tested are 0, 5, 10, 20 and 50% of the maximum value flow sensor  548  can read (e.g., y max =12 gpm). This may be written as y min =[0; 0:6; 1:2; 2:4; 6] gpm. The time constants of the EWMAs for the calculation of a in are: τ α =60 sec., T γ =60 sec., τ β =86400 sec (e.g., 1 day). 
     In some embodiments, the performance metrics calculated are the average setpoint error, and average actuator effort. The average setpoint error is calculated as 
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and the average effort in the actuator, calculated as
 
     
       
         
           
             
               
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     In these equations, the terms r T,k , y T,k  and û v,k  correspond to the temperature setpoint, temperature measurement and compensated valve command at each sample time k, respectively. The term N may be the number of samples used to calculate the averages. In some embodiments, the simulation is sampled every 1 second and is run for 5 days, but only the last 3 days of data collected are used to calculate the performance metrics in order to let the controllers achieve stable tuning parameters; this makes N=259201. 
     Referring now to  FIG.  10   , a simulation result  1000  is shown. Simulation result  1000  shows the change in temperature of building zone  506  over a period of time and is shown to include experimental data lines  1002 , theoretical data line  1004 , and legend  1006 . In some embodiments, simulation result  1000  shows the results of implementing the command compensation block  702 , as depicted in  FIGS.  7 - 8 B . 
     In one example, the performance of the command compensation block  702  is tested with a simulation of feedback control system  500 . The simulation is made to include system disturbances by means of set point error, pressure changes in valve  546 , and building disturbances (e.g., building deterioration, fires, etc.). The simulation shows temperature of building zone  506  when flow sensor  548  is able to measure any amount of flow (i.e., no lower cutoff value) and when flow sensor  548  has various different minimum readable values (dashed lines). Legend  1006  shows a plurality of different minimum sensor specifications for flow sensor  548 . As shown in simulation result  1000 , the command compensation block may appear successful as temperature from experimental data lines  1002  appears to converge to temperature from theoretical data line  1004  after overshoot. As depicted by theoretical data line  1004 , flow sensor  548  is always operating reliably, allowing the command compensation block  702  to maintain a constant scaling factor 0. This may allow the command compensation block  702  to only input signals from flow/velocity feedback controller  530 , allowing for smoother temperature changes. Experimental data lines  1002  are shown to represent flow sensor  548  operating reliably at varying rates, allowing command compensation block  702  to implement command compensation. 
     Referring now to  FIG.  11   , a flow diagram of process  1100  for controlling the temperature of an HVAC system by means of command compensation is shown, according to an exemplary embodiment. Process  1100  may represent a high-level process of implementing command compensation within system  500 . Process  1100  can be performed by various controllers in a building control system. For example, process  1100  can be implemented by flow control loop  700 , as shown in  FIGS.  7 A-B . 
     Process  1100  is shown to include establishing a temperature control system comprising a valve, an actuator coupled to the valve, and a sensor configured to monitor water flow through the valve (step  1102 ). Step  1102  may be implemented as system  500 . In some embodiments, step  1102  includes establishing valve  546 , actuator  502 , and flow sensor  548 . 
     Process  1100  is shown to include configuring a first controller to monitor temperature of a building zone and establish a setpoint (step  1104 ). This step may be performed by controller  504  or zone temperature controller  524 . In some embodiments, these two controllers are not separate in functionality and output a single command to flow/velocity span block  526 . 
     Process  1100  is shown to include configuring the second controller to monitor fluid flow through the valve (step  1106 ). This step may be performed by flow/velocity feedback controller  530 . 
     Process  1100  is shown to include sending an added command to the actuator in an attempt to reach the setpoint, wherein the added command is a linear combination of a first command from the first controller and a second command from the second controller (step  1108 ). This step may be performed by a control application (e.g., command compensation block  702 ) communicably coupled to the actuator, wherein the added command adjusts a valve based on the reliability of a sensor. In some embodiments, an added signal from zone temperature controller  524  and flow/velocity feedback controller  530  may be sent to valve actuator  540  to adjust valve  546 . 
     Referring now to  FIG.  12   , another embodiment of loop  700  is shown, according to some embodiments.  FIG.  12    is shown to include a variety of system disturbances, including setpoint changes  1204 , pressure changes  1206 , building disturbances  1208 , and flow sensor noise  1210 . System disturbances  1204 - 1210  may be directed to various disturbances that produce noise, or other unwanted information within control system signals (e.g., feedback signals, temperature setpoints, flow setpoints, control signals, etc.). Loop  700  is further shown to include zone model  1202  and ZNT sensor noise  1212 . In some embodiments, Zone model  1202  is a virtual representation of a building zone that may be used as part of a simulation for system  700 . ZNT sensor noise may be an additional system disturbance, such as pressure changes  1206 . In some embodiments, ZNT sensor noise is virtual noise implemented for zone model  1202  to represent noise in a simulated environment. 
     The above figures may disclose a way to overcome the inability of flow sensors to measure low flows in a cascaded control system. The method combines linearly the commands given by the controllers in the inner and outer loops, which in some embodiments are flow and temperature controllers. By performing this combination, a process can transition from controlling a valve exclusively with the flow controller, to controlling it with the temperature controller when the flow sensor provides unreliable measurements or it completely fails. Simulations can show the process is tacks setpoint and disturbances at the expense of actuator effort. Although this process may be applied to a cascaded temperature control system, the compensation method can potentially be applied to any cascaded control system. 
     In some embodiments, a benefit of having the inner loop that can perform pressure rejection in flow control decreases as the outer command is used more. This may happen because the outer controller provides most of the control command to the valve, and it will take longer to reject disturbances in the inner loop since the disturbance effects have to be manifested in the outer loop before the outer controller takes a corrective action. However, the command from the outer controller will be used more only when a sensor in the inner loops has failed to provide reliable measurements; this situation is equivalent to having an inner open loop. 
     Configuration of Exemplary Embodiments 
     The construction and arrangement of the systems and methods as shown in the various exemplary embodiments are illustrative only. Although only a few embodiments have been described in detail in this disclosure, many modifications are possible (e.g., variations in sizes, dimensions, structures, shapes and proportions of the various elements, values of parameters, mounting arrangements, use of materials, colors, orientations, etc.). For example, the position of elements can be reversed or otherwise varied and the nature or number of discrete elements or positions can be altered or varied. Accordingly, all such modifications are intended to be included within the scope of the present disclosure. The order or sequence of any process or method steps can be varied or re-sequenced according to alternative embodiments. Other substitutions, modifications, changes, and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present disclosure. 
     The present disclosure contemplates methods, systems and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure can be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions. 
     Although the figures show a specific order of method steps, the order of the steps may differ from what is depicted. Also two or more steps can be performed concurrently or with partial concurrence. Such variation will depend on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations could be accomplished with standard programming techniques with rule based logic and other logic to accomplish the various connection steps, processing steps, comparison steps and decision steps.