Abstract:
A control system ( 300 ) for optimizing a power plant includes a chemical loop having an input for receiving an input signal ( 369 ) and an output for outputting an output signal ( 367 ), and a hierarchical fuzzy control system ( 400 ) operably connected to the chemical loop. The hierarchical fuzzy control system ( 400 ) includes a plurality of fuzzy controllers ( 330 ). The hierarchical fuzzy control system ( 400 ) receives the output signal ( 367 ), optimizes the input signal ( 369 ) based on the received output signal ( 367 ), and outputs an optimized input signal ( 369 ) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present invention claims the benefit of co-pending U.S. Provisional Patent Application Ser. No. 61/033,202, entitled “CONTROL AND OPTIMIZATION SYSTEM”, co-pending U.S. Provisional Patent Application 61/033,210, entitled “FUZZY LOGIC CONTROL AND OPTIMIZATION SYSTEM”, and co-pending U.S. Provisional Patent Application Ser. No. 61/033,185, entitled “INTEGRATED CONTROLS DESIGN OPTIMIZATION”, all of which are incorporated herein by. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     The U.S. Government has rights in this invention pursuant to Contract No. DE-FC26-07NT43095 awarded by the U.S. Department of Energy. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates generally to a control and optimization system and, more particularly, to a hierarchical fuzzy logic control and optimization system for solids transport in a circulating fluidized bed system or a chemical looping system. 
     BACKGROUND 
     Fluidized bed combustion (FBC) is a combustion technology used in power plants, primarily to burn solid fuels. FBC power plants are more flexible than conventional plants in that they can be fired on coal, coal waste or biomass, among other fuels. In general, FBC power plants evolved from efforts to find a combustion process able to control pollutant emissions without external emission controls (such as scrubbers). Although FBC power plants have lower pollutant emissions than conventional combustion plants, ongoing efforts continually strive to reduce pollutant emissions to even lower levels. 
     Chemical looping (CL) is another combustion technology which can also be utilized in electrical power generation plants which burn fuels such as coal, coal waste, biomass, and other opportunity fuels. The CL process can be implemented in existing or new power plants, and provides promising improvements in terms of reduced plant size, reduced emissions, and increased plant operational efficiency, among other benefits. 
     A typical CL system utilizes a high temperature process, whereby solids such as calcium- or metal-based compounds, for example, are “looped” between a first reactor, called an oxidizer, and a second reactor, called a reducer. In the oxidizer, oxygen from air injected into the oxidizer is captured by the solids in an oxidation reaction. The captured oxygen is then carried by the oxidized solids to the reducer to be used for combustion and/or gasification of a fuel such as coal, for example. After a reduction reaction in the reducer, the solids, no longer having the captured oxygen, are returned to the oxidizer to be oxidized again, and the cycle repeats. 
     The CL process is more complicated than processes of other plants such as conventional circulating fluidized bed (CFB) plants, for example. In particular, control of circulating solids in the CL process requires multi-loop interactive flow and inventory controls which are not required in traditional plants. As a result, traditional plant controls applied to the CL process necessarily result in separate control loops for each CL loop. However, using separate control loops for each CL loop is inefficient and does not optimize performance of the CL process, since accurate control requires coordinated control of parameters between individual loops. Interactions between variables for each loop of the CL process have to be taken into account to optimize overall CL process performance. Solids flow between loops, for example, is particularly difficult to regulate, due a large number of nonlinear, interrelated variables associated with the solids flow. More specifically, oscillation coupling between loops of a multiple-loop CL-based plant, for example, disrupts flow and makes solids inventory regulation thereof difficult. Also, crossover flows interact with main, e.g., recirculation, flows of opposite loops, thereby complicating overall regulation of solids transport with each respective loop. 
     Control and optimization tools which have been developed thus far are focused on controlling and optimizing conventional combustion power plants. As a result, these tools have been focused on solving very specific, localized problems rather than global control and optimization of complex plant operations. 
     Control systems using conventional process controls based on fuzzy set theory (fuzzy logic) have been developed to help overcome some the problems described above. Fuzzy set theory is based on rule-based decision making which emulates a “rule of thumb” reasoning process similar to that of human thought and decision making. However, conventional fuzzy set theory control systems are limited in the number rules which can be memorized, since an excessive number of rules overburdens the fuzzy logic decision making process, effectively obviating the advantages of using fuzzy logic. Thus, as power plant designs evolve and processes thereof become more complex, such as with CL-based power plants described above and, specifically, with multi-loop CL-based power plants, the number of variables involved increases dramatically. As a result, a number of required rules becomes unacceptable, and conventional fuzzy set theory control systems are thereby unable to optimally or efficiently control certain processes, such as solids transport, for example, of a CL-based power plant. 
     Accordingly, it is desired to develop a control and optimization system for solids transport, for example, in a CFB system or a CL system which overcomes the shortfalls described above. 
     SUMMARY 
     According to the aspects illustrated herein, there is provided a control system for optimizing a power plant. The control system includes a chemical loop having an input for receiving an input signal and an output for outputting an output signal, and a hierarchical fuzzy control system operably connected to the chemical loop. The hierarchical fuzzy control system includes a plurality of fuzzy controllers. The hierarchical fuzzy control system receives the output signal, optimizes the input signal based on the received output signal, and outputs an optimized input signal to the input of the chemical loop to control a process of the chemical loop in an optimized manner. 
     According to the other aspects illustrated herein, a control system for optimizing a power plant includes a first chemical loop having a first input for receiving a first input signal and a first output for outputting a first output signal, and a hierarchical fuzzy control system operably connected to the first chemical loop and having a plurality of fuzzy controllers. The first chemical loop includes a first reactor having at least a first inlet and a first outlet, a first separator operably connected to the first outlet of the first reactor, and a first seal pot control valve disposed between the first separator and the first inlet of the first reactor. The hierarchical fuzzy control system receives the output signal, optimizes the input signal based on the received output signal, and outputs an optimized input signal to the input of the chemical loop to control a process of the chemical loop in an optimized manner. 
     According to yet other aspects illustrated herein, a control system for optimizing a power plant includes a first chemical loop having a first input for receiving a first input signal and a first output for outputting a first output signal. The first chemical loop includes a first reactor having at least a first inlet and a second outlet, a first separator operably connected to the first outlet of the first reactor, and a first seal pot control valve disposed between the first separator and the first inlet of the first reactor. 
     The control system further includes a second chemical loop having a second input for receiving a second input signal and a second output for outputting a second output signal. The second chemical loop includes a second reactor having at least a second inlet and a second outlet, a second separator operably connected to the second outlet of the second reactor, and a second seal pot control valve disposed between the second separator and the second reactor inlet. The control system further includes a first crossover leg in fluid communication with the first seal pot control valve of the first chemical loop and the second reactor inlet of the second chemical loop, a second crossover leg in fluid communication with the second seal pot control valve of the second chemical loop and the first reactor inlet of the first chemical loop, and a hierarchical fuzzy control system. 
     The hierarchical fuzzy control system includes a global fuzzy controller, a first fuzzy controller operably connected to the global fuzzy controller, a second fuzzy controller operably connected to the global fuzzy controller, a third fuzzy controller operably connected to the global fuzzy controller, and a fourth fuzzy controller operably connected to the global fuzzy controller. The global fuzzy controller controls an operation of the first fuzzy controller, the second fuzzy controller, the third fuzzy controller and the fourth fuzzy controller. At least one of the first fuzzy controller, the second fuzzy controller, the third fuzzy controller and the fourth fuzzy controller receives one of the first output signal and second output signal, optimizes one of the first input signal and second input signal based on the received one of the first output signal and second output signal, and outputs an optimized one of the first input signal and second input signal to one of the first chemical loop and the second chemical loop. 
     The hierarchical fuzzy control system optimizes at least one of a recirculation solids flow in the first chemical loop, a crossover solids flow from the first chemical loop to the second chemical loop through the first crossover leg, a recirculation solids flow in the second chemical loop, and a crossover solids flow from the second chemical loop to the first chemical loop through the second crossover leg. 
     The above described and other features are exemplified by the following figures and detailed description. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Referring now to the figures, which are exemplary embodiments, and wherein the like elements are numbered alike: 
         FIG. 1  is a block diagram of a CL combustion-based steam power plant; 
         FIG. 2  is a block diagram of two interconnected loops of a CL system; 
         FIG. 3  is a block diagram of single fuzzy logic controller; and 
         FIG. 4  is block diagram of a hierarchical fuzzy logic control system; and 
         FIG. 5  is a block diagram which shows a hierarchical fuzzy logic control system utilized with a CL system. 
     
    
    
     DETAILED DESCRIPTION 
     Disclosed herein is a hierarchical fuzzy logic control and optimization system. More specifically, the hierarchical fuzzy logic control and optimization system in an exemplary embodiment is utilized in a dual loop chemical looping (CL) system of a CL-based power plant to optimally controlling solids transport therein. However, alternative exemplary embodiments are not limited thereto. For example, the hierarchical fuzzy logic control and optimization system may be utilized in a circulating fluidized bed (CFB) system or, alternatively, may be utilized in single or multiple (e.g., two or more) loop CL systems. 
     Referring to  FIG. 1 , a CL system  5  shown is similar to that described in U.S. Patent No. 7,083,658, which is incorporated herein by reference. The CL system  5  includes a first reactor  10 , e.g., a reducer  10 , and a second reactor  20 , e.g., an oxidizer  20 . Air  30  is supplied to the oxidizer  20 , and calcium (Ca)  40 , such as limestone, is oxidized therein to produce a calcium oxide (CaO)  50 . The CaO  50  is supplied to the reducer  10  via a separator  52  and a seal pot control valve (SPCV)  55 , and acts as a carrier to deliver oxygen to fuel  60  (such as coal  60 , for example) supplied to the reducer  10 . As a result, the oxygen delivered to the reducer  10  interacts with the coal  60  in the reducer  10 , and reduced calcium oxide is then returned to the oxidizer  20  to again be oxidized into CaO  50 , and the cycle described above repeats. 
     Oxidation gas  70 , such as nitrogen gas (N 2 )  70 , extracted from the air  30  during oxidation, as well as heat (not shown) produced during oxidation, exit the oxidizer  20 . Likewise, a gas  80  produced during reduction in the reducer  10  exits the reducer  10 . The gas  80  includes, for example, a synthesis gas (syngas)  80 , hydrogen gas (H 2 )  80 , and/or carbon dioxide gas (CO 2 )  80 . Composition of the gas  80 , e.g., proportions of the syngas  80 , the H 2    80 , and/or the CO 2    80  therein, varies based upon a ratio of the coal  60  to the air  30 . 
     Exemplary embodiments are not limited to two loops, as described above with reference to  FIG. 1 , but instead may include either a single loop or more than two loops. For example, in an alternative exemplary embodiment, the CL system  5  includes a third loop (not shown), such as a calciner loop, for example, which allows H 2  generation from reformed syngas  80 . 
     The CL system  5  according to an exemplary embodiment further includes a thermal loop  90 . The thermal loop  90  includes a steam turbine  95  which drives a power generator  100  using steam  105  generated by boiling feedwater  110  with heat produced during oxidation in the oxidizer  20 . 
     Waste  115 , such as ash  115 , is removed from the oxidizer  20  for disposal in an external facility (not shown). The coal  60 , as well as limestone  120  containing calcium carbonate (CaCO 3 ) and recirculated steam  125 , are supplied to the reducer  10  for the reduction reaction therein. 
     While a calcium oxide based CL system has been described, the present invention is also applicable to a metal oxide based CL system similar to that described in U.S. patent application Ser. No. 10/542,749, which is incorporated herein by reference. 
     In operation, the reduction reaction occurs between carbon and sulfur in the coal  60 , the CaCO 3  in the limestone  120 , and the CaO  50 . The reduction reaction produces the Ca  40 , which is separated by the separator  52  and is thereafter supplied to the oxidizer  20  through the SPCV  55 . In an exemplary embodiment, the Ca  40  is calcium sulfide (CaS)  40  and the separator  52  is a cyclone separator  52 , but alternative exemplary embodiments are not limited thereto. The CaS  40  is then oxidized in an oxidation reaction in the oxidizer  20 , thereby producing the CaO  50 , which is separated from the oxygen gas  70  (e.g., the N 2    70 ) by a separator  52  and is supplied back to the reducer  10  via a SPCV  55 . The oxidation reaction produces the heat which boils the feedwater  110  into the steam  105  which is supplied to the steam turbine  95 . 
     Hereinafter, the reducer  10 , the separator  52  connected to the reducer  10 , the SPCV  55  connected thereto, and associated piping connecting the aforementioned items together, e.g., forming a fluidly-connected “loop” therewith, will be referred to as a first loop  200   a  ( FIG. 2 ). Likewise, the oxidizer  20 , the separator  52  connected to the oxidizer  20 , the SPCV  55  connected thereto, and associated piping connecting the aforementioned items will be referred to as a second loop  200   b  ( FIG. 2 ). As will be described in further detail with reference to  FIG. 2 , a portion of the Ca  40  which exits the reducer  10  through the separator  52  is recirculated back to the reducer  10 , e.g., is not sent to the oxidizer  20 , by the SPCV  55 , based, for example, on a differential pressure between the reducer  10  and the oxidizer  20 . Similarly, a portion of the CaO  50  which exits the oxidizer  20  is recirculated back to the oxidizer  20  instead of being sent to the reducer  10 . For purposes of discussion herein, transport of solids such as the Ca  40  and the CaO  50  within a given loop, e.g., recirculation, will be referred to as “recirculation solids transport,” while transport of solids such as the Ca  40  and the CaO  50  between different loops, e.g., between the first loop  200   a  and the second loop  200   b  ( FIG. 2 ), will be referred to as “crossover solids transport.” Recirculation solids transport and crossover transport are collectively referred to as “solids transport.” 
     Referring now to  FIG. 2 , the first loop  200   a  includes a first reactor  10 , a separator  52   a , and an SPCV  55   a . An upper pipe  205   a  connects the first reactor  10  to the separator  52   a , while a dip leg  207   a  is connected between the separator  52   a  and an input of the SPCV  55   a . A lower pipe  210   a  connects an air source  215   a  to both the first reactor  10  and a return leg  220   a . In addition, the return leg  220   a  is connected between the lower pipe  210   a  and a first output of the SPCV  55   a , as shown in  FIG. 2 . 
     Similarly, the second loop  200   b  includes a second reactor  20 , a separator  52   b , and an SPCV  55   b . An upper pipe  205   b  connects the second reactor  20  to the separator  52   b , while a dip leg  207   b  is connected between the separator  52   b  and an input of the SPCV  55   b . A lower pipe  210   b  connects an air source  215   b  to both the second reactor  10  and a return leg  220   b . Further, the return leg  220   b  is connected between the lower pipe  210   b  and a first output of the SPCV  55   b.    
     The first loop  200   a  further includes a crossover leg  225   a  which connects a second output of the SPCV  55   a  to the lower pipe  210   b  of the second loop  200   b , while the second loop  200   b  further includes a crossover leg  225   b  which connects a second output of the SPCV  55   b  to the lower pipe  210   a  of the first loop  200   a.    
     In an alternative exemplary embodiment, the air sources  215   a  and  215   b  may be combined, e.g., into a single air source (not shown) which supplies both the first loop  200   a  and the second loop  200   b  with air. 
     During operation of a CL-based power plant, for example, having the first loop  200   a  and the second loop  200   b , solids in the first loop  200   a  flow upward through the first reactor  10 , into the upper pipe  205   a , and then into the separator  52   a . In the separator  52   a , the solids are separated from gas  80  ( FIG. 1 ) and thereafter flow downward into the SPCV  55   a  via the inlet of the SPCV  55   a . Recirculation solids, e.g., a portion of the solids in the SPCV  55   a  which flow out of the SPCV  55   a  (through the first outlet thereof) to the return leg  220   a  to be mixed with air  30  ( FIG. 1 ) from the air source  215   a , causes the recirculation solids to be recirculated back to the first reactor  10  (recirculation solids transport). 
     On the other hand, solids in the SPCV  55   a  which are not recirculated, e.g., crossover solids, flow out of the SPCV  55   a  (through the second outlet thereof) and are thus supplied to the lower pipe  210   b  of the second loop  200   b . Crossover solids are thereby delivered to the second reactor  20  (crossover solids transport). 
     In a similar manner, solids flow in the second loop  200   b  includes recirculation solids transport within the second loop  200   a  and crossover solids transport to the first loop  200   a.    
     In an exemplary embodiment, relative proportions of solids in each of the recirculation solids transport and the crossover solids transport of both the first loop  200   a  and the second loop  200   b , e.g., sizes of the portions of solids either recirculated or supplied to another loop, are controlled based upon an amount of air supplied to an associated SPCV  55   a  or SPCV  55   b . More specifically, recirculation air control valves  230   a  and  230   b  control recirculation solids transport in the first loop  200   a  and the second loop  200   b , respectively, while crossover air control valves  235   a  and  235   b  control crossover solids transport in the first loop  200   a  and the second loop  200   b , respectively. A control system  300  provides control signals to the recirculation air control valves  230   a  and  230   b  and the crossover air control valves  235   a  and  235   b.    
     Specifically, the control system  300  according to an exemplary embodiment provides a first control signal  305  to the recirculation air control valve  230   a , a second control signal  310  to the crossover air control valve  235   a , a third control signal  315  to the recirculation air control valve  230   b , and a fourth control signal  320  to the crossover air control valve  235   b , but alternative exemplary embodiments are not limited thereto. For example, the control system  300  may provide control signals (not shown) which control an air flow from the air source  215   a  and/or the air source  215   b , as well as a flow of the fuel  60  ( FIG. 1 ), the limestone  120  ( FIG. 1 ), and/or the recirculation steam  125  ( FIG. 1 ). In additional, control signals of the control system  300  according to alternative exemplary embodiments will be described in further detail below with reference to  FIGS. 3 through 5 . 
     Still referring to  FIG. 2 , the control signals according to an exemplary embodiment will now be described in further detail. The first control signal  305  is based upon a difference between a differential pressure (D/P) across the dip leg  207   a  and a D/P across the first reactor  10 . More specifically, the first control signal  305  adjusts air flow from the air source  215   a  through the recirculation air control valve  230   a  to regulate recirculation solids transport in the first loop  200   a  based upon both the difference between the D/P across the dip leg  207   a  and the D/P across the first reactor  10  and fuzzy logic rules (described in greater detail below). 
     The second control signal  310  according to an exemplary embodiment is based upon a difference between a D/P across the crossover leg  225   a  and a D/P between the lower pipe  210   a  and the lower pipe  210   b . More specifically, the second control signal  310  adjusts air flow from the air source  215   a  through the crossover air control valve  235   a  to regulate crossover solids transport from the first loop  200   a  to the second loop  200   b  based upon both the difference between the D/P across the crossover leg  225   a  and the D/P between the lower pipe  210   a  and the lower pipe  210   b , as well as fuzzy logic rules. 
     The third control signal  315  is based upon a difference between a D/P across the dip leg  207   b  and a D/P across the second reactor  20 . More specifically, the third control signal  315  adjusts air flow from the air source  215   b  through the recirculation air control valve  230   b  to regulate recirculation solids transport in the second loop  200   b  based upon both the difference between the D/P across the dip leg  207   b  and the D/P across the second reactor  20  and fuzzy logic rules. 
     The fourth control signal  320  according to an exemplary embodiment is based upon a difference between a D/P across the crossover leg  225   b  and a D/P between the lower pipe  210   b  and the lower pipe  210   a . More specifically, the fourth control signal  320  adjusts air flow from the air source  215   b  through the crossover air control valve  235   b  to regulate crossover solids transport from the second loop  200   b  to the first loop  200   a  based upon both the difference between the D/P across the crossover leg  225   b  and the D/P between the lower pipe  210   b  and the lower pipe  210   a , as well as fuzzy logic rules. 
     It will be noted that the control signals are not limited to those described herein. For example, control signals according to alternative exemplary embodiments may encompass other controllable parameters, such as temperatures, pressures, flow rates, emissions, and/or heat rates, for example, but not being limited thereto. Furthermore, the control system  300  may be utilized with CL-based plants having more than two loops. As a result, additional control signals will be required based upon the number of loops to be controlled. 
     A fuzzy controller  330  of the control system  300  according to an exemplary embodiment will now be described in further detail with reference to  FIG. 3 . As described above in greater detail, fuzzy control is based on fuzzy set theory and is a rule-based decision making process. Further, fuzzy control is a natural extension to conventional proportional-integral-derivative (PID) controls using human heuristic knowledge about plant operations captured in fuzzy rules. In addition, fuzzy rules are used to represent nonlinear mappings between inputs and outputs and fuzzy control thereby offers an alternative to nonlinear model based controllers. Another advantage of fuzzy controllers, particularly when implemented as a neural-fuzzy engine, is that test data can be used to fine tune, e.g., train, rules in the fuzzy controller. Additionally, rules can be added which further support controls optimization and/or process diagnosis. 
     Referring to  FIG. 3 , the fuzzy controller  330  includes a fuzzification part  335 , a fuzzy logic decision engine  340  connected to the fuzzification part  335 , and a defuzzification part  345  connected to the fuzzy logic decision engine  340 . The fuzzy logic decision engine  340  includes a rule base  350  and an inference engine  355  connected to the rule base  350 , as shown in  FIG. 3 . The fuzzy controller  330  receives a preprocessed signal  360  and outputs a processed signal  365 . In an exemplary embodiment, the preprocessed signal  360  is an output signal  367  ( FIG. 5 ) from an output of the first loop  200   a  or the second loop  200   b.    
     In addition, the processed signal  365  according to an exemplary embodiment is a control signal, e.g., an input signal  369  ( FIG. 5 ) supplied to an input of to the first loop  200   a  or the second loop  200   b , such as the first control signal  305 , the second control signal  310 , the third control signal  315 , or the fourth control signal  320  ( FIG. 2 ), for example, but alternative exemplary embodiments are not limited thereto. 
     The fuzzy controller  330  receives the preprocessed signal  360 , and the fuzzification part  335  fuzzifies the preprocessed signal  360 , e.g., converts the preprocessed signal  360  into an appropriate format for processing by the fuzzy logic decision engine  340 . In an exemplary embodiment, the fuzzy logic decision engine  340  includes a neural-fuzzy engine  340 . The fuzzy logic decision engine  340  then uses the inference engine  355  to determine an appropriate parameter, e.g., solution, for the fuzzified preprocessed signal  360  based upon rules (not shown) of the rule base  350 . Then, the defuzzification part  345  defuzzifies the preprocessed signal  360  to output the processed signal  365 . 
     Referring to  FIG. 4 , a hierarchical fuzzy control system  400  according to an exemplary embodiment includes a plurality of fuzzy controllers such as the fuzzy controller  330 . In addition, individual fuzzy controllers of the plurality of fuzzy controllers are arranged in a hierarchical manner. Specifically, a global fuzzy controller  403  operates in a supervisory manner, coordinating overall control of the hierarchical fuzzy control system and, more specifically, control over local fuzzy controllers such as a first fuzzy controller  405 , a second fuzzy controller  410 , a third fuzzy controller  415 , and a fourth fuzzy controller  420 , as shown in  FIG. 4 . Alternative exemplary embodiments, however, are neither restricted nor limited to local fuzzy controllers. For example, the global fuzzy controller  403  may supervise any one type of, or all of, local fuzzy controllers, local PID controllers, local neuro-adaptive controllers, and/or local model-based controllers, for example. In addition, the hierarchical fuzzy control system  400 , or a portion thereof, may, in an alternative exemplary embodiment, be integrated into a plant system optimization system, for example. 
     In an exemplary embodiment, the hierarchical fuzzy control system  400  is implemented as the control system  300 , described in greater detail above with reference to  FIG. 2 , in a CL-based power plant having, for example the first loop  200   a  and the second loop  200   b  ( FIG. 2 ). Thus, the global fuzzy controller  403  according to an exemplary embodiment coordinates and supervises the local fuzzy controllers. Further, the local fuzzy controllers individually process signals. More specifically, the first fuzzy controller  405  provides the first control signal  305 , the second fuzzy controller  410  provides the second control signal  310 , the third fuzzy controller  415  provides the third control signal  315 , and the fourth fuzzy controller  420  provides the fourth control signal  320 , as shown in  FIG. 4 . 
     As a result of using the hierarchical structure shown in  FIG. 4 , a size of a rule base  350  ( FIG. 3 ) of a given fuzzy controller  300 , e.g., the rule base  350  of each of the global fuzzy controller  403 , the first fuzzy controller  405 , the second fuzzy controller  410 , the third fuzzy controller  415 , and the fourth fuzzy controller  420 , is substantially reduced and/or or effectively minimized, thereby providing an advantage of optimized control over the complex, multivariable, nonlinear and interrelated processes, described above in greater detail, associated with a CL-based power plant. It will be noted that exemplary embodiments described herein can be implemented in any and all CL-based power plants, including but not limited to: single, dual, and multiple, e.g., two or more, loop CL systems, whether calcium- or metal oxide-based; CL-based plant with CO2 capture for utilization or sequestration; and CL-based CO2-ready power plants, but is not limited thereto. 
     Referring now to FIG.  5 ., implementation of the hierarchical fuzzy control system  400  in the CL system  5  will be described in further detail. The output signal  367  from the output of the first loop  200   a  or the output of second loop  200   b  ( FIG. 2 ) of the CL system  5  is supplied to a loop control part  500  having the hierarchical fuzzy control system  400  connected to a data acquisition system (DAS)  505  therein. In an exemplary embodiment, the DAS  505  is an automatic DAS  505  which monitors plant parameters such as temperature, pressure, differential pressure, heat rate, air flow, fuel flow, for example, but not being limited thereto. In addition, in an exemplary embodiment, the loop control part includes a software platform (such as MATLAB® or LABVIEW®, for example) which monitors and facilitates communications between the hierarchical fuzzy control system  400  and the DAS  500 . 
     In operation, the loop control part  500  receives the output signal  367  from the CL system  5 . In an exemplary embodiment, the output signal  367  includes, for example, a differential pressure (or a plurality of differential pressures) from the first loop  200   a  and/or the second loop  200   b , as described above in greater detail with reference to  FIG. 2 . The loop control part  500  outputs a loop control signal based on plant conditions (according to the DAS  505 ) and fuzzy logic analyses (according to the hierarchical fuzzy control system  400 ). In an exemplary embodiment, the loop control signal includes, but is not limited to, the first control signal  305 , the second control signal  310 , the third control signal  315 , and/or the fourth control signal  320  (note that for purposes of illustration, only the first control signal  305  is shown in  FIG. 5 ). The loop control signal, e.g., the first control signal  305  shown in  FIG. 5 , is then supplied to a mass flow controller  510 . The mass flow controller  510  then supplies the input signal  369  to the CL system  5 , to optimally control the CL system  5  by, e.g., adjusting a valve position such as a position of the recirculation air control valve  230   a  ( FIG. 2 ) to control a flow of air therethrough, as described above in greater detail. The loop control part  500  may also provide control signals  305  for actuating or generally controlling the operation of a pump, valve, actuator and/or a switch for controlling the operation of the system  5 . 
     The mass flow controller  510  according to an exemplary embodiment includes a valve actuator  510 . In addition, the input signal  369  includes, but is not limited to, valve position, fuel flow rate, air flow rate, water flow rate, sorbent flow rate, limestone flow rate, steam flow rate, and a ratio of at least two of fuel flow, air flow rate, limestone flow rate and steam flow rate. Furthermore, the output signal  367  includes signals indicative of operational parameters of the CL system  5 , such as power generation rate, load demand, solids inventory, solids transport rate, recirculation solids transport rate, crossover solids transport rate, reactor temperature, loop temperature, bed temperature, heat rate, pressure, differential pressure, reactor pressure, reactor differential pressure, riser differential pressure, seal differential pressure, dip leg differential pressure, crossover leg differential pressure, CO 2  flow, CO 2  utilization, CO 2  capture, CO 2  storage, CO 2  sequestration, H 2  flow rate, N 2  flow rate, and synthesis gas flow rate, but alternative exemplary embodiments are not limited thereto. 
     In an alternative exemplary embodiment, the control system  300  may be utilized with a CFB plant or a CL-plant subsystem having a single loop, e.g., only the first loop  200   a  shown in  FIG. 2 . In this case, there is no crossover solids transport. However, it is still desirable to maximize solids flow rate in the first reactor  10  while minimizing a cumulative pressure drop, e.g., differential pressure, across the dip leg  207   a , the SPCV  55   a , and the return leg  220   a . As a result, the control system  300 , when used with a CFB plant or a CL-plant subsystem having a single loop, effectively maintains a pressure balance between a riser side of the single loop  200   a , e.g., the first reactor  10 , and a seal side of the single loop  200   a , e.g., the dip leg  207   a , the SPCV  55   a , and the return leg  200   a . Thus, in an exemplary embodiment having only the single loop  200   a , a single control signal based upon a pressure difference between the riser side and the seal side of the single loop  200   a  may control a single control valve regulating an air flow to the SPCV  55   a , for example. 
     In summary, a fuzzy logic control and optimization system according to an exemplary embodiment includes a hierarchical structure. As a result, sizes of rule bases of individual fuzzy controllers included in the fuzzy logic control and optimization system are substantially reduced and/or or effectively minimized, thereby providing an advantage of optimized control over complex, multivariable, nonlinear and interrelated processes associated with a multiple loop CL-based power plant, for example. As a result, plant emissions are substantially reduced and/or effectively minimized, while overall economic plant efficiency is substantially improved, resulting in lower overall operating costs. Further, a hierarchical fuzzy control system (or a part of it) can be integrated into a CL-based plant optimization system, thereby further reducing operating costs. 
     It will be noted that exemplary embodiments of the fuzzy logic control and optimization system are not limited to the CL plant configurations described herein, or even to CL-based power plants in general. For example, in alternative exemplary embodiments, the fuzzy logic control and optimization system may be used with any and all CL-based systems, including but not limited to: single, dual, and multiple, e.g., two or more, loop CL systems, whether calcium- or metal oxide-based; CL-based plant with CO 2  capture for utilization or sequestration; and CL-based CO 2 -ready power plants, but is not limited thereto. Alternatively, the fuzzy logic control and optimization system may be implemented with any and all fluidized bed combustion (FBC) power plants, including circulating fluidized bed (CFB) boilers, bubbling fluidized bed (BFB) boilers, and variations thereof. 
     Furthermore, empirical modeling methods such as neural networks (NN), for example, may be implemented in conjunction with (or implemented within) the fuzzy logic control and optimization system described herein. 
     While the invention has been described with reference to various exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims.