Abstract:
An industrial control system uses a number of autonomous control units, each associated with one piece of equipment in an industrial process. The autonomous control units negotiate by bidding among themselves to determine a common set of input and output values for the interconnected machines with which they are associated. Each autonomous control unit determines whether input values are acceptable by using a model of its associated equipment. The model provides anticipated output values which may be compared against a predetermined range of outputs of associated machines, outputs compatible with downstream machines, or the constraints of the overall industrial process according to a designated job to be accomplished. Optimization of the input and output values is provided by allowing preliminary bids to be the subject of optimizing counter-bids if the original bid value could have been accepted.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation-in-part of U.S. Pat. No. 6,272,391 issued Aug. 7, 2001 and entitled: Self Organizing Industrial Control System Importing Neighbor Constraint Ranges, which is a continuation-in-part of U.S. Pat. No. 6,091,998 issued Jul. 18, 2000 and entitled: Self-Organizing Industrial Control System Using Bidding Process. 
    
    
     STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
     BACKGROUND OF THE INVENTION 
     The present invention relates to industrial controllers for the real-time control of equipment used in manufacturing and in particular to an industrial controller that automatically organizes equipment for the manufacture of a product based on the capabilities of the equipment. 
     Industrial controllers are special purpose computers used in controlling industrial processes. Under the direction of a stored control program, an industrial controller examines a series of inputs reflecting the status of the controlled process and changes a series of outputs controlling the industrial process. The inputs and outputs may be binary, that is, on or off, or analog, providing a value within a continuous range. The inputs may be obtained from sensors attached to the controlled equipment and the outputs may be signals to actuators on the controlled equipment. 
     Unlike the standardized software normally executed on conventional computers, the control program executed on an industrial controller is normally unique to each controlled process. The writing and troubleshooting of the control program is thus a significant cost in the creation of an industrial control system. After the controlled program is complete, it must often be modified as the product to be manufactured changes or as equipment is exchanged, replaced or repaired. 
     The above referenced grand-parent to this application describes a self-configuring industrial control system employing a number of autonomous control units, each associated with a particular piece of manufacturing equipment. The autonomous control units are programmed with data describing the capabilities of their equipment and the equipment&#39;s ability to interact with other equipment. A desired product is described in a “job description language and broadcast to the autonomous control units, each which identifies portions of the job that they can complete. The autonomous control units then exchange bids and counter-bids with the other autonomous control units to allocate the job among units and to select the desired operating parameters of the associated equipment. The autonomous control units are programmed with generalized goals so that the allocation may be further optimized for high productivity, low cost or some other objective measure. 
     The above referenced parent to this application describes an improvement to this bidding process in which each autonomous control unit exchanges intermediate constraints, that is, their common ranges of inputs and outputs, with upstream and downstream equipment. By importing these constraint ranges into the autonomous control units, the process of bidding can be simplified and shortened because each autonomous control unit can pre-evaluate its bids against the ranges before they are submitted, preventing unacceptable bids from being further processed. 
     Determining whether a bid is acceptable, assuming it meets the intermediate constraint ranges, can be difficult because the bids usually propose input values to the receiving autonomous control unit, whereas the outputs of the equipment, resulting from the bid inputs, may determine the acceptability of the bid according to whether the outputs remain within their constraint ranges. The equipment outputs may be constrained by the intermediate constraint ranges that the equipment shares with its downstream neighbors resulting from physical limits in the equipment&#39;s capabilities or from the job description which may describe desired outputs of individual pieces of equipment. Because the outputs of the equipment may be a function of several inputs, the validity of a bid input cannot be determined by comparison of the input to a fixed range of acceptable input values. 
     BRIEF SUMMARY OF THE INVENTION 
     The present invention provides a simple protocol for accepting or rejecting bids by applying the bids as inputs to the model of a particular piece of equipment and accepting the bids if the outputs from the model fall within the output constraints. The constraints may be those defined by the job plan or may be intrinsic to a machine or to machines which are connected to a machine. Within this protocol of rejection or acceptance of a bid, counterbids may be made in response to bids that propose acceptable but non-optimal input values. 
     Specifically then, the present invention provides an autonomous control unit forming part of an industrial controller for controlling a process made up of sub-processes, the autonomous control unit associated with a sub-process and used with other autonomous control units associated with other sub-processes, each sub-process having input variables describing input values to the sub-process and output variables describing corresponding output values of the sub-process. Each autonomous control unit includes a network connection allowing intercommunication between autonomous control units and the receipt by the autonomous control unit of a job plan describing the process. The autonomous control units also include an electronic memory holding a sub-process model relating the input variables to the output variables for the sub-process of the autonomous control unit. Also, the electronic memory includes a constraint table holding a constraining range for the output variables of the sub-process. The autonomous control unit also includes an electronic computer communicating with the network connection and the electronic memory, and executing a stored program to receive the job and receive a bid from a second autonomous control unit describing a proposed value of input variables of the sub-process of the autonomous control unit. The program further determines corresponding values of output variables using the model and, when the output variables satisfy the constraint ranges of the sub-process, responds to the second autonomous control unit accepting the proposed value of the variable as part of response to the job plan. On the other hand when the output variables do not satisfy the constraint range, the execution of the stored program causes a responding to the second autonomous control unit rejecting the proposed value of the input variables. 
     Thus it is one object of the invention to provide for a relatively simple protocol to determine whether a bid is acceptable or not. A bid is acceptable if its resulting output values when modeled do not violate any of the known constraints. 
     The constraints of the sub-process may represent at least one of the restraints imposed by the job plan or the physical operation of the sub-process of the first autonomous control unit or the physical operation of a sub-process associated with a third autonomous control unit communicating with the sub-process of the first autonomous control unit. 
     Thus it is another object of the invention to provide for multiple sources of constraints to be used in this simple protocol. The constraint may be simply that of the job plan defining, for example, the goods to be manufactured, or may result from physical constraints on the equipment associated with the autonomous control units or those of upstream or downstream autonomous control units. 
     The autonomous control unit may respond to the second autonomous control unit indicating alternative input variables when the output variables satisfy the constraint ranges. 
     Thus it is another object of the invention to permit within this protocol a counter-bidding in which the autonomous control unit can indicate preferable input values other than those bids based on its internal optimizing function. 
     The autonomous control unit executing the stored program may identify whether the proposed input variables are “preliminary or “final” and may respond to the second autonomous control unit indicating an alternative input variable optimized by the autonomous control unit only when the proposed input variables are preliminary. 
     Thus it is another object of the invention to provide for different classes of bids so as to allow or curtail counter-bidding according to the originator of the bid. 
     The autonomous control unit executing the stored program may, when the output variable satisfies the constraints of the job plan, send a bid to a third autonomous control unit proposing the output variables as preliminary input variables to the third autonomous control unit. 
     Thus it is another object of the invention to permit a successful bid to cause the propagation of additional bids to other autonomous control units. 
     The messages between the autonomous control units may be contained in message wrappers identifying the input variables as preliminary or final and the message wrappers may make use of protocols of the standard agent language such as, but not limited to, KQML. 
     Thus it is another object of the invention to make use of existing agent communication protocols for an industrial process that is self-organized. 
     The foregoing and other objects and advantages of the invention will appear from the following description. In the description, reference is made to the accompanying drawings which form a part hereof and in which there is shown by way of illustration a preferred embodiment of the invention. Such embodiment does not necessary represent the full scope of the invention, however, and reference must be made to the claims herein for interpreting the scope of the invention. 
    
    
     BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
     FIG. 1 is a perspective view of a simplified rolling mill composed of a sequential set of machines each associated with an autonomous control unit per the present invention; 
     FIG. 2 is a schematic block diagram of the autonomous control units of FIG. 1 showing the inter connection of the autonomous control units through interfaces on a common link and processors and memories of the autonomous control units; 
     FIG. 3 is a detailed block diagram of the memory of one autonomous control unit of FIG. 2 showing the contained bid program (including a performative generator), constraint data, goal data, self-assessment data, and a model of the equipment associated with the autonomous control unit; 
     FIG. 4 is an expanded block diagram of the constraint data, goal data, self-assessment data, and model of FIG. 3; 
     FIG. 5 is a graphical representation of the equipment of the rolling mill of FIG. 1 as defined by various inputs and constraints; 
     FIG. 6 is a flow chart of the bid program of FIG. 3 such as may be used to generate a control strategy communicated through bids expressed by performatives and data for the machines of FIGS. 1 and 5; 
     FIG. 7 is a flow chart of the operation of the model of FIGS. 3 and 4 in responding to a counter-bid performative per the flow chart of FIG. 6; 
     FIG. 8 is a perspective representation of a sub-process (e.g., equipment) controlled by an autonomous control unit showing input and output variables falling within input and output constraint ranges; 
     FIG. 9 is a flow chart showing a response by an autonomous control unit to a preliminary bid performative; 
     FIG. 10 is a flow chart showing a response by the autonomous control unit to a determinative bid performative; 
     FIG. 11 is a flow chart showing a response by the autonomous control unit to a counter-bid performative; 
     FIG. 12 is a flow chart showing the response by the autonomous control unit to an acceptance of a bid performative; 
     FIG. 13 is a graphical representation of a simple model for an autonomous control unit showing application of the model to a propose bid value to determine acceptance or rejection performatives; 
     FIG. 14 is a graphical representation of the iterative process used with the model of FIG. 13 to traverse input space when counter-bid performatives proposing output values are received; 
     FIG. 15 is a graphical representation of an iterative process used to optimize input values in a manner analogous to the process of FIGS. 13 and 14; and 
     FIG. 16 is a block diagram showing the inputs and outputs of the performative generator of FIG.  3 . 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Components of the Control System 
     Referring now to FIG. 1, an industrial process  10  may provide for the processing of metal billets  12  through a series of machines  14 . Each machine  14  may have an associated autonomous control unit  16  being either discrete devices as shown in FIG. 1 or portions of a centralized machine. The autonomous control units  16  may be separate computers interconnected by a common communication link  18  and also connected by the communication link  18  to a controller  20  and a human/machine interface such as a computer terminal  22  of conventional design. Alternatively, the autonomous control units  16  may be partitions of controller  20  communicating with the machines  14  via sensors and actuators on the machines  14 . 
     In an example, process  10  suitable for control by the present invention, machines  14  may include a reheat furnace  14   a  for heating precast billets  12  to a predetermined temperature, a rolling mill  14   b  for rolling the billets  12  to a predetermined diameter, a water bath  14   c  for cooling the billets  12  with water and a Stelmor conveyor  12   d  cooling the billets  12  with air. The billets  12  may alternatively come directly from a continuous casting machine  14   e  at casting temperature without the need for reheating by reheat furnace  14   a . In this case, the billets pass directly from the continuous caster  14   e  to the rolling mill  14   b.    
     Referring now to FIGS. 2 and 3, each autonomous control unit  16  includes an interface circuit  24  connected with the common communication link  18  and handling communication protocols so that the autonomous control units  16  may communicate bids and counter-bids among themselves and may receive a job description as will be discussed below. The interface circuits  24  of each autonomous control unit  16  are connected by an internal bus  26  to a processor  28  and memory  30 . 
     Data Structures 
     Referring now to FIG. 3, the memory  30  holds a bid program  32  that will be used to generate bids and counter-bids to be exchanged among the autonomous control units  16  in developing a control strategy for the machines  14 . The bids and counter-bids, as well as other types of messages are uniquely identified in purpose by “performatives” embedded in message wrappers holding bid data and establishing the context of the bid data according to the type of performative as will be described. The message wrappers may be semantically analyzed to identify the performative, such as “preliminary bid”, “determination” or “final bid”, “counter-bid” and “rejection”, to determined the stage of the bidding process and the appropriate range of responses, which my also be conveyed by a performative as well. Other performatives will be noted below, each associated with one or more stages of the bidding process. Generally the format of the performatives may follow the format of a standard agent control language such as KQML. A performative generator  33  accomplishes the task of identifying the particular stage of the bidding from the performatives. 
     The bid program  32  communicates with the other autonomous control units  16  according to a communications protocol program  35  which extracts performatives and data from incoming message from other autonomous control units  16  and which determines the source of the message (i.e., the identity of the sending autonomous control unit  16 ) and which accepts response performatives, data and the identification of a destination autonomous control unit  16  to properly format a message to that destination autonomous control unit  16 . The communications protocol program  35  thus provides a network connection to the performative generator. Referring to FIG. 16, the performative generator  33  accepts as inputs the extracted performatives, data and source and produces the response performatives, data and destination necessary to effectuate a converging bid process as will be described below. The performative generator  33  thus serves to interpret in the broadest sense, bids and counter-bids and to direct bids and counter-bids to the correct device according to a predefined protocol. 
     The performative generator  33 , as part of the bid program  32  has access to stored data tables representing constraint data  34  which generally quantifies the limitations of performance of the associated machine  14 , goal data  36 , which describes preferences among modes of operation of the associated machine  14  within the constraints  34 , self-assessment data  38  generally describing the dynamic state of the associated machine, and a model  40  modeling operation of the associated machine by mathematical means. 
     Referring to FIG. 4, the constraints  34  are of a number of different kinds. Task constraints  42  describe generally the kind of operation that the associated machine  14  is intended to perform. Thus, for example, the reheat furnace  14   a  may perform heating tasks (GOTO TEMP); the rolling mill  14   b  (as shown) may perform a diameter reduction task (GOTO DIA.). The task constraints  42  allow the autonomous control units  16  to make a threshold determination as to whether their associated machines  14  will make a bid for a particular task of a plan to produce a product. Continuing with the example of the rolling mill  14   b , the autonomous control unit  16   a  of the rolling mill  14   b  will only bid for tasks requiring diameter reductions. 
     The constraint data also includes input constraints  44  which describe the limits of the inputs to the associated machine  14 . The inputs (as opposed to the outputs of the machines  14 ) are well defined and their ranges are set by the physical design of the machine. For example, for the rolling mill  14   b , the input will be the amount of gas valve opening and the range of the input will be from zero to one hundred percent. For the rolling mill  14   b , the inputs will be rolling diameter from 0 to 1. For the water bath  14   c , the input will be water flow rate and for the Stelmor conveyor  14   d , the inputs will be airflow rate. As used herein, input constraints are only those constraints independent of the operation of other machines  14 . 
     The constraints  34  also include path constraints  46  which generally reflect limitations on the possible paths of the product, e.g., the billet  12  between machines  14  as dictated by their physical layout. In this example, two paths are available, the first in which the billet  12  passes from reheat furnace  14   a  to rolling mill  14   b , then to water bath  14   c  and finally to Stelmor conveyor  14   d  and the second where the billet  12  passes from continuous caster  14   e  to rolling mill  14   b  then to water bath  14   c  and finally to Stelmor conveyor  14   d . These path topologies are reflected in the path constraints  46  listing the path in a first column and a set of intermediate constraints  48  (as will be described) in a second column. From this table, all possible paths between machines  14  may be determined. The task constraints  42 , the path constraints  46  and the input constraints  44  will be termed generally “operational” constraints as they constrain the operation of the machine  14  in contrast to the inter-machine constraints to be described below. 
     Referring also to FIG. 5, deriving from the path constraints  46  and possibly including other inputs of the machines  14  are the “inter-machine” or “intermediate” constraints  48  representing operating parameters shared between machines  14  based on the path of the material between machines  14 . Generally these intermediate constraints  48  connect identical operating parameters of the machines  14  forming outputs of upstream machines in the material path with inputs of downstream machines in the material flow path. Thus the input temperature of the rolling mill  14   b  will be constrained to be equal to output temperature of the reheat furnace  14   a  or the output temperature of the continuous caster  14   e  depending on the particular path. The continuous caster  14   e  has an output speed and hence this is an inter-machine constraint for that path only. Generally, the rolling mill  14   b  and water box  14   c  also share output and input temperatures, respectively, and also billet speed i.e., the speed of exit of the billet  12  from the rolling mill  14   b  equaling the speed of entry of the billet into the water box  14   c.    
     As a result of the coiling of the billet product in the Stelmor conveyor  14   d  the water box  14   c  and Stelmor conveyor  14   d  do not share the parameter of conveyor speed but do share the parameter of temperature as the temperature of the billet output from the water box  14   b  will equal the temperature of the billet  12  entering to the Stelmor conveyor. 
     Referring again to FIGS. 3 and 4, the memory may also hold goal data  36  implemented as a utility function  50  having as input arguments one or more of the characterizing parameters of the machine  14 , either inputs or outputs, and as a value, an arbitrarily defined utility which reflects a preprogrammed goal of the autonomous control unit  16 . In the case of the rolling mill  14   b , the utility function  50  may be a function of speed reflecting a desire for high production, but also a particular speed for metallurgical reasons. A more complex utility function  50  might consider other metallurgical properties and wear on the equipment. Generally the autonomous control unit  16  strives to maximize utility within the operational and intermediate constraints. 
     Other machines will have other goals as selected and programmed by the user or manufacturer. The goals for the reheat furnace  14   a , the water box  14   c  and Stelmor conveyor  14   d  are generally reduction of gas, water and air volume, respectively. 
     Referring still to FIGS. 3 and 4, the self-assessment data  38  will typically include various sensed parameters  52  of the associated machine  14 . As shown in FIG. 4 for the rolling mill  14   b , the self-assessment data includes current rolling diameter and the rolling speed (sensed outputs). A general operational status for the rolling mill  14   b  may also be provided as generated from other inputs and outputs and possibly a heuristic program evaluating the fitness of the machine  14 . Generally the self-assessment data  38  is used to modify the operation constraints  34  if the operational status of the machine  14  is somehow impaired. 
     The model  40  provides a mathematical description  54  relating inputs to the machine  14  to its outputs and thus makes the performative generator specific to the subprocess of the machine  14 . In the example of the rolling mill  14   b , a simple linear equation of three variables is shown relating output temperature of the rolling mill  14   b  to the input temperature, the rolling speed and the diameter reduction. This model reflects generally the fact that the rolling process can increase the temperature of the stock. Generally far more complex models may be created relating one or more inputs to particular outputs of the machine. In most cases, the inverse of the model function is not also a function and thus an iterative process must be used to deduce an input from an output such as a binary search using successive input values until the desired output is arrived at. 
     For the reheat furnace  14   a , the model  40  will take into account the time integral of the gas valve opening as reflects the heating of the furnace. The model for the water box  14   c  may relate cooling water flow and process speed to surface and internal temperatures. The model  40  for Stelmor conveyor  14   d  will provide a time and air flow relationship to temperature of the output billet  12 . The construction of such models is generally understood in the art and will depend on the particular machine  14 . 
     Job Description Language 
     Referring now to FIGS. 1 and 5, a “product” autonomous control unit  16  may be implemented by an arbitrary controller  20  to represent the desired product to be manufactured from the billet  12 . This product autonomous control unit provides a convenient unit for implementing the functions of describing the product to the autonomous control units  16  of the machines  14  and of evaluating the plans produced by the autonomous control units  16  against the product definition. For this first task, the product autonomous control unit, accepts input from a user through computer terminal  22  describing the product characteristics and produces a machine independent description of desired tasks for producing that product in a job description language. In the preferred embodiment, the job description language is an ASCII text file providing a number of steps defining desired machine outputs. For example, to produce a rolled billet, the job description is as follows: 
     STEP  1 =GOTO TEMP(ALL)&lt;1300.0 
     STEP  2 =GOTO DIAMETER=5.5 TOL(−0.2, 0.2) 
     CONSTRAIN TEMP(ALL)&lt;1300.0 
     CONSTRAIN TEMP(ALL)&gt;825.0 AT TIME=END 
     DEPENDS ON (1) 
     STEP  3 =GOTO TEMP(SURF)=850 TOL(−5.0, 5.0) 
     CONSTRAIN TEMP(ALL)&gt;825.0 AT TIME=0.0 
     CONSTRAIN TEMP(SURF)&gt;450.0 AND&lt;1300.0 
     WITH DIAMETER=5.5 
     DEPENDS ON (2) 
     STEP  4 =GOTO TEMP(AVG)=650.0 TOL(−5.0, 5.0) IN TIME&lt;15.0 
     CONSTRAIN TEMP(SURF)&gt;500 AT TIME&gt;=0.0 AND&lt;=2.0 
     WITH DIAMETER=5.5 
     DEPENDS ON (3) 
     STEP  5 =GOTO TEMP(AVG)=600.0 TOL(−5.0,5.0) IN TIME&gt;40.0 
     WITH DIAMETER=5.5 
     DEPENDS ON (4) 
     Each step defines temperatures (TEMP), diameters (DIAMETER) and tolerances (TOL) of the billet and the sequence (DEPENDS ON) and timing (AT TIME) of the steps. In this example, both surface temperature (SURF) and overall temperature (ALL) is considered and so the models  40  must provide outputs for both. 
     Operation of the Control System 
     The operation of the autonomous control units  16  (and the controller  20 ) will now be described with reference to the flow chart of FIG.  6 . The flow chart of FIG. 6 is executed in part by different autonomous control unit  16   a  and the controller  20  as will be apparent from context. 
     At a first step, the job description language (JDL) is generated by the autonomous control unit implemented in controller  20  for the product and is represented by process block  60 . At succeeding process block  62 , the JDL is broadcast over the communication link  18  accompanied by a performative identifying it as such. 
     As indicated by decision block  64 , each autonomous control unit receiving the broadcast JDL evaluates the tasks of the JDL generally in light of its own task constraints  42  and submits to the most upstream autonomous control unit  16  in the path (indicated by the path constraints  46 ), and in this case the reheat furnace  14   a , an indication of which tasks represented by steps in the JDL, it can perform. The data is again associated with a performative indicating that is associated with this preliminary stage of the bidding process. 
     The most upstream autonomous control unit  16   a , based on the received indications about task capability from the other autonomous control units  16 , next tries to create one or-more “template job plans” representing a possible allocation of tasks to machines  14 . In the event that there is not at least one autonomous control unit  16  indicating an ability to perform at least each step of the JDL, the most upstream autonomous control units  16   a  proceeds to a fail state  66  indicating that the desired product cannot be produced by the machines  14 . 
     More typically, at process block  68 , one or more job templates will be created as described. A number of different job templates may address different allocation of machines  14  to different steps of the JDL or different material flow paths in the case where the topology is not as simple as the example used herein, or different job templates may address different products. 
     The job plans are then broadcast, wit the appropriate performatives, to the autonomous control units  16  which extract the path constraints  46  from the material paths contained in the job plans and establish a set of machine-relationships manifest in the inter-machine or intermediate constraints  48 . A different set of machine relationships will be prepared for each job plan reflecting possibly different material paths and hence different machine interactions. Each autonomous control unit  16  initially is programmed with a set of ranges for the intermediate constraints  48 , the ranges based on the known characteristics of the machine associated with the autonomous control unit  16 , for example, a speed or temperature range which may be determined by the design of the machine  14 . As indicated by process block  69 , these initial ranges are then exchanged with the upstream and downstream machines sharing the same operational parameters as indicated by the intermediate constraints  48 . For example, for a first path where rolling mill  14   b  receives billets  12  from the reheat furnace  14 ( a ), the oven output temperature range may be 0 to 2000 degrees substantially larger than the rolling mill  14   b  input temperature range of 1000 to 1200 degrees. In this case, the intersection of these two ranges 1000-1200 is adopted by the reheat oven  14   a  and the rolling mill  14   b  for this shared parameter. In contrast, for a second path where the rolling mill  14   b  receives billets  12  from the continuous caster  14 ( e ), the casting process may require a narrow temperature range about 800 degrees so as to preserve pliability of the billets  12  and to prevent eruption of the cooling liquid interior. In this case, the intersection of the ranges for the continuous caster  14   e  and the rolling mill  14   b  is the single value 800. Note that if the rolling mill  14   b  had a smaller range in input temperature than the output of the continuous caster  14   e , the smaller range of the rolling mill  14   b  would be adopted by the continuous caster  14   e.    
     The purpose of this exchange of ranges is to simplify the bidding process which is described below by enabling the autonomous control units to eliminate bids, and hence avoid the bidding process for values outside the combined solutions space of these ranges. 
     After this exchange, the most upstream machine  14 , either the reheat furnace  14   a  or the continuous caster  14   e , then reads the first step of the JDL, which in this case indicates that the temperature of the product should be raised to a value of less than 1300 degrees, and evaluates whether it can create a bid for that task as indicated by process block  70 . Specifically, the autonomous control unit  16  evaluates its current temperature in its self-assessment  38  and its goals  36  and the requirements of the JDL to create a bid indicating a specific temperature to which the reheat furnace will raise the billet  12 . In this case, the intermediate constraints  48  are those associated with the reheat furnace  14   a  and material path I. Simultaneously, a similar process is performed by the continuous caster  14   e  for material path II. 
     Assuming that the autonomous control unit  16   a  of the reheat furnace  14   a  (and/or the continuous caster  14   e ) may make a bid within the above constraints, the program proceeds to decision block  72  to test if this is the last autonomous control unit on the job path ( i.e., in either case, the Stelmor conveyor  14   d ). At this time it is not, and so the program proceeds to process block  74  where the bids are perfected by transmitting them, identified by the appropriate performative and containing bid data value, to the succeeding rolling mill  14   b  and more generally to the autonomous control unit(s) immediately downstream from the autonomous control unit  16  making the bid. The autonomous control unit  16   a  also updates an internal bid storage table (not shown) and a counter-bid, to be described, may be also made at this time. 
     The process then proceeds to the next autonomous control unit  16   b  as generally shown by process block  76 . The next autonomous control unit  16   b , associated with the rolling mill  14   b , receives the template plans and the bids proposed by the reheat furnace  14   a  and the continuous caster  14   e . At process block  70 , autonomous control unit  16   b  determines whether it can make a bid based on the information from the JDL and on the constraints  34 , including this time, constraints from the table holding intermediate constraints  48  which links the input temperature or the rolling mill  14   b  to the output temperature of the reheat furnace  14   b  or continuous caster  14   e  depending on the bid. The modification of the intermediate constraints  48  to reflect the restraints of adjacent machines makes this generation of the bids more robust against constraints of the other machines and thus less likely to trigger time consuming counter-bids. Nevertheless, because the counter-bid process strives to preserve the range of the intermediate constraints  48 , the autonomous control unit making the bid can exercise some influence on the job plan from its unique goals. 
     In the example given, the JDL requires that the temperature of the billet  12  be greater than 825 degrees at the end of the rolling. Assuming for the moment that the temperature selected by the reheat furnace  14   a  is insufficient for the rolling mill  14   b  to reach the required output temperature (as may be determined by model  40  for the rolling mill  14   b ), then at process block  70 , the autonomous control unit  16   b  proceeds to process block  104  to generate rejection response. 
     For the counter-bid, the autonomous control unit  16   b  must first determine an acceptable input temperature to the rolling mill  14   b . Generally this cannot be done by consulting stored input constraints for temperature because the relevant constraints will dynamically depend on the particular output temperature required. Accordingly, the program  32  of the autonomous control unit  16   b  must refer to the model  40 . 
     Referring now to FIG. 7, the process of determining the necessary input temperature (or an arbitrary input value from a defined output) begins at a process block  82  in which the new defined output condition is established. In this example the output condition is a temperature of greater than 825 degrees as required by the JDL. 
     At decision block  84 , an unconstrained input is identified, in this case an input temperature from the reheat furnace  14   a  within a temperature range permitted by the rolling mill  14   b . By unconstrained it is meant that the input may be varied in a desired direction without the input constraints  44 . 
     At process block  86 , the identified input is modified in a direction to reduce the difference between the desired output value (per the JDL and process block  82 ) and the modeled output value produced by evaluating the model  40  with the unmodified input. The modified input is then evaluated by executing the model  40  as indicated at process block  88  to produce a new output. 
     At decision block  90 , the current output from the model  40  is matched to the desired new output from process block  82  and if the outputs match within a tolerance the modified input established at process block  86  is used for the counter-bid as indicated by process block  92 . The counter-bid incorporates a new range for the input rather than a single input value so as to preserve the flexibility of the autonomous control units accepting the counter-bid as much as possible. If the modification of the input was downward, then the input becomes the new upper boundary of the input range, whereas if the modification of the input was upward, the input becomes the new lower boundary of the range. The new range is forwarded to autonomous control units for the corresponding upstream machine as part of the counter-bid. 
     More typically, at least initially, the outputs will not match and the program loops back to process block  84  for a second or subsequent iteration. If prior to a matching of the outputs, the input becomes constrained and there are no further inputs that can be modified, the program proceeds to a fail block  94  indicating the process cannot be completed. 
     Referring again to FIG. 6, assuming that a suitable counter-bid can be obtained at process block  92  of FIG. 7, the counter-bid is perfected by forwarding it to the proceeding autonomous control unit  16 , in this case, autonomous control unit  16   a  for the reheat furnace  14   a.    
     Autonomous control unit  16   a  receiving the counter-bid at decision  96  then determines whether it can accept the counter-bid&#39;s new proposed output temperature range. The model  40  for the reheat furnace  14   a  (not shown) may be invoked to determine whether with practical inputs (per input constraints  44 ), the desired output temperature value can be obtained. Often a range of possible modified bids are available and one bid is selected by use of the goal of the utility function  50 . The counter-bid may be accepted if the autonomous control unit  16   a  can create a bid using input values that do not violate the intermediate constraints. 
     Referring again to decision block  96 , if the counter-bid cannot be accepted then at decision block  100 , a test is performed to see if the autonomous control units  16  receiving the counter-bid is the first autonomous control unit  16 . If it is, then the program proceeds to process block  102  and a failure condition is indicated as would be the case were the reheat furnace  14   a  receiving the counter-bid. 
     More typically, however, the autonomous control unit  16  receiving a counter-bid will not be the first autonomous control unit  16  and thus it is possible to reject the bid and allow possibly other counter-bids as indicated by process block  104 . 
     Bids and counter-bids may thus ripple up and down the chain of autonomous control units  16   a ,  16   b ,  16   c , and  16   d  and the chain of autonomous control units  16   e ,  16   b ,  16   c , and  16   d  until at process block  72 , the last autonomous control unit in the material path is successfully bid for each chain and the program proceeds to process block  104  and the completed plans are forwarded to the product autonomous control unit in the controller  20  to be evaluated. 
     The product autonomous control unit in controller  20  may then accept one of the plans or may change the job description in a process analogous to the counter-bidding proposal and the process may be repeated. As a result of the possibility of unresolvable bidding outcomes, the product autonomous control unit  16  normally produces a time limit on the process which if exceeded causes the process to indicate a failure. 
     Referring now to FIGS. 4 and 8, during the bidding process, the autonomous control unit  16 , for example, for the rolling mill  14   b  receives variables of input temperature  150  and input speed  152  through bids which fall within the intermediate constraints  48  for those particular variables. The autonomous control unit  16  may in turn transmit variables of output temperature  154  and output speed  156  as bids to other autonomous control units  16 , such outputs being also within intermediate constraints  48 . 
     Because of the complexity of a typical sub-process such as that of the rolling mill  14   b , in general, the variables of output temperature  154  and output speed  156  will be complex functions of both input temperature  150  and input speed  152 . The fact that a bid input temperature  150  and input speed  152  both falls within their constraint ranges thus does not guarantee that the variables of output temperature  154  and output speed  156 , resulting from those input variables and possible other inputs to the sub-process, will fall within their intermediate constraints  48 . For this reason prior to evaluating any bid containing input variables, requires taking the input variables of the bid, running them in the model of the sub-process, in this case the rolling mill model  40  to determine whether the corresponding outputs are consistent with the output intermediate constraints  48 . 
     Referring to FIG. 9, in this regard, a preliminary bid  160  may be received by the autonomous control unit  16  and a determination made, as indicated by decision block  162 , as to whether that bid can be accepted. As described above, the intermediate constraints  48  have been shared between the autonomous control units  16  so it can be assumed that any input values in a bid  160 , for example, temperature and speed for rolling mill  14   a , are within their intermediate constraints  48 . Nevertheless, it must be determined whether the rolling mill  14   a  operating according to the proposed values of the bid  160  will produce acceptable output values meeting the job description and the physical limitations of the rolling mill sub-process  14   b  and possibly downstream limitations of succeeding machines as embodied in the range of the intermediate constraints  48 . 
     Referring now to FIG. 13, the model  40  of the sub-process  14   b  of the rolling mill converts the input values contained in the bid, for example, input speed  152  and input temperature  150 , into a value of output temperature  154 . A three-dimensional model is shown accommodating the three variables of input temperature, output temperature and speed, however, it will be understood that generally the models will have multiple dimensions corresponding to all possible sub-process variables of interest. 
     If the modeled variable of output temperature  154  falls outside of the corresponding range of intermediate constraints  48  applicable to that output variable, then as shown in FIG. 9, a rejection of the bid is transmitted to the bidding autonomous control unit as shown by process block  164 . 
     On the other hand, if the modeled output temperature  154  falls inside the range of its corresponding intermediate constraints  48  as shown in FIG. 13, then the autonomous control unit  16  proceeds to optimize process block  166  where it is determined whether there exist better values of input speed  152  or input temperature  150  according to the internal utility function  50  of the autonomous control unit. Generally, a preferred input speed  152 ′ may be deduced using the utility function  50 . The particular variable optimized is determined by a preference provided in the table of intermediate constraints  48 . 
     The preferred input speed  152 ′ must also be constrained so that the variable of output temperature falls within the corresponding range of its intermediate constraints  48  of the outputs. For this reason, a binary search routine may be used to vary the input speed  152  so that it is moved successively in repeated iteration of half the remaining distance to the optimal input speed  152 ′. At each iteration, the changed variable of input speed  152  is modeled to ensure that the output temperature  154  remain within its range. 
     Referring now to FIG. 15, in an alternative embodiment, if the utility function  50  is not well characterized for analytic maximization, the input speed  152  may be alternately moved half the distance to the terminus points  151  of its range of intermediate constraint  48  to values indicated by arrows A. That value, which when modeled, both yields an output temperature  154  remaining within its intermediate constraints  48  and the highest utility is then adopted and half that distance of movement is made to the adopted value of variable  152  in two directions and the same logic applied, until changes in utility below a certain tolerance value are obtained at which case the then current value is adopted as the preferred input speed  152 ′. 
     Referring again to FIG. 9, in the event that no optimized value can be obtained, then at process block  168 , an acceptance bid is sent to the bidding autonomous control unit and as indicated by arrow  170 , a bid is passed downstream using the new output values deduced from the model  40 . On the other hand, if an optimized value can be obtained, then as indicated by process block  172 , a counter-bid incorporating the new input value  152 ′ is sent to the bidding autonomous control unit. The counter-bid  172  includes an acceptance of the original bid as well. 
     Referring now to FIG. 10, an additional performative of bid beyond the proposed bid  160  described above may be implemented by further distinguishing the bids with their wrapper surrounding the bid message according to additional performatives. This additional performative of bid is a determination bid which indicates that no optimizing is allowed. Accordingly, when such a determination bid is received as indicated by process block  174 , at process block  162 , a rejection at process block  164  is provided or an acceptance at process block  168  only according to the rules described above with respect to process block  162 . 
     Referring now to FIG. 11, the autonomous control unit may receive a counter-bid  176 , such as is generated by process block  172  of FIG. 9 from a succeeding autonomous control unit. At process block  178 , the autonomous control unit must determine whether it can accept this counter-bid  176  which unlike a bid  160  proposes values of output variables to the autonomous control unit  16  as opposed to values of input variables. 
     Referring now to FIG. 14, the model  40  is again employed for counter-bid  176  to determine whether the counter-bid  176  may be accepted. In this case, the model  36  is used to determine whether inputs  150  and  157  corresponding to the counter-bid output will fall within their constraint ranges  48 . Again a binary search algorithm may be adopted to scan through the input space of the model  36  until the appropriate output is obtained. In this way the model may in effect be run backwards. The input variable to be changed is determined by a preference contained in the table of intermediate constraints  48 . 
     In the case where a value of input speed  152  was associated with the bid  160  that produced the counter-bid  176 , a new value of output temperature  154 ′ halfway between the bid  152  and a terminus point  151  of the constraint range for that variable is adopted. That input is modeled to see how close the output is to the value of the counter-bid  176  and if the output has moved closer to the desired output, the process is repeated again moving the variable  152  by half its previous moved distance. Movement in the opposite direction is undertaken if the output value is not converging. This process is repeated until convergence upon the desired output value of the counter-bid  176  is reached (within a predefined tolerance) or else convergence is clearly indicated as impossible. In the latter case, a rejection of the counter-bid is sent as indicated by process block  180 . However, in the former case, a bid is forwarded as indicated by process block  182  incorporating the counter-bid values. 
     An alternative situation may occur when a counter-bid is accepted as indicated by process block  184 . In this case, it is matched with a previously made bid  186  and a determinative bid  188  is made to be received as indicated by the discussion of FIG.  10 . 
     The above description has been that of a preferred embodiment of the present invention, it will occur to those that practice the art that many modifications may be made without departing from the spirit and scope of the invention. In order to apprise the public of the various embodiments that may fall within the scope of the invention, the following claims are made.