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A state based adaptive PID controller includes a model set component including a plurality of process models, each process model including a plurality of parameters. An error generator generates a model error signal representative of a difference between a model output signal and a process output si

A state based adaptive PID controller includes a model set component including a plurality of process models, each process model including a plurality of parameters. An error generator generates a model error signal representative of a difference between a model output signal and a process output signal. A model evaluation component computes a model squared error based on the model error signal. A parameter interpolator calculates an adaptive parameter value based on the model squared error. A controller update component updates adaptive controller parameter values based on adaptive parameter values.

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What is claimed is: 1. A method of automatically switching an adaptive PID controller comprising: defining a model set having a plurality of individual models representative of a controlled process, wherein each of the models includes a plurality of parameter values; defining a plurality of model s

What is claimed is: 1. A method of automatically switching an adaptive PID controller comprising: defining a model set having a plurality of individual models representative of a controlled process, wherein each of the models includes a plurality of parameter values; defining a plurality of model subsets within the model set; wherein each of the model subsets includes a state parameter representative of a process variable input and a plurality of initial parameter values representative of the model subset; determining the state parameter and updating the PID controller with the plurality of initial parameter values associated with the state parameter; evaluating each of the models in the model subset corresponding to the state parameter and calculating a model squared error for each model; determining an adaptive parameter value as a function of the model squared error; and updating the PID controller in response to the adaptive parameter value. 2. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein the adaptive parameter values define a parameter model set including a center parameter value, an upper bound parameter value, and a lower bound parameter value. 3. The method of automatically switching an adaptive PID controller as defined in claim 2 wherein the upper bound parameter value is offset from the center parameter value by +Δ% and the lower bound parameter value is offset from the center parameter value by-Δ%. 4. The method of automatically switching an adaptive PID controller as defined in claim 2 wherein the center parameter value is set equal to the adaptive parameter value upon the conclusion of an adaptation cycle. 5. The method of automatically switching an adaptive PID controller as defined in claim 2, wherein the model squared error, E l(t)=(y(t)-Yl(t))2, for the model, Modi, is determined by squaring the difference between the process output at a given time, y(t), and the model output at that time, Yl(t). 6. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein evaluating each of the models in the model subset further includes: (i) performing a first evaluation scan on a first model set and determining, for each model in the first model set, the difference between an instantaneous process output and a model output during the first evaluation scan and computing a first Norm based on the determined difference; (ii) performing a second evaluation scan on the first model set and determining, for each model in the first model set, the difference between the instantaneous process output and the model output during the second evaluation scan and computing a second Norm based on the determined difference; (iii) computing an aggregate Norm by summing the second Norm for each parameter value and the first Norm for each parameter; (iv) performing additional evaluation scans on each of the models to determine at least one additional Norm for each parameter and summing the additional Norm to the corresponding aggregate Norm to determine a final Norm at the end of an adaptation cycle; (v) computing an adaptive parameter value for each parameter value that is weighted by the sum of the final Norm for all values of the parameter divided by the final Norm computed for the respective parameter value. 7. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein a model squared error, E l(t), is computed as El(t)=(y(t)-Yl(t))2, where y(t) is the process output at a particular time and Yl(t) is the model output at that time. 8. The method of automatically switching an adaptive PID controller as defined in claim 1, Wherein an adaptation cycle is initiated by evaluating the value of the state parameter corresponding to a disturbance measured in a process variable. 9. The method of automatically switching an adaptive PID controller as defined in claim 8, wherein disturbance measured in the process variable is detected in a process output signal y(t). 10. The method of automatically switching an adaptive PID controller as defined in claim 8, wherein disturbance measured in the process variable is detected in a process input signal. 11. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein a Norm is assigned to each model parameter value represented in a model, wherein the Norm is the sum of the model squared errors that are computed in the course of the evaluation of each of the models. 12. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein the parameters of the process model include an adaptive memory parameter and an adaptive memoryless parameter, and wherein the controller is updated in response to the adaptive memory parameter before being updated in response to the adaptive memoryless parameter. 13. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein the plurality of parameter initial values include initial values having a center parameter value, an upper bound parameter value, and a lower bound parameter value. 14. The method of automatically switching an adaptive PID controller as defined in claim 13, wherein the upper bound parameter value is offset from the center parameter value by +Δ% and the lower bound parameter value is offset from the center parameter value by-Δ%. 15. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein the adaptive parameter includes a center parameter that is set equal to the adaptive parameter value determined at the conclusion of an adaptation cycle. 16. The method of automatically switching an adaptive PID controller as defined in claim 1, wherein the adaptive parameter values are determine in a sequential manner. 17. The method of automatically switching an adaptive PID controller as defined in claim 16, wherein a subset of the adaptive parameters values are held constant while the remaining adaptive parameter value is adapted. 18. A system for adaptively tuning a process controller, the system comprising: a model set component communicatively coupled to a process input, the model set component including a state variable defining a plurality of process regions, and a plurality of models grouped into the plurality of process regions, each of the grouped models includes a plurality of parameters having a value selected from a set of predetermined initial values assigned to the respective parameter; an error generator communicatively coupled to the model set component and a process output, the error generator configured to generate a model error signal representative of the difference between a model output signal and a process output signal; a model evaluation component communicatively coupled to the error generator for computing a model squared error corresponding to a model and correlating the model squared error to parameter values represented in the model; a parameter interpolator communicatively coupled to the model evaluation component for calculating a respective adaptive parameter value for parameters represented in the model; and a controller update component communicatively coupled to the parameter interpolator and a process controller, the controller update component for updating the process controller in response to adaptive parameter values upon conclusion of an adaptation cycle. 19. The system for adaptively tuning a process controller as defined in claim 18, further comprising a supervisor component communicatively coupled to the process for initiating model evaluation when a change in a process input or a process output exceeds a respective threshold level. 20. The system for adaptively tuning a process controller as defined in claim 19, wherein the supervisor component is communicatively coupled to a feedforward input for initiating model evaluation when a change in a disturbance input exceeds a threshold level. 21. The system for adaptively tuning a process controller as defined in claim 18, wherein the set of predetermined initial values for each parameter includes a center parameter value, an upper-bound parameter value and a lower-bound parameter value. 22. The system for adaptively tuning a process controller as defined in claim 18, wherein the model evaluation component computes a model squared error, El(t), equal to (y(t)-Yl(t)) 2, corresponding to a model Modi, where y(t) is the process output at a given time and Y1(t) is the output of model Modi at that time. 23. The system for adaptively tuning a process controller as defined in claim 21, wherein the model evaluation component assigns a Norm to each model parameter value, which Norm is equal to the sum of the model squared errors computed in the evaluation of each of the models in which the parameter value is represented. 24. The system for adaptively tuning a process controller as defined in claim 23, wherein the adaptive parameter value calculated by the parameter interpolator is calculated as a sum of weighted parameter values. 25. The system for adaptively tuning a process controller as defined in claim 24, wherein the weighting factor applied to each parameter value is proportional to the sum of the Norms computed for all values of the parameter and is inversely proportional to the Norm computed for that value of the parameter. 26. The system for adaptively tuning a process controller as defined in claim 25, wherein the weighting factor applied to each parameter value is equal to the sum of the Norms computed for all values of the parameter, divided by the Norm computed for the respective parameter value. 27. The system for adaptively tuning a process controller as defined in claim 18, wherein the models component comprises a plurality of feedback controller models and a plurality of feedforward controller models. 28. The system for adaptively tuning a process controller as defined in claim 27, wherein the parameter interpolator comprises a feedback controller parameter interpolator and a feedforward controller feedback interpolator. 29. The system for adaptively tuning a process controller as defined in claim 28, wherein the controller update component is communicatively coupled to a feedback controller for updating feedback controller parameter values to the feedback controller and to a feedforward controller for updating feedforward controller parameter values to a feedforward controller. 30. A state based adaptive feedback/feedforward controller comprising: a model component coupled to a process and having a plurality of process models, wherein each of the models includes a plurality of parameters having a value selected from a set of predetermined initial values assigned to the respective parameter; a state variable describing the change of a process variable, the state variable defining at least one process region including a subset of the process models, the state variable corresponding to a set of region initial parameters representative of the process region; an error generator for generating a model error signal that represents the difference between a model component output signal and a process output signal; a model evaluation component for computing a model squared error corresponding to the model and for attributing the model squared error to parameter values represented in the model; a parameter interpolator for calculating an adaptive parameter value for at least one of the plurality of parameter values represented in the model; and a controller update component for updating a controller parameter value within the controller upon conclusion of an adaptation cycle. 31. The state based adaptive feedback/feedforward controller as defined in claim 30, further comprising a supervisor component for initiating the model evaluation when a change in the measure disturbance exceeds a respective threshold level. 32. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the predetermined initial values for each parameter include a center parameter value, an upper-bound parameter value and a lower-bound parameter value. 33. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the evaluation component computes a model squared error, E1(t), equal to (y(t)-Y1(t))2, corresponding to a model Modi, where y(t) is the process output at a given time and Y1(t) is the output of model Modi at that time. 34. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the adaptive parameter value calculated by the parameter interpolator component is calculated as a sum of weighted parameter values. 35. The state based adaptive feedback/feedforward controller as defined in claim 34, wherein the weighting factor applied to each parameter value is proportional to the sum of a Norm computed for all values of the parameter and is inversely proportional to the Norm computed for that value of the parameter. 36. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the process variable is a disturbance signal. 37. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the process variable is a change in a process set point. 38. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the process variable is a change in the process output signal. 39. The state based adaptive feedback/feedforward controller as defined in claim 30, wherein the parameter interpolator includes an adaptation limit for limiting the calculated change for the at least one of the plurality of parameter values.