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Adaptive Predictive Functional Control of a Class of Nonlinear Systems

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

 

 

Step responses of the nominal closed loop system.

 

Abstract: This paper describes the use of pseudo-partial derivative (PPD) to dynamically linearize a nonlinear system, and aggregation is applied to the predicted PPD, resulting in a model-free adaptive predictive control algorithm for a nonlinear system. The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection.

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