Adaptive predictive functional control of a class of nonlinear systems

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...

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Veröffentlicht in:ISA transactions 2006-04, Vol.45 (2), p.175-183
Hauptverfasser: Zhang, Bin, Zhang, Weidong
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description 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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subjects Adaptative systems
Aggregation
Applied sciences
Base functions
Computer science
control theory
systems
Control theory. Systems
Dynamic linearization
Exact sciences and technology
Nonlinear system
Predictive functional control
title Adaptive predictive functional control of a class of nonlinear systems
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