PMID: 16649564May 3, 2006Paper

Adaptive predictive functional control of a class of nonlinear systems

ISA Transactions
Bin Zhang, Weidong Zhang

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.

Citations

Nov 1, 2011·ISA Transactions·Tufan KumbasarEngin Yesil
Dec 8, 2011·IEEE Transactions on Neural Networks·Zhongsheng Hou, Shangtai Jin
Apr 15, 2019·Water Research·Kathryn B NewhartTzahi Y Cath

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