MULTIVARIABLE SELF-TUNING PID CONTROLLER BASED ON WAVELET FUZZY NEURAL NETWORKS

被引：0

作者：

Lu, Chi-Huang ^{[1
]}

Liao, Pen-Yu ^{[1
]}

Charng, Yuan-Hai ^{[2
]}

Liu, Chi-Ming ^{[1
]}

Guo, Jheng-Yu ^{[1
]}

机构：

[1] Hsiuping Univ Sci & Technol, Dept Elect Engn, Taichung, Taiwan

[2] Hsiuping Univ Sci & Technol, Dept Mech Engn, Taichung, Taiwan

来源：

PROCEEDINGS OF 2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOL 2 | 2014年

关键词：

Multivariable system; Generalized predictive control; PID controller; Self-tuning; Wavelet fuzzy neural network; GENERALIZED PREDICTIVE CONTROL; NONLINEAR-SYSTEMS; DISCRETE-TIME; DESIGN;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a multivariable self-tuning proportional-integral-derivative (PID) controller based on wavelet fuzzy neural networks (WFNNs) for a class of nonlinear systems. A mathematic model using WFNN is constructed for the controlled nonlinear multivariable system, and the self-tuning PID controller is derived via a generalized predictive performance criterion. Numerical simulations exhibit that the proposed multivariable self-tuning PID control law gives satisfactory tracking and disturbance rejection performances.

引用

页码：755 / 759

页数：5

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