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
收藏
页码：755 / 759
页数：5
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