PID controller based adaptive GA and neural networks

被引：0

作者：

Sun, Lei ^{[1
,2
]}

Mei, Tao ^{[3
]}

Yao, Yansheng ^{[3
]}

Cai, Linqin ^{[3
]}

Meng, Max Q. -H. ^{[3
]}

机构：

[1] Chinese Acad Sci, Ctr Biomimet Sensing & Control Res, Inst Intelligent Machines, Hefei, Anhui, Peoples R China

[2] Univ Sci & Technol China, Dept Automat, Hefei, Anhui, Peoples R China

[3] Chinese Acad Sci, Inst Machine Intelligence, Ctr Biomimet Sensing & Control Res, Hefei, Anhui, Peoples R China

来源：

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年

关键词：

PID; adaptive GA; RBF; neural network;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A self-tuning PID controller based on adaptive genetic algorithm (AGA) and neural networks is presented. AGA optimizes not only the initial weights of the BP neural networks(BPNN) which optimizes parameters of PID, but also the optimum values of the following radial basis function neural networks(RBFNN) parameters: centers, variance and weights of the output layer. RBFNN identifies the Jacobian information of the controlled plant. The influence on the control performance is solved which results from the initial parameters of BPNN and RBFNN. The result of the simulation shows that the method can improve the robust performance of the control system.

引用

页码：6564 / +

页数：2

共 8 条

[1]

AKHYAR S, P 1993 INT JOINT C N

[2]

Gao Jun-shan, 2004, Electric Machines and Control, V8, P108

[3]

JIANG XY, 2004, P 5 WORLD C INT CONT

[4]

LI Z, 1996, CONTROL DECISION MET, V10, P340

[5]

Liu J., 2003, Advanced PID Control and MATLAB Simulation, V3

[6]

Niu Jian-jun, 2005, Journal of System Simulation, V17, P1425

[7]

STRINIVAS M, 1994, IEEE T SYST MAN CYB, V24, P656

[8]

Wu Zhiyuan, 1999, Control Theory & Applications, V16, P127

← 1 →