A learning algorithm of CMAC based on RLS

被引：15

作者：

Qin, T ^{[1
]}

Chen, ZH ^{[1
]}

Zhang, HT ^{[1
]}

Li, SF ^{[1
]}

Xiang, W ^{[1
]}

Li, M ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2004年 / 19卷 / 01期

关键词：

CMAC; CMAC-PID controller; nonlinear plant; recursive least squares algorithm;

D O I：

10.1023/B:NEPL.0000016847.18175.60

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Conventionally, least mean square rule which can be named CMAC-LMS is used to update the weights of CMAC. The convergence ability of CMAC-LMS is very sensitive to the learning rate. Applying recursive least squares (RLS) algorithm to update the weights of CMAC, we bring forward an algorithm named CMAC-RLS. And the convergence ability of this algorithm is proved and analyzed. Finally, the application of CMAC-RLS to control nonlinear plant is investigated. The simulation results show the good convergence performance of CMAC-RLS. The results also reveal that the proposed CMAC-PID controller can reject disturbance effectively, and control nonlinear time-varying plant adaptively.

引用

页码：49 / 61

页数：13

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