Genetic algorithms for learning the rule base of fuzzy logic controller

被引：51

作者：

Chin, TC ^{[1
]}

Qi, XM ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

来源：

FUZZY SETS AND SYSTEMS | 1998年 / 97卷 / 01期

关键词：

fuzzy logic control; genetic algorithms; rule base; inverted pendulum;

D O I：

10.1016/S0165-0114(96)00354-5

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, genetic algorithms are used in the study to maximise the performance of a fuzzy logic controller through the search of a subset of rule from a given knowledge base to achieve the goal of minimising the number of rules required. Comparisons are made between systems utilising reduced rules and original rules to verify the outputs. As an example of non-linear system, an inverted pendulum will be controlled by minimum rules to illustrate the performance and applicability of this proposed method. (C) 1998 Elsevier Science B.V. All rights reserved.

引用

页码：1 / 7

页数：7