Fine control of monotonic systems using a global self-learning adaptive fuzzy controller

被引：0

作者：

Pomares, H ^{[1
]}

Rojas, I ^{[1
]}

Herrera, LJ ^{[1
]}

Gonzalez, J ^{[1
]}

Prieto, A ^{[1
]}

机构：

[1] Univ Granada, Dept Comp Architecture & Comp Technol, E-18071 Granada, Spain

来源：

2004 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3, PROCEEDINGS | 2004年

关键词：

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：

The goal of this paper is to achieve real time control of a monotonic system which, in general, may be non-linear and whose differential equations are unknown. We assume that there is no model of the plant available so there cannot be any offline pre-training of the main controller parameters. We propose a both adaptive and self-learning algorithm capable of starting from a "void" fuzzy controller and, in real time, optimizing the fuzzy controller's rules (both antecedents and consequents) in order to translate the state of the plant to the desired value in the shortest possible time.

引用

页码：1299 / 1303

页数：5

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