Genetically Generated Double-Level Fuzzy Controller with a Fuzzy Adjustment Strategy

被引：0

作者：

Achiche, Sofiane ^{[1
]}

Wei, Wang ^{[1
]}

Fan, Zhun ^{[1
]}

Ozkil, Ali ^{[1
]}

Sorensen, Torben ^{[1
]}

Wang, Jiachuan ^{[2
]}

Goodman, Erik ^{[3
]}

机构：

[1] Tech Univ Denmark, Nils Koppels Alle,Bldg 404, DK-2800 Lyngby, Denmark

[2] United Technol Res Ctr, Syst Dept, E Hartford, CT 06128 USA

[3] Michigan State Univ, E Lansing, MI 48823 USA

来源：

GECCO 2007: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2 | 2007年

基金：

加拿大自然科学与工程研究理事会;

关键词：

Genetic algorithm; fuzzy logic controller; modularity;

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 describes the use of a genetic algorithm (GA) in tuning a double-level modular fuzzy logic controller (DLMFLC), which can expand its control working zone to a larger spectrum than a single-level FLC. The first-level FLCs are tuned by a GA so that the input parameters of their membership functions and fuzzy rules are optimized according to their individual working zones. The second-level FLC is then used to adjust contributions of the first-level FLCs to the final output signal of the whole controller, i.e., DLMFLC, so that it can function in a wider spectrum covering all individual working zones of the first-level FLCs. The second-level FLC is again optimized by a GA. An inverted pendulum system (IPS) is used to demonstrate the feasibility of the approach.

引用

页码：1880 / +

页数：3

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