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
收藏
页码：1880 / +
页数：3
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