Group-based evolutionary swarm intelligence for recurrent fuzzy controller design

Chia Feng Juang*, I. Fang Chung, Shin Kuan Chen

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Recurrent fuzzy controller design by the hybrid of Multi-group Genetic Algorithm and Particle Swarm Optimization (R-MGAPSO), is proposed in this paper. The recurrent fuzzy controller designed here is the Takagi-Sugeno-Kang (TSK)-type Recurrent Fuzzy Network (TRFN). Both the number of fuzzy rules and parameters in TRFN are designed concurrently by R-MGAPSO. Evolution of population consists of three major operations: group enhancement by particle swarm optimization, variable-length individual crossover and mutation. To verify the performance of R-MGAPSO, control of a dynamic plant is simulated and compared with other genetic algorithms

原文English
主出版物標題2006 IEEE International Conference on Fuzzy Systems
頁面1710-1714
頁數5
DOIs
出版狀態Published - 2006
事件2006 IEEE International Conference on Fuzzy Systems - Vancouver, BC, Canada
持續時間: 16 7月 200621 7月 2006

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

Conference

Conference2006 IEEE International Conference on Fuzzy Systems
國家/地區Canada
城市Vancouver, BC
期間16/07/0621/07/06

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