A multiple population genetic algorithm and its application in fuzzy controller

Tian, Yukang and Vu, Huy Quan 2010, A multiple population genetic algorithm and its application in fuzzy controller, in IITSI 2010 : Proceedings of the 3rd International Symposium on Intelligent Information Technology and Security Informatics, IEEE, Piscataway, N.J., pp. 729-733.

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Title A multiple population genetic algorithm and its application in fuzzy controller
Author(s) Tian, Yukang
Vu, Huy Quan
Conference name International Symposium on Intelligent Information Technology and Security Informatics (3rd : 2010 : Jinggangshan, China)
Conference location Jinggangshan, China
Conference dates 2-4 Apr. 2010
Title of proceedings IITSI 2010 : Proceedings of the 3rd International Symposium on Intelligent Information Technology and Security Informatics
Editor(s) Yu, Fei
Peng, Xuange
Liu, Haiwen
Shu, Jian
Ng, Roy
Publication date 2010
Conference series International Symposium on Intelligent Information Technology and Security Informatics
Start page 729
End page 733
Total pages 5
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) genetic algorithm
fuzzy control
inverted pendulum
Summary Genetic Algorithm is an important optimization technique, though its application in Fuzzy system is usually limited by problems like local optimal and premature convergence. With an aim to improve the performance of simple Genetic Algorithm, we propose a multi-population genetic algorithm MP-GA which uses two populations collaborating with each other, and apply it to fuzzy controller design to optimize its control rules. The simulation results of Inverted Pendulum demonstrate the effectiveness of this proposed method.
ISBN 9780769540207
Language eng
Field of Research 080503 Networking and Communications
Socio Economic Objective 890199 Communication Networks and Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2010
Copyright notice ©2010, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30034425

Document type: Conference Paper
Collection: School of Information Technology
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