Fuzzy modeling strategy for control of nonlinear dynamical systems

Authors:
Bin Ye;Chengzhi Zhu;Chuangxin Guo;Yijia Cao
Affiliations:
College of Electrical Engineering, National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, Zhejiang, China;College of Electrical Engineering, National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, Zhejiang, China;College of Electrical Engineering, National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, Zhejiang, China;College of Electrical Engineering, National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, Zhejiang, China
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Year:
2005

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Abstract

This paper presents a novel fuzzy modeling strategy using the hybrid algorithm EPPSO based on the combination of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) for control of nonlinear dynamical systems. The EPPSO is used to automatically design fuzzy controllers for nonlinear dynamical systems. In the simulation part, one multi-input multi-output (MIMO) plant control problem is performed. The performance of the suggested method is compared to that of EP, PSO and HGAPSO in the fuzzy controllers design. Simulation results demonstrate the superiority of the proposed method.