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Based on Extended T-S Fuzzy Model of Self-Adaptive Disturbed PSO Algorithm

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2 Author(s)
Wang Jian-Fang ; Coll. of Comput., Northwestern Polytech. Univ., Xi'an, China ; Li Wei-Hua

The PSO (particle swarm optimization) algorithm is applied to non-linear process, and is easy to be run into local optimum. The PSO algorithm is improved by T-S (Takagi-Sugeno) fuzzy model, although it solved the non-linear features of PSO algorithm, the PSO algorithm is still inability once in holding stop pattern. Thus, the membership function of the T-S fuzzy model extend the Gaussian function, the membership function is changed self-adaptively according to the actual situation. In the paper, based on extended T-S fuzzy model of self-adaptive disturbed PSO (ETSD-PSO) algorithm is presented. The results of the simulation and comparative analysis show that ETSD-PSO algorithm in both performance and precision, or when the PSO algorithm hold stop pattern achieve very good results.

Published in:

2009 Second International Conference on Information and Computing Science  (Volume:3 )

Date of Conference:

21-22 May 2009