Stability analysis of a T-S fuzzy stochastic PSO model

摘要：

Many theoretical and experimental results have appeared recently on the stability of T-S fuzzy systems and the convergence of the Particle Swarm Optimization (PSO) algorithm. In this paper, we present a T-S fuzzy stochastic PSO model in which the PSO algorithm is viewed as a time-invariant linear plant with a time-varying feedback controller that is embedded in the T-S fuzzy state system. The randomly weighted sum of the cognition component and social component is used as the state feedback controller in the local linear state system, and the PSO algorithm is theoretically improved from one that performs single stochastic optimization to one that performs fuzzy stochastic optimization. Conditions for asymptotic stability of the new model are given using the T-S fuzzy stability theory.

关键词： Particle Swarm Optimization T-S fuzzy theory Asymptotic stability

作者: JiQiang FENG WeiXin XIE Chen XU

作者单位: Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China Institute of Intelligent Computing Science, Shenzhen University, Shenzhen, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1433-1436

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）