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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | JiQiang Feng WeiXin Xie Chen Xu |
| Copyright Year | 2010 |
| Description | Author affiliation: Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China (JiQiang Feng; WeiXin Xie) || Institute of Intelligent Computing Science, Shenzhen University, Shenzhen, China (Chen Xu) |
| Abstract | 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. |
| Starting Page | 1433 |
| Ending Page | 1436 |
| File Size | 105005 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458974 |
| e-ISBN | 9781424459001 |
| DOI | 10.1109/ICOSP.2010.5656944 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Stochastic processes Stability analysis Particle swarm optimization Mathematical model Analytical models Asymptotic stability Optimization Particle Swarm Optimization T-S fuzzy theory |
| Content Type | Text |
| Resource Type | Article |
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