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首页> 外文会议>International Conference on Fuzzy Systems and Knowledge Discovery(FSKD 2005) pt.1; 20050827-29; Changsha(CN) >Construction of Fuzzy Models for Dynamic Systems Using Multi-population Cooperative Particle Swarm Optimizer
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Construction of Fuzzy Models for Dynamic Systems Using Multi-population Cooperative Particle Swarm Optimizer

机译：多种群协同粒子群优化器的动态系统模糊模型构建

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摘要

A new fuzzy modeling method using Multi-population Cooperative Particle Swarm Optimizer (MCPSO) for identification and control of nonlinear dynamic systems is presented in this paper. In MCPSO, the population consists of one master swarm and several slave swarms. The slave swarms execute Particle Swarm Optimization (PSO) or its variants independently to maintain the diversity of particles, while the particles in the master swarm enhance themselves based on their own knowledge and also the knowledge of the particles in the slave swarms. The MCPSO is used to automatic design of fuzzy identifier and fuzzy controller for nonlinear dynamic systems. The proposed algorithm (MCPSO) is shown to outperform PSO and some other methods in identifying and controlling dynamic systems.
机译：提出了一种基于多种群合作粒子群优化器（MCPSO）的非线性动力学系统辨识和控制的模糊建模方法。在MCPSO中，种群由一个主群和几个从群组成。从属群独立执行粒子群优化（PSO）或其变体以维护粒子的多样性，而主群中的粒子基于自身知识以及从属群中的粒子知识来增强自身。 MCPSO用于非线性动态系统的模糊标识符和模糊控制器的自动设计。结果表明，所提出的算法（MCPSO）在识别和控制动态系统方面优于PSO和其他方法。

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