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Acceleration factor harmonious particle swarm optimizer

  • Jie ChenEmail author
  • Feng Pan
  • Tao Cai
Article

Abstract

A Particle Swarm Optimizer (PSO) exhibits good performance for optimization problems, although it cannot guarantee convergence to a global, or even local minimum. However, there are some adjustable parameters, and restrictive conditions, which can affect the performance of the algorithm. In this paper, the sufficient conditions for the asymptotic stability of an acceleration factor and inertia weight are deduced, the value of the inertia weight w is enhanced to (−1,1). Furthermore a new adaptive PSO algorithm — Acceleration Factor Harmonious PSO (AFHPSO) is proposed, and is proved to be a global search algorithm. AFHPSO is used for the parameter design of a fuzzy controller for a linear motor driving servo system. The performance of the nonlinear model for the servo system demonstrates the effectiveness of the optimized fuzzy controller and AFHPSO.

Keywords

Particle swarm optimizer acceleration factor harmonious PSO asymptotic stability global convergence fuzzy control 

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Copyright information

© Institute of Automation, Chinese Academy of Sciences 2006

Authors and Affiliations

  1. 1.Department of Automatic Control, School of Information Science and TechnologyBeijing Institute of TechnologyBeijingPRC

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