Parameter estimation for chaotic systems with a Drift Particle Swarm Optimization method |
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Authors: | Jun Sun Ji Zhao Wei Fang Wenbo Xu |
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Affiliation: | a School of Information Technology, Jiangnan University, Wuxi, Jiangsu 214122, China b Key Laboratory of Industrial Biotechnology, School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China |
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Abstract: | Inspired by the motion of electrons in metal conductors in an electric field, we propose a variant of Particle Swarm Optimization (PSO), called Drift Particle Swarm Optimization (DPSO) algorithm, and apply it in estimating the unknown parameters of chaotic dynamic systems. The principle and procedure of DPSO are presented, and the algorithm is used to identify Lorenz system and Chen system. The experiment results show that for the given parameter configurations, DPSO can identify the parameters of the systems accurately and effectively, and it may be a promising tool for chaotic system identification as well as other numerical optimization problems in physics. |
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Keywords: | Chaotic systems Parameter estimation Global optimization Particle Swarm Optimization Drift motion |
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