Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61161
Title: Parameter identification of chaotic systems by a novel dual particle swarm optimization
Authors: Jiang, Y
Lau, FCM 
Wang, S
Tse, CK 
Keywords: Adaptive search range
Chaotic systems
Dual particle swarm optimization
Parameter identification
Issue Date: 2016
Publisher: World Scientific
Source: International journal of bifurcation and chaos in applied sciences and engineering, 2016, v. 26, no. 2, 1650024, p. 1-16 How to cite?
Journal: International journal of bifurcation and chaos in applied sciences and engineering 
Abstract: In this paper, we propose a dual particle swarm optimization (PSO) algorithm for parameter identification of chaotic systems. We also consider altering the search range of individual particles adaptively according to their objective function value. We consider both noiseless and noisy channels between the original system and the estimation system. Finally, we verify the effectiveness of the proposed dual PSO method by estimating the parameters of the Lorenz system using two different data acquisition schemes. Simulation results show that the proposed method always outperforms the traditional PSO algorithm.
URI: http://hdl.handle.net/10397/61161
ISSN: 0218-1274
EISSN: 1793-6551
DOI: 10.1142/S0218127416500243
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