Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method

doi:10.1088/1674-1056/21/5/050507

Abstract We study the parameter estimation of a nonlinear chaotic system, which can be essentially formulated as a multi-dimensional optimization problem. In this paper, an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems. This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy. Experiments are conducted on the Lorenz system and the Chen system. The proposed algorithm is used to estimate the parameters for these two systems. Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.

Keywords: cuckoo search algorithm chaotic system parameter estimation orthogonal learning

Received: 20 September 2011
Revised: 27 April 2012
Accepted manuscript online:

PACS:

05.45.Pq

(Numerical simulations of chaotic systems)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 60473042, 60573067 and 60803102).

Cite this article:

Li Xiang-Tao(李向涛) and Yin Ming-Hao(殷明浩) Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method 2012 Chin. Phys. B 21 050507

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Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method

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