Volterra series identification method based on adaptive ant colony optimization

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Journal of Vibration and Shock ›› 2011, Vol. 30 ›› Issue (10) : 35-38.

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Volterra series identification method based on adaptive ant colony optimization

Li Zhi-nong1; Tang Gao-song2; Xiao Yao-xian1; Wu Guan-hua1

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Abstract

A Volterra series identification method based on Adapt Ant Colony Optimization (AACO) algorithm is proposed. In the proposed method, the Volterra kernel is identified by ant colony optimization algorithm. the parameters of the ant colony algorithm can be adaptively adjusted as the incre.ase of evolution number. At the same time, the proposed method are compared with the Volterra kernel identification method based on basic ant colony optimization (ACO). The simulation result shows that the proposed method and ACO identification method have good identification accuracy, convergence stability and robust anti-noise performance whether in the noise-free or noise environment. However in the convergence speed, the proposed method is supirior to the ACO identification method.

Key words

adapt ant colony optimization (aaco) / volterra series / nonlinear system / system identification

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Li Zhi-nong;Tang Gao-song;Xiao Yao-xian;Wu Guan-hua. Volterra series identification method based on adaptive ant colony optimization[J]. Journal of Vibration and Shock, 2011, 30(10): 35-38