压电谐振混沌系统参数辨识的蚁群优化方法

2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA) Pub Date : 2015-12-01 DOI:10.1109/STA.2015.7505182

F. Maamri, S. Bououden, I. Boulkaibet

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引用次数: 6

摘要

本文将蚁群优化算法应用于压电谐振器的离线参数辨识。将压电混沌谐振器的未知控制参数作为参数向量，应用所提出的蚁群算法对参数精确值进行最优估计。采用蚁群优化算法求解非线性混沌谐振器的最优控制参数，使估计输出与实际输出之间的误差最小。压电谐振器系统的仿真结果表明，蚁群算法用于参数辨识的有效性，并给出了混沌压电谐振器的稳定振荡。

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An Ant colony optimization approach for parameter identification of piezoelectric resonator chaotic system

In this paper, the Ant colonies optimization (ACO) algorithm is used for offline parameters identification of piezoelectric resonator. The unknown control parameters of the piezoelectric chaotic resonator are taken as a parameter vector, and will be estimated optimally for the exact values of parameters with the application of the proposed ACO algorithm. The Ant colony optimization algorithm is used to find the optimal control parameters of the nonlinear chaotic resonator by minimizing errors between the estimated and actual output. Simulation results of piezoelectric resonator system shows that the ACO algorithm is applied to illustrate the effectiveness for the parameter identification and gives a stable oscillation of the chaotic piezoelectric resonator.

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2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

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