Duffing-Holmes型振子混沌系统的控制

The Control of DuffingHolmes Oscillator Chaotic System

对Duffing-Holmes型振子混沌系统进行动力学分析,发现其内部蕴含着丰富的动力学特性,在适当的参数取值下会体现出混沌系统的特性.采用自适应控制方法对Duffing-Holmes型振子混沌系统进行控制,利用RBF神经网络逼近系统模型中的非线性项,通过设计合适的控制器和参数自适应律,从理论上对此受控系统进行了稳定性分析,并进行系统数值仿真,受控系统变量能够在很短时间内跟踪期望目标值.而且和采用输入-状态线性化控制方法及基于RBF神经网络逼近非线性项的滑模控制方法相比较,具有快速性更好、稳定性更高的特点.

A dynamic analysis of DuffingHolmes oscillator chaotic system was conducted,revealing that the system is characterized by an extensive range of dynamic traits.With suitable parameter settings,these traits can exhibit the properties of a chaotic system.The adaptive control method was used to control the chaotic system with the RBF neural network to approximate the nonlinear term of the system model.A tailored controller and parameter adaptation rule were designed to theoretically assess and numerically simulate the stability of the controlled system,enabling system variables to rapidly follow desired target values.Compared with the control methods through inputstate linearization and the sliding mode based on RBF neural network approximating nonlinear term,the approach presented in this paper,distinguished by its rapid response and high stability,has achieved the set control goals and demonstrated its validity.