The Control of DuffingHolmes Oscillator Chaotic System
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.
RBF neural networkDuffingHolmes oscillatorcontrol lawadaptive law
万方数据
维普
