基于神经网络反馈控制的混沌运动的仿真研究

摘要：本文应用神经网络反馈控制策略，对混沌系统进行控制研究。首先利用神经网络能够高精度逼近非线性系统的特点，通过系统辨识建立要研究的混沌系统的神经网络模型，然后控制器应用此系统模型对混沌运动进行反馈线性化控制，将混沌吸引子中的不稳定周期轨道镇定到不动点，或诱导到各个周期轨道。对Lorenz混沌系统的仿真结果表明，神经网络反馈控制混沌的方法具有有效性。

Simulation Research of Chaotic Motion Based on Neural Network Feedback Control

Abstract: The chaotic motion control of Lorenz system is studied by using neural network feedback method. First, the neural network model of the chaotic Lorenz system is established by system identification. Then the feedback control is applied to the chaotic motion by the controller using the system model to control the unsteady periodic track in the chaotic attractor to the fixed point. Simulation results show that the method is effective in the chaotic motion control.