混沌系统的遗传神经网络控制

Genetic-based neural network control for chaotic system

提出遗传神经网络控制混沌新方法 .将小扰动技术和周期控制技术结合起来 ,用遗传算法训练神经网络 ,使之成为混沌控制器 .对Henon映射和Logistic映射的仿真结果说明控制器能产生小扰动控制序列信号 ,将混沌振荡转变成规则运动状态 .该方法无需了解动态系统数学模型 ,具有一定抗噪声干扰能力 ,可将它推广应用到其他混沌系统的控制中 .

A novel genetic-based neural network control for chaos is presented. The method proposed has been successfully applied to control two simulated chaotic systems by incorporating the techniques of small perturbations and the periodic control in this paper. The simulation results showed that the neural network trained by genetic algorithm can learn to produce a series of small perturbations to convert chaotic oscillations of a chaotic system into desired regular ones. The scheme requires no knowledge about the mathematical model. Moreover, the approach is reasonably robust to noise, it can be extended to control other chaotic systems.