混沌的模糊神经网络逆系统控制

提出用Sugeno型的模糊推理神经网络建立混沌系统的逆系统模型,并采用逆系统方法进行混沌的控制.这种方法的特点是可以不必建立混沌系统的解析模型,通过模糊神经网络学习混沌系统的运动规律,通过学习获得的规律对混沌进行有效的控制,并且该控制方法可以控制混沌系统以一定精度跟踪连续变化的给定信号.理论分析及针对虫口模型和Henon模型仿真研究证明了该方法的有效性 关键词： 混沌 模糊神经网络 逆系统控制

Inverse-system control of chaos using fuzzy-neural network

The Sugeno fuzzy-neural network is employed to establish the inverse system model of chaotic system, and the inverse system method is used to control chaos. The characteristic of this method is to learn the dynamics of a chaotic system and control chaos effectively with the knowledge obtained instead of establishing an analytical model of the chaotic system; moreover, this method does not require the control object to be a stationary point or periodic trajectory. Theoretical analysis and simulations with the Logistic and Henon models prove that this method is effective.