不确定混沌系统的直接自适应模糊神经网络控制

Direct adaptive fuzzy-neural control of unknown chaotic system

提出利用直接自适应模糊神经网络控制一类不确定非线性混沌系统新方法 .采用Takagi_Sugeno模糊逻辑系统估计混沌对象中未知函数 ,然后再对模糊神经网络控制律参数进行在线调整 ,在系统所有信号一致有界情形下 ,解决混沌状态跟踪给定参考轨道控制问题 .

A novel direct adaptive fuzzy neural networks(FNNs)controller for a class of uncertain nonlinear chaotic system is presented.Takagi-Sugeno fuzzy logic systems are applied to estimate the unknown function of the chaotic system,then the parameters of adaptive FNNs control law are on-line tuned so that the tracking problem is realized,i.e.to force the solutions of the chaotic plant to follow a certain given trajectory under the condition that all signals involved are uniformly bounded.Simulation results show the validity of the obtained result.