连续混沌系统的非线性自适应预测跟踪控制

基于混沌时间序列的非线性自适应预测原理,用一种sigmoid-Volterra自适应预测滤波器研究了连续混沌系统的非线性自适应预测跟踪控制.通过对Lorenz,R?ssler等典型混沌系统的控制,仿真证实了这种sigmoid-Volterra自适应预测控制器的有效性.这种方法的优点在于它既不需要知道精确的混沌系统模型,也不需要进行系统模型辨识.关键词：混沌sigmoid-Volterra自适应预测滤波器非线性自适应预测跟踪

NONLINEAR ADAPTIVE PREDICTIVE TARGETING CONTROL OF THE CONTINUOUS CHAOTIC SYSTEMS

The sigmoid-Volterra adaptive predictors are used to perform nonlinear adaptive predictive targeting control of chaos in continuous chaotic systems based on the nonlinear adaptive predictive principle of chaotic time series, where the nonlinear adaptive controller acts on only one-dimensional time series coming from the chaotic state of the controlled system. This adaptive predictive targeting controller can control the system to any desired state by means of adaptive cancellation. Computer simulation results on the Lorenz and Rǒssler systems are shown to demonstrate the effectiveness of this nonlinear adaptive predictive targeting control method. The advantages of this new method are that it does not need to know the accurate equations or to identify the system′s model of the controlled chaotic systems.