Control of chaos solely based on RBF neural network without an analytical model
基于径向基函数神经网络的未知模型混沌系统控制

An intelligent control method based on RBF neural network is proposed for chaos control- The control objective can be either periodic orbits or continuous variable functions without the need of an analytic model- The method is still effective when there are parameter perturbation and measurement noise- The influence of the RBF model error upon control precision is studied, and related theorem is developed and testified- Simulation results with a Logistic mapping and Henon attractor show the effectiveness and feasibility of this method-