Control And Synchronization Of Uncertain Chaotic System

As an important branch in the field of intelligent control, the technology of chaotic control and synchronization has received more and more attention in recent years. Some correlative issues in this area are studied in this paper, such as the controller design problem of uncertain chaotic systems, which have the form of linear and nonlinear input. The design and analysis procedure is based on a series of control theories, including Lyapunov stability theory, adaptive control theory, neural network approximate theory, sliding mode control theory and so on. The main work in this paper is summarized as follows.Firstly, controller using radial basis function (RBF) neural network for uncertain chaotic system is adopted. Considering the different neural network model errors upon chaotic system control precision, an improved hierarchy genetic-based RBF neural network is presented. Simulations with Henon and Lorenz system are studied, and the results are compared with other training algorithms. The results show the effectiveness of this method.Secondly, an adaptive sliding mode controller using RBF neural network for uncertain chaotic system is designed. All of the upper bounds of unknown parameters are needed to be obtained before the commencement of the design...