Some Control Problem for Chaos System Lü Based on T-S Fuzzy Model
|School||Beijing Jiaotong University|
|Course||Control Theory and Control Engineering|
|Keywords||T - S fuzzy model Tracking feedback control Robust Control Guaranteed Cost Control Lü chaotic systems Linear matrix inequality (LMI)|
With the development of science and technology, control methods continue to progress and improve, more and more of the control method is applied to study the new scientific problems. Chaotic systems has attracted widespread attention as a new discipline, L (u | ¨) chaotic systems as a special class of chaotic systems especially attracting much attention in recent years. On the other hand, the fuzzy control is an important branch of intelligent control, and mature linear system theory of nonlinear control problems can borrow based on TS model fuzzy control. Currently, the fuzzy theory is applied to the study of the chaotic system control problems have made some achievements. But is relatively small, most of the major achievements of the stability analysis. This article is the TS fuzzy methods used in chaotic systems, and strive to facilitate the solution of certain control problems. The stability is the most important indicator of the control system design. The chaotic nature of the system is a nonlinear control systems, stability analysis more difficult. For complex chaotic system with nonlinearity and uncertainty, fuzzy control may well be a strong complement of traditional control theory, TS fuzzy traditional control theory and fuzzy control model is proposed since good combination. TS fuzzy model has blurred under the framework of linear form characteristics, which makes it possible to study the stability problem of the fuzzy system using Lyapunov stability theory, the theory of linear uncertain systems. Therefore, this article uses the TS fuzzy model to analyze and solve L (u | ¨) chaotic system stability. On the basis of the previous chaotic system using TS fuzzy model approximation using Schur complement, the distribution of compensation, the weighted average defuzzification method, fuzzy controller design, and to study their guaranteed cost control, robust control, tracking control problem. TS fuzzy model can well realize the linearization of the nonlinear system, and play a very effective role in the design of the controller. The simulation results also underlined the TS fuzzy model chaotic system is great potential. Thesis statement of work, for chaotic systems, linear after pieces of TS fuzzy model to take full advantage of the local information and expert control experience to arbitrary precision approximation of the actual control object. In addition, fuzzy control study of chaotic systems can provide another idea for the study of ordinary fuzzy system, to some extent enrich ordinary fuzzy system research.