Tracking And Synchronization Control For Nonlinear Systems Based On Adaptive Fuzzy Logic Systems

Fuzzy control is based on practical experience, and through better fuzzy rules and parameters design of the fuzzy logic system to ensure the control effect. Ever since its birth in the year of1965, fuzzy control theory has obtained several achievements in both theory development and practical application. In the aspect of application, fuzzy control has realized over flight from the simple control of the steam engine to the aeronautic attitude control; in the aspect of theory, from initial fuzzy theory on the basis of the lack of to the demonstration of the universal approximation ability of the fuzzy system, from the fuzzy logic system only relied on the practical experience to the appearance of the adaptive fuzzy logic system(AFLS) with self-organization, adaptive learning function and adaptive fuzzy control(AFC),all of this shows that the fuzzy theory and fuzzy control have the unique charm of science.In the beginning, this thesis introduces the fundamental knowledge of fuzzy logic system, these are briefly introduced respectively, including the fuzzy set. the structure of fuzzy logic system and the classification of fuzzy logic system, and lay the foundation for the subsequent designs of fuzzy modeling and fuzzy control in this thesis.Then, from the engineering application point of view, aimed at a class of nonlinear strict-feedback triangle system with uncertain, this thesis firstly provides the ideal signal tracking controller and the ideal output stability controller according to a kind of conventional controller design method, then under the condition of the ideal controllers which contain the unknown functions of the nonlinear system, through the parameter identification method in fuzzy modeling, the adaptive fuzzy logic systems with self-learning function are designed to approximate the unknown functions by utilizing the data information sampled from the inputs and outputs of the unknown functions, finally the constructed adaptive fuzzy logic systems are applied to the ideal controllers to replace the unknown functions, and to form the fuzzy controllers and complete the tracking control and output stability control of the signal. The validity of the method in this thesis is illustrated through the pendulum simulation. Finally, for a class of complex nonlinear system with chaos phenomenon, completed the design of synchronization controller of the drive-response chaotic system. Firstly, design a kind of adaptive fuzzy logic systems to approximate the unknown nonlinear functions in the system, then with the help of design idea based on observer, combined the Lyapunov stability theorem to design and analyze of drive-response synchronization control, finally, the designed adaptive fuzzy logic systems are applied to the synchronization controller of the drive-response chaotic systems, so as to complete the synchronization control for a class of chaotic systems. The validity and advantage of the method are illustrated through the synchronization simulation about Lorenz and Duffing chaotic systems.