The Research And Application For A Class Of Nonlinear System Adaptive Fuzzy Controller

Since the 1960s the modern control theory has already obtained prodigious development, and especially yields the magnificent results in the astronautics and aviation fields. Yet along with the rapid development of science and technology, it also unfolds certain limitation. The modern control theory is established at the foundation of accurate mathematical model of the controlled object, but some complex industry processes vary frequently and have high non-linearity, uncertainty, multivariable, strong coupling and hourly operation change and so on .Therefore, the mathematical model is very difficult to establish or the established mathematical model structure is extremely complex, so that it is hard to design and accomplish the control effectively. The foundation of fuzzy modeling and adaptive control of nonlinear system is the artificial intelligence, which has the ability to carry out the active control for complex uncertainty system, and it has adaptive and self-learning capability. So the in-depth research on adaptive fuzzy control of nonlinear system has important academic significances and practical values to solve the complex industry control.This thesis mainly aims at a class of nonlinear system and use adaptive fuzzy controller to conduct the research. The main works are summarized as follows:1. The problem of designing adaptive fuzzy controller of a class SISO nonlinear system is considered. The method through unifying fuzzy control, H_∞control and adaptive control in together has implemented the track question for the expected output signal. When the controller is designed we combine the expert knowledge with the fuzzy logic system, and give the parameterized adaptive regulate law of fuzzy system based on Lyapunov function, and prove the stability of fuzzy control system strictly. Finally through the simulation example, the design proposal is confirmed effective.2. The proposed design technique of SISO nonlinear system will be extended to the MIMO nonlinear system which it has boundary and outside disturbance. In the above research foundation, the problem of designing adaptive fuzzy controller of MIMO nonlinear system possessing uncertainty and outside disturbance is studied. Discuss that the parameterized adaptive regulate law of adaptive fuzzy controller is adjusted by the tracking error and the approximate error together, which causes the convergence rate for tracking error of closed-loop system to speed up and the tracking error satisfies certain H_∞performance index.3. The application of adaptive fuzzy controller has been studied in the robot movement control aspect. Take a two degree of freedom manipulator as the example, and discuss this manipulator's path track through establishing the manipulator's dynamic model. Finally simulation results verify that the proposed plan is provided with these characteristics, such as quick track speed, good dynamic performance and small tracking error.