Fuzzy adaptive control is a research field which is formed basing on the development of Fuzzy control theory toward the direction of adaptive (or self-learning, self-organizing) to make the fuzzy control rules automatically in the control process to amend, improve and adjust, so that the control system performance continues to improve, to achieve the desired. Fuzzy adaptive control system as a result of the operation process can be constantly revised their own rules to improve control performance and fast convergence, robustness, and ivery applicable to nonlinear and multi-variable complex system, which is under control a wide range of community importance.Now, there are many specific approaches to the different systems in Fuzzy adaptive control theory. The designment of structure and the scope of application for each approach are different.This paper introduces Fuzzy adaptive control theory and several types of commonly used fuzzy adaptive control approaches. According to the different objects, from the point of view as fuzzy adaptive control approach of linear systems/nonlinear systems, this paper introduces Self-adaptive fuzzy PID controller, Model reference fuzzy adaptive controller (MRFAC) and Direct and Indirect adaptive fuzzy controller.According to the research of Fuzzy adaptive control approach of linear systems, compared to the convergence, error, stability, and other indicators, this paper summarizes the draw:Fuzzy adaptive control approach in the disturbance or sudden changes in object parameters, which has strong adaptability and robustness.Fuzzy adaptive control of non-linear system has become a hot area of current control research. This paper focuses on the tracking issue of affine nonlinear system, and uses the Lyapunov synthesis method to study the designment of Direct and Indirect adaptive fuzzy controller and the designment of adaptive law, then through the simulation results show the effectiveness and feasibility of designment.In addition, based on Indirect adaptive fuzzy control approach, this paper puts forward a method to select the parameters which are the two parametersγ1,γ2 in relation to self-learning law, and the parameterh of simulation step-size, and give the value range of these three parameters in theory. In this paper, the simulation is about the inverted pendulum tracking model, then verifies the effectiveness of the method to select the parameters. Based on the simulation results, this paper sums up the law of the impact of system performance by the changes of the parameters. |