In the past twenty years, fuzzy control has gained tremendous acceptance in academia and industry. Especially, fuzzy PID control therein played important role. It reasonable to predict that fuzzy PID control will continue to be developed and used. In the dissertation, the systematic design methodology of the one-input fuzzy PID controller is studied based on the existed achievement on fuzzy PID control. Main works and contributions of this dissertation are as follows. 1. Based on the analysis of the structure of fuzzy PID controllers and the comparison of typical fuzzy PID with different structures, two criteria are provided to choose beneficial fuzzy PID controllers. Considering the wide application of conventional PID controllers due to their simplicity and effectiveness, the fuzzy PID controllers that have similar structures as, and work in a way similar to, the conventional ones, are especially emphasized. Also, the simplicity of gain tuning is important. The criteria are used as guide for selecting appropriate fuzzy PID control structure. Consequently, the one-input fuzzy PID controllers have advantages according to the criteria. 2. The nonliearity of the one-input fuzzy PID controllers is analyzed. Two step tuning method of the fuzzy PID is introduced. First, linear PID is generated and tuned to control plants, then fuzzy nonlinear part is introduced to improve the performance of linear PID control loop. The effect of different types of nonlinear curves to the performance is studied, and heuristic tuning rules of nonlinear parameters of the fuzzy PID are constructed. The numerical simulation shows the validation of the method. Based on the tuning rules, expert auto-tuning fuzzy PID tuner is proposed. Considering the applicability and inexpensive cost, the dissertation develops the construction of the fuzzy PID on the bases of PID control software commercially available on the market. 3. Based on the comparison of several nonlinear stability criteria, it is found that the Circle Criteria is suitable to analyze the stability of the fuzzy PID control systems, and the stability condition of the fuzzy PID control systems is derived from the Circle Criteria. The effect of different types of nonlinear curves to the stability of the system is analyzed. In the frame-work of optimization with constraint, the optimal robust performance design method for perturbed plant model is developed. The Genetic algorithm is used as optimization solver with the stability condition derived being constraint. Numerical simulation verified the effectiveness of the procedure.
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