Research And Application Of Fuzzy Control On Long Time Delay Systems

The long time delay phenomenon within the industry process is very widespread its existence affected the stability of the system seriously, cause system overshot become big, adjust time to lengthen consumedly, even appear to flap and dissipation, the dynamic quality of the system becomes obviously bad. It is difficult to get satisfactory results using the traditional control strategies. Fuzzy control can work effectively in the situation that no mathematical model exists. This paper uses fuzzy control on long time delay systems, but the selection of control rules are according to the experience, which is the bottleneck of fuzzy controller design process. This paper based on the research status and development trend of fuzzy control in recent years, and on the basis of fuzzy rules improves the fuzzy controller, the main work are as follows:First, combined the fuzzy control with the traditional PID control, design a fuzzy adaptive PID controller, it can optimize the controller parameters in real-time, constitute the function with parameter self-adaptive intelligent control systems.Then, the fuzzy linguistic variable membership function are adjusted adaptively, designed a fuzzy controller based on variable membership function, by changing the shape and the initial position of the membership function, can adjustment the membership function in real-time, so that the determine of the membership function is more rationalization, indeed achieve the target of objective adjustment fuzzy rules, so that achieve the desired control results.Finally, through derived fuzzy rules analytical expressions, design a kind of subsection analytic fuzzy controller, according to the characteristics and the change of the process parameters of system, using different fuzzy control rule bases, in the corresponding state to achieve better control effect. Then design a kind of multi-parameter paste controller which can automatic on-line adjusting control rules, using multi-parameter analytic description to describe the fuzzy control rules by least-squares method, then use genetic algorithms to optimize its parameters, automatically generate or adjust the rules and parameters, improved the performance of the fuzzy controller, also enhanced the ability to adapt to the environmental changes.