Hydraulic Servo Control System Of Fuzzy Control

This paper is a research for how to solve some problems which are parameters in time-varying, external load disturbance, nonlinear and some other issues in the hydraulic servo system, and to design an appropriate control strategy for controlling this kind of system. Because of hydraulic servo system precisely have these series of uncertainties questions, making conventional PID control can not achieve better control effects, and fuzzy control does not need a precise mathematical model so that it can come true real-time more easier with the plant that have such as uncertainty, non-linear problems. Therefore, this paper will use the method of fuzzy control to command hydraulic servo control system.In this paper, after the introduction of hydraulic servo system and the theoretical basis of fuzzy control, we design of the conventional PID control system and fuzzy control system respectively with the mathematical model of hydraulic servo system; and based on both the basic control system, we increase the reference model and the fuzzy adaptive institutions two parts to constitute the model reference fuzzy adaptive control system (MRFAC).The reason why fuzzy adaptive institutions is necessary because the hydraulic servo system often has more than third-ranks, using the conventional adaptive institutions algorithms is very complex, and that in the process of controlling it will use more memory and more time, so it's not satisfied for the quality of rapid, the fuzzy control does not require the precise mathematical model, and the reaction course is relatively simple and convenient, so it can be gradually replaced by adaptive institutions. Though the control system simulation, this paper shows that the design of these control systems can be resolved the problems well for hydraulic servo system, with have better control effects, such as better tracking precision, better static and dynamic performance and so on. At last we can prove the design's feasibility with this model reference fuzzy adaptive control system.