An intelligent position control of electrohydraulic drive using hybrid fuzzy control structure

Abstract

Improved characteristics of fluid power actuators due to integration of electronics and fluid power technologies have already become standard. Valves can be electronically actuated and can control hydraulic power quickly and accurately. There are sensors capable of transforming fluid power and mechanical variables into electronic signals. Appropriate control strategies and sophisticated control algorithms are required to overcome the disadvantages and nonlinear dynamic behavior of hydraulic drives. This is successfully obtainable only by implementation of digital control systems designed on the basis of modern control theory. Several types of conventional PID-controllers, adaptive controllers and fuzzy logic controllers have been developed. The purpose of the research work described in this paper was to explore the possibilities of inserting self-learning and self-organising characteristics into control algorithms for control of electrohydraulic drives. The proposed reinforcement learning method enables a faster adaption on parameter changes than some traditional learning methods. The results of experimental investigations are also shown.