Adaptively fuzzy iterative learning control for SRM direct-drive volume control servo hydraulic press

Abstract

Hydraulic press as a kind of very important press machining equipment has been widely used in national defense and civilian industry. This paper developed a new kind of hydraulic press that synthesizes the advantages of both hydraulic and SRM (Switched Reluctance Motor) driving technology. Aiming at the serious nonlinearity and time-variability existing in electro-hydraulic servo system of pump-controlled cylinder, the ILC (Iterative Learning Control) method was applied to track the shift curve. The fuzzy strategy was utilized to adjust the iterative learning gain adaptively in order to improve the convergence speed and precision of ILC. The simulation and experimental results show that the iterative learning speed is raised enormously by this method, and tracking of the slider shift curve with high response speed and control accuracy is realized.