A robust control of electro hydrostatic actuator using the adaptive back-stepping scheme and fuzzy neural networks

Abstract

In general, the position control of electro hydrostatic actuator(EHA) systems is difficult because of the large variation of the effective bulk modulus of the working fluid, which is due to the absence of a heat exchanger like a reservoir tank, the friction between the cylinder and piston, and the external disturbance force. Moreover, it is difficult to identify the values of the effective bulk modulus and friction. In this paper, the variation of the effective bulk modulus, friction, and external disturbance are considered as uncertainties of EHA systems. To solve the problems due to these system uncertainties, an adaptive back-stepping control scheme with fuzzy neural networks(FNNs) is proposed. The effectiveness of the adaptive back-stepping control(ABSC) system with FNNs was compared with those of the standard back-stepping control(BSC) system and the ABSC system through computer simulation.