FAT-based adaptive control for pneumatic servo systems with mismatched uncertainties

In this paper, a function approximation technique (FAT)-based adaptive controller is proposed for pneumatic servo systems with variable payload and uncertain disturbances. The system model is firstly described by a set of non-autonomous state equations with mismatched uncertainties. Since the uncertainties are time-varying and their variation bounds are not available, most traditional robust designs or adaptive strategies are not directly applicable. The FAT-based design is proposed here to estimate these uncertainties so that the closed-loop stability can be proved by using the Lyapunov-like theory. The problem in dealing with the mismatched uncertainties is circumvented by using the multiple-surface sliding control (MSSC) algorithm. Experimental results justify that the proposed scheme can give good performance regardless of various uncertainties.