Predictive sliding mode tracking control for a class of SISO systems

This paper aims to develop a predictive sliding mode controller (PSMC) for a class of nonlinear SISO systems. The PSMC is designed as the combination of an adaptive sliding mode controller (ASMC) and an adaptive grey predictor (AGP). The ASMC is designed to ensure robust tracking performance of a nonlinear system which is represented by advanced fuzzy sets. Meanwhile, the AGP is used to estimate impacts of system uncertainties and disturbances on the performance in order to regulate the ASMC adaptive gain to minimize the control efforts while improving the control quality. Real-time experiments are carried out to validate the effectiveness and applicability of the proposed control scheme.