Predictive and sliding mode cascade control for Unmanned Surface Vessels

This paper presents an optimizing sliding mode cascade control structure that determines the optimal sliding surface parameters for sliding mode control of underactuated Unmanned Surface Vessel systems. A discrete-time, nonlinear model predictive controller is used to update the parameters of the sliding mode control surfaces in order to achieve a specified performance objective such as minimum tracking error, minimum time or minimum energy. The determination of these surface parameters is subject to constraints that arise from the stability conditions imposed by the sliding mode control law and the physical limits on the system such as input saturation. Examples are presented to verify the superior performance of the cascade control structure compared with the original sliding mode control.