Robust receding horizon control for linear systems with state and input dependent disturbances

A robust model predictive controller is proposed for constrained linear systems with unknown disturbances that are subject to state and input dependent piecewise affine bounds. The formulation encompasses problems involving model uncertainty arising from unknown system parameters and linearisation errors. We propose a computationally efficient method for the online optimization of a receding horizon min-max cost over the class of feedback strategies subject robust constraint satisfaction and provide an illustrative numerical example.