Explicit LPV-MPC with bounded rate of parameter variation

Abstract

Recently it was shown how one can reformulate the MPC problem for LPV systems to a series of mpLPs by a closed-loop minimax MPC algorithm based on dynamic programming. A relaxation technique is employed to reformulate constraints which are polynomial in the scheduling parameters to parameter-independent constraints. The algorithm allows the computation of explicit control laws for LPV systems and enables the controller to exploit information about the scheduling parameter. This improves the control performance compared to a standard robust approach where no uncertainty knowledge is used, while keeping the benefits of fast online computations. In this paper the explicit LPV-MPC scheme is extended to incorporate limits on the rate of parameter variation in the controller design. Taking these limits into account can further improve control performance since impossible trajectories of the scheduling parameter do not have to be considered during control law computations.