An Improved Output Feedback MPC scheme for Constrained Linear Systems

Abstract We propose an output feedback model predictive control (MPC) scheme that is independent of the estimation method employed. The proposed approach is non-conservative by design as the feedback information subject to estimation errors is explicitly considered in the predictions. The proposed scheme is robust to both the plant-model mismatch and the estimation error and avoids the unnecessary conservatism introduced by other existing output feedback MPC approaches in the literature. We achieve this by making use of all the available information at every time-step and formulate a control policy with the assumption that bounds for the estimation error are available at all times. We show that the proposed scheme is recursively feasible and demonstrate its advantages using a double-integrator example.