A novel tube-based output feedback MPC for constrained linear systems

Abstract

Model Predictive Control (MPC) is an advanced strategy for the control of multi-variable and constrained dynamical systems. Tube-based MPC is a robust control technique that handles uncertainties present in the model. Since full state information is seldom available in practical systems, the estimation error must also be taken into account in addition to model uncertainties to achieve closed-loop stability and constraint satisfaction despite estimation and model errors. In this paper, we propose a novel strategy for the design of a tube-based output feedback MPC which is independent of the estimation method employed. We formulate a control policy by choosing a candidate estimate that is consistent with the reachable sets of the system under control. The proposed method can be combined with any estimation scheme as long as the assumed error bounds are satisfied. We show that the proposed method is recursively feasible, robustly exponentially stable, and performs better than other available strategies.