Robust Output Feedback MPC for Constrained Linear Systems Based on Zonotopic Kalman Filter

This paper presents a robust output feedback model predictive control (MPC) method integrating a zonotopic Kalman filter (ZKF) for constrained linear systems under disturbances. Firstly, A ZKF is used to increase estimation accuracy and its optimal gain is obtained via solving a discrete-time algebraic Riccati equation. Secondly, a robust output MPC strategy is proposed, where an efficient constraint-handling strategy utilizing zonotope properties to replace linear programming (LP) with matrix operations, significantly reducing computational load. The approach ensures recursive feasibility and exponential stability while maintaining computational tractability. Finally, two simulation examples demonstrate the effectiveness and superiority of the proposed method.