Robust Model Predictive Control with Polytopic Model Uncertainty through System Level Synthesis

Understand

We propose a robust model predictive control (MPC) method for discrete-time linear systems with polytopic model uncertainty and additive disturbances.

• Optimizing over linear time-varying (LTV) state feedback controllers has been successfully used for robust MPC when only additive disturbances are present.
• However, it is challenging to design LTV state feedback controllers in the face of model uncertainty whose effects are difficult to bound.
• To address this issue, we propose a novel approach to over-approximate the effects of both model uncertainty and additive disturbances by a filtered additive disturbance signal.