Robust IMMPC: An Offset-free MPC for Rejecting Unknown Disturbances

TL;DR

This paper introduces a robust offset-free Model Predictive Control scheme that effectively rejects unknown disturbances and ensures output regulation, validated on a four-tank system.

Contribution

It extends Internal Model MPC to handle general bounded disturbances not generated by the disturbance model, ensuring offset-free control.

Findings

Recursive feasibility and constraint satisfaction are guaranteed.

Convergence conditions for optimal reachable output are established.

Validated effectiveness on a four-tank system.

Abstract

Output regulation is the problem of finding a control input to asymptotically track reference trajectories and reject disturbances. This can be addressed by using the internal model principle to embed a model of the disturbance in the controller. In this work, we present a Model Predictive Control scheme to achieve offset-free control. To do so, we extend Internal Model MPC to general bounded disturbances that must not be generated by the disturbance model. We show recursive feasibility, constraint satisfaction, and provide convergence conditions for the optimal reachable output. The proposed controller is validated on a four-tank system.