Robust Funnel Model Predictive Control for output tracking with prescribed performance

TL;DR

This paper introduces a robust funnel Model Predictive Control scheme that ensures output tracking within prescribed bounds for nonlinear MIMO systems, even with disturbances and model mismatches, validated through simulations.

Contribution

It combines funnel MPC with adaptive control to guarantee recursive feasibility and robustness without terminal conditions or fixed prediction horizons.

Findings

Guarantees output tracking within prescribed bounds

Ensures recursive feasibility without terminal conditions

Validated effectiveness through simulations

Abstract

We propose a novel robust Model Predictive Control (MPC) scheme for nonlinear multi-input multi-output systems of relative degree one with stable internal dynamics. The proposed algorithm is a combination of funnel MPC, i.e., MPC with a particular stage cost, and the model-free adaptive funnel controller. The new robust funnel MPC scheme guarantees output tracking of reference signals within prescribed performance bounds -- even in the presence of unknown disturbances and a structural model-plant mismatch. We show initial and recursive feasibility of the proposed control scheme without imposing terminal conditions or any requirements on the prediction horizon. Moreover, we allow for model updates at runtime. To this end, we propose a proper initialization strategy, which ensures that recursive feasibility is preserved. Finally, we validate the performance of the proposed robust MPC scheme by simulations.