Beyond Inherent Robustness: Strong Stability of MPC Despite Plant-Model Mismatch

In this article, we establish the asymptotic stability of MPC under plant-model mismatch for problems where the origin remains a steady state despite mismatch. This class of problems includes, but is not limited to, inventory management, path-planning, and control of systems in deviation variables. Our results differ from prior results on the inherent robustness of MPC, which guarantee only convergence to a neighborhood of the origin, the size of which scales with the magnitude of the mismatch. For MPC with quadratic costs, continuous differentiability of the system dynamics is sufficient to demonstrate exponential stability of the closed-loop system despite mismatch. For MPC with general costs, a joint comparison function bound and scaling condition guarantee asymptotic stability despite mismatch. The results are illustrated in numerical simulations, including the classic upright pendulum problem. The tools developed to establish these results can address the stability of offset-free MPC, an open and interesting question in the MPC research literature.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-09-01
DOI
https://doi.org/10.1109/tac.2025.3604662
Citations
2
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
2.43
Controls
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article

Beyond Inherent Robustness: Strong Stability of MPC Despite Plant-Model Mismatch

Steven J. Kuntz, James B. Rawlings
2 citations
IEEE Transactions on Automatic Control
Advanced Control Systems Optimization
2.43
article

Beyond Inherent Robustness: Strong Stability of MPC Despite Plant-Model Mismatch

Steven J. Kuntz, James B. Rawlings
article en
2 citations

Abstract

In this article, we establish the asymptotic stability of MPC under plant-model mismatch for problems where the origin remains a steady state despite mismatch. This class of problems includes, but is not limited to, inventory management, path-planning, and control of systems in deviation variables. Our results differ from prior results on the inherent robustness of MPC, which guarantee only convergence to a neighborhood of the origin, the size of which scales with the magnitude of the mismatch. For MPC with quadratic costs, continuous differentiability of the system dynamics is sufficient to demonstrate exponential stability of the closed-loop system despite mismatch. For MPC with general costs, a joint comparison function bound and scaling condition guarantee asymptotic stability despite mismatch. The results are illustrated in numerical simulations, including the classic upright pendulum problem. The tools developed to establish these results can address the stability of offset-free MPC, an open and interesting question in the MPC research literature.

IEEE Transactions on Automatic ControlVol. 71(2)
University of California, Santa Barbara (US)
Openalex Percentile: Top 10%
Advanced Control Systems Optimization
2.43
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