Data-Driven Predictive Control with Adaptive Disturbance Attenuation for Constrained Systems

Nan Li; Ilya Kolmanovsky; Hong Chen

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arXiv · 2403.14935

Data-Driven Predictive Control with Adaptive Disturbance Attenuation for Constrained Systems

Nan Li·Ilya Kolmanovsky·Hong Chen

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Abstract

In this paper, we propose a novel data-driven predictive control approach for systems subject to time-domain constraints. The approach combines the strengths of H-infinity control for rejecting disturbances and MPC for handling constraints. In particular, the approach can dynamically adapt H-infinity disturbance attenuation performance depending on measured system state and forecasted disturbance level to satisfy constraints. We establish theoretical properties of the approach including robust guarantees of closed-loop stability, disturbance attenuation, constraint satisfaction under noisy data, as well as sufficient conditions for recursive feasibility, and illustrate the approach with a numerical example.

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BibTeX RIS

Nan Li, Ilya Kolmanovsky, Hong Chen. 2024-03-22. Data-Driven Predictive Control with Adaptive Disturbance Attenuation for Constrained Systems. https://arxiv.org/abs/2403.14935

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