Robust adaptive model predictive control with persistent excitation conditions

Xiaonan Lu; Mark Cannon

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arXiv · 2211.09275

Robust adaptive model predictive control with persistent excitation conditions

Xiaonan Lu·Mark Cannon

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Abstract

For constrained linear systems with bounded disturbances and parametric uncertainty, we propose a robust adaptive model predictive control strategy with online parameter estimation. Constraints enforcing persistently exciting closed loop control actions are introduced for a set-membership parameter identification scheme. The algorithm requires the online solution of a convex program, satisfies constraints robustly, and ensures recursive feasibility and input-to-state stability. Almost sure convergence to the actual system parameters is demonstrated under assumptions on stabilizability, reachability, and tight disturbance bounds.

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Xiaonan Lu, Mark Cannon. 2022-11-17. Robust adaptive model predictive control with persistent excitation conditions. https://arxiv.org/abs/2211.09275

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