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.
@article{arxiv.2211.09275,
title = {Robust adaptive model predictive control with persistent excitation conditions},
author = {Xiaonan Lu and Mark Cannon},
journal= {arXiv preprint arXiv:2211.09275},
year = {2023}
}