Adaptive robust predictive control with sample-based persistent excitation

Xiaonan Lu; Mark Cannon

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arXiv · 2211.12478

Adaptive robust predictive control with sample-based persistent excitation

Xiaonan Lu·Mark Cannon

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Abstract

We propose a robust adaptive Model Predictive Control (MPC) strategy with online set-based estimation for constrained linear systems with unknown parameters and bounded disturbances. A sample-based test applied to predicted trajectories is used to ensure convergence of parameter estimates by enforcing a persistence of excitation condition on the closed loop system. The control law robustly satisfies constraints and has guarantees of feasibility and input-to-state stability. Convergence of parameter set estimates to the actual system parameter vector is guaranteed under conditions on reachability and tightness of disturbance bounds.

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BibTeX RIS

Xiaonan Lu, Mark Cannon. 2022-11-22. Adaptive robust predictive control with sample-based persistent excitation. https://arxiv.org/abs/2211.12478

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