Almost Surely $\sqrt{T}$ Regret for Adaptive LQR

• URL: http://arxiv.org/abs/2301.05537v4
• Date: Mon, 27 Jan 2025 17:45:44 GMT
• Title: Almost Surely $\sqrt{T}$ Regret for Adaptive LQR
• Authors: Yiwen Lu, Yilin Mo,
• Abstract summary: We propose an adaptive LQR controller with almost surely $tilde mathcalO(sqrtT)$ regret upper bound.<n>The controller features a circuit-breaking mechanism, which circumvents potential safety breach and guarantees the convergence of the parameter estimate.
• Score: 3.8499701725610285
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Linear-Quadratic Regulation (LQR) problem with unknown system parameters has been widely studied, but it has remained unclear whether $\tilde{ \mathcal{O}}(\sqrt{T})$ regret, which is the best known dependence on time, can be achieved almost surely. In this paper, we propose an adaptive LQR controller with almost surely $\tilde{ \mathcal{O}}(\sqrt{T})$ regret upper bound. The controller features a circuit-breaking mechanism, which circumvents potential safety breach and guarantees the convergence of the system parameter estimate, but is shown to be triggered only finitely often and hence has negligible effect on the asymptotic performance of the controller. The proposed controller is also validated via simulation on Tennessee Eastman Process~(TEP), a commonly used industrial process example.

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