Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Bartos, Marcell, Köhler, Johannes, Dörfler, Florian, Zeilinger, Melanie N.
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866914474810671104
author Bartos, Marcell
Köhler, Johannes
Dörfler, Florian
Zeilinger, Melanie N.
author_facet Bartos, Marcell
Köhler, Johannes
Dörfler, Florian
Zeilinger, Melanie N.
contents Standard model-based control design deteriorates when the system dynamics change during operation. To overcome this challenge, online and adaptive methods have been proposed in the literature. In this work, we consider the class of discrete-time linear systems with unknown time-varying parameters. We propose a simple, modular, and computationally tractable approach by combining two classical and well-known building blocks from estimation and control: the least mean square filter and the certainty-equivalent linear quadratic regulator. Despite both building blocks being simple and off-the-shelf, our analysis shows that they can be seamlessly combined to a powerful pipeline with stability guarantees. Namely, finite-gain $\ell^2$-stability of the closed-loop interconnection of the unknown system, the parameter estimator, and the controller is proven, despite the presence of unknown disturbances and time-varying parametric uncertainties. Real-world applicability of the proposed algorithm is showcased by simulations carried out on a nonlinear planar quadrotor.
format Preprint
id arxiv_https___arxiv_org_abs_2511_08236
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters
Bartos, Marcell
Köhler, Johannes
Dörfler, Florian
Zeilinger, Melanie N.
Systems and Control
Optimization and Control
Standard model-based control design deteriorates when the system dynamics change during operation. To overcome this challenge, online and adaptive methods have been proposed in the literature. In this work, we consider the class of discrete-time linear systems with unknown time-varying parameters. We propose a simple, modular, and computationally tractable approach by combining two classical and well-known building blocks from estimation and control: the least mean square filter and the certainty-equivalent linear quadratic regulator. Despite both building blocks being simple and off-the-shelf, our analysis shows that they can be seamlessly combined to a powerful pipeline with stability guarantees. Namely, finite-gain $\ell^2$-stability of the closed-loop interconnection of the unknown system, the parameter estimator, and the controller is proven, despite the presence of unknown disturbances and time-varying parametric uncertainties. Real-world applicability of the proposed algorithm is showcased by simulations carried out on a nonlinear planar quadrotor.
title Stability of Certainty-Equivalent Adaptive LQR for Linear Systems with Unknown Time-Varying Parameters
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2511.08236