This paper presents a data-driven algorithm to solve the problem of infinite-horizon linear quadratic regulation (LQR), for a class of discrete-time linear�...
Dec 18, 2020 � Abstract—This paper presents a data-driven algorithm to solve the problem of infinite-horizon linear quadratic regulation.
This paper presents a data-driven algorithm to solve the problem of infinite-horizon linear quadratic regulation (LQR), for a class of discrete-time linear�...
Sep 16, 2024 � This paper presents a one-shot learning approach with performance and robustness guarantees for the linear quadratic regulator.
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A model predictive control law is considered that optimizes the infinite horizon linear quadratic regulator (LQR) objective over the infinite dimensional�...
Missing: driven Approach
This letter presents a data-driven solution to the discrete-time infinite horizon linear quadratic regulator (LQR) problem. The state feedback gain is�...
The method proposed in this paper also recovers the infinite-horizon solution in a very natural way. Our approach is based on the framework developed in. De�...
Sep 16, 2024 � This paper presents a one-shot learning approach with performance and robustness guarantees for the linear quadratic regulator (LQR) control of�...
Missing: Constrained | Show results with:Constrained
Abstract—This paper is a contribution to the theory of the infinite- horizon linear quadratic regulator (LQR) problem subject to inequality constraints on the�...
Missing: driven | Show results with:driven
Sep 20, 2024 � PDF | This paper presents a one-shot learning approach with performance and robustness guarantees for the linear quadratic regulator (LQR)