Operator-valued Kernels and Control of Infinite dimensional Dynamic Systems

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publication2022 IEEE 61st Conference on Decision and Control (CDC)
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages1039-1044
ISBN (electronic)9781665467612, 978-1-6654-6760-5
ISBN (print)978-1-6654-6762-9
Publication statusPublished - Dec 2022

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (electronic)2576-2370

Conference

Title61st IEEE Conference on Decision and Control (CDC 2022)
PlaceMexico
CityCancún
Period6 - 9 December 2022

Abstract

The Linear Quadratic Regulator (LQR), which is arguably the most classical problem in control theory, was recently related to kernel methods in [1] for finite dimensional systems. We show that this result extends to infinite dimensional systems, i.e. control of linear partial differential equations. The quadratic objective paired with the linear dynamics encode the relevant kernel, defining a Hilbert space of controlled trajectories, for which we obtain a concise formula based on the solution of the differential Riccati equation. This paves the way to applying representer theorems from kernel methods to solve infinite dimensional optimal control problems. © 2022 IEEE.

Citation Format(s)

Operator-valued Kernels and Control of Infinite dimensional Dynamic Systems. / Aubin-Frankowski, Pierre-Cyril; Bensoussan, Alain.
2022 IEEE 61st Conference on Decision and Control (CDC). Institute of Electrical and Electronics Engineers, Inc., 2022. p. 1039-1044 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review