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Discrete-Time Sliding Mode Energy Control of sine-Gordon Chain with Adaptive Augmentation∗. / Andrievsky, Boris; Orlov, Yury.

In: IFAC-PapersOnLine, Vol. 55, No. 12, 2022, p. 717-722.

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Andrievsky, Boris ; Orlov, Yury. / Discrete-Time Sliding Mode Energy Control of sine-Gordon Chain with Adaptive Augmentation∗. In: IFAC-PapersOnLine. 2022 ; Vol. 55, No. 12. pp. 717-722.

BibTeX

@article{118d79181dd64bcc8dbedaf5228cb5fa,
title = "Discrete-Time Sliding Mode Energy Control of sine-Gordon Chain with Adaptive Augmentation∗",
abstract = "The present paper focuses on the robustness issues of the speed-gradient energy control design for the one-dimensional sine-Gordon system. The energy stabilization of a non-zero level is addressed as the energy reference tracking problem. In the paper, the {"}relay{"} speed gradient algorithm, using state feedback with in-domain actuators, is designed and its adaptive augmentation is proposed. The properties of the closed-loop energy feedback for sampling-in-time control algorithms are studied numerically. In the PDE setting, such an adaptive adjustment of the sliding mode control gain has not been investigated so far. This modification is demonstrated to ensure the closed-loop system robustness with respect to the time sampling.",
keywords = "adaptation, energy control, sampling-it-time control, sine-Gordon equation, speed-gradient",
author = "Boris Andrievsky and Yury Orlov",
note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.. All rights reserved.; 14th IFAC Workshop on Adaptive and Learning Control Systems, ALCOS 2022 ; Conference date: 29-06-2022 Through 01-07-2022",
year = "2022",
doi = "10.1016/j.ifacol.2022.07.397",
language = "English",
volume = "55",
pages = "717--722",
journal = "IFAC-PapersOnLine",
issn = "2405-8971",
publisher = "Elsevier",
number = "12",

}

RIS

TY - JOUR

T1 - Discrete-Time Sliding Mode Energy Control of sine-Gordon Chain with Adaptive Augmentation∗

AU - Andrievsky, Boris

AU - Orlov, Yury

N1 - Publisher Copyright: © 2022 Elsevier B.V.. All rights reserved.

PY - 2022

Y1 - 2022

N2 - The present paper focuses on the robustness issues of the speed-gradient energy control design for the one-dimensional sine-Gordon system. The energy stabilization of a non-zero level is addressed as the energy reference tracking problem. In the paper, the "relay" speed gradient algorithm, using state feedback with in-domain actuators, is designed and its adaptive augmentation is proposed. The properties of the closed-loop energy feedback for sampling-in-time control algorithms are studied numerically. In the PDE setting, such an adaptive adjustment of the sliding mode control gain has not been investigated so far. This modification is demonstrated to ensure the closed-loop system robustness with respect to the time sampling.

AB - The present paper focuses on the robustness issues of the speed-gradient energy control design for the one-dimensional sine-Gordon system. The energy stabilization of a non-zero level is addressed as the energy reference tracking problem. In the paper, the "relay" speed gradient algorithm, using state feedback with in-domain actuators, is designed and its adaptive augmentation is proposed. The properties of the closed-loop energy feedback for sampling-in-time control algorithms are studied numerically. In the PDE setting, such an adaptive adjustment of the sliding mode control gain has not been investigated so far. This modification is demonstrated to ensure the closed-loop system robustness with respect to the time sampling.

KW - adaptation

KW - energy control

KW - sampling-it-time control

KW - sine-Gordon equation

KW - speed-gradient

UR - http://www.scopus.com/inward/record.url?scp=85137169083&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2022.07.397

DO - 10.1016/j.ifacol.2022.07.397

M3 - Conference article

AN - SCOPUS:85137169083

VL - 55

SP - 717

EP - 722

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8971

IS - 12

T2 - 14th IFAC Workshop on Adaptive and Learning Control Systems, ALCOS 2022

Y2 - 29 June 2022 through 1 July 2022

ER -

ID: 99633340