Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions

Davood Babaei Pourkargar; Antonios Armaou

doi:10.1109/ACC.2015.7171129

Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions

Davood Babaei Pourkargar, Antonios Armaou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We focus on adaptive wave motion suppression of fluid flows in the presence of unknown parameters. The suppression problem is addressed by low-dimensional adaptive nonlinear output feedback controller synthesis. We employed adaptive proper orthogonal decomposition to recursively compute the set of empirical basis functions needed by the Galerkin projection to derive updated reduced order models that can be used as the basis for Lyapunov-based adaptive output feedback controller design. A static observer is applied to estimate the state modes of the system required by the adaptive controller. The effectiveness of the proposed adaptive wave motion suppression method is illustrated on a generalized form of the Korteweg-de Vries-Burgers (KdVB) equation which can adequately describe the wave motions in a wide range of fluid flow processes.

Original language	English (US)
Title of host publication	ACC 2015 - 2015 American Control Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2619-2624
Number of pages	6
ISBN (Electronic)	9781479986842
DOIs	https://doi.org/10.1109/ACC.2015.7171129
State	Published - Jul 28 2015
Event	2015 American Control Conference, ACC 2015 - Chicago, United States Duration: Jul 1 2015 → Jul 3 2015

Publication series

Name	Proceedings of the American Control Conference
Volume	2015-July
ISSN (Print)	0743-1619

Other

Other	2015 American Control Conference, ACC 2015
Country/Territory	United States
City	Chicago
Period	7/1/15 → 7/3/15

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/ACC.2015.7171129

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Pourkargar, D. B., & Armaou, A. (2015). Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions. In ACC 2015 - 2015 American Control Conference (pp. 2619-2624). Article 7171129 (Proceedings of the American Control Conference; Vol. 2015-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2015.7171129

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title = "Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions",

abstract = "We focus on adaptive wave motion suppression of fluid flows in the presence of unknown parameters. The suppression problem is addressed by low-dimensional adaptive nonlinear output feedback controller synthesis. We employed adaptive proper orthogonal decomposition to recursively compute the set of empirical basis functions needed by the Galerkin projection to derive updated reduced order models that can be used as the basis for Lyapunov-based adaptive output feedback controller design. A static observer is applied to estimate the state modes of the system required by the adaptive controller. The effectiveness of the proposed adaptive wave motion suppression method is illustrated on a generalized form of the Korteweg-de Vries-Burgers (KdVB) equation which can adequately describe the wave motions in a wide range of fluid flow processes.",

author = "Pourkargar, {Davood Babaei} and Antonios Armaou",

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year = "2015",

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doi = "10.1109/ACC.2015.7171129",

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Pourkargar, DB & Armaou, A 2015, Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions. in ACC 2015 - 2015 American Control Conference., 7171129, Proceedings of the American Control Conference, vol. 2015-July, Institute of Electrical and Electronics Engineers Inc., pp. 2619-2624, 2015 American Control Conference, ACC 2015, Chicago, United States, 7/1/15. https://doi.org/10.1109/ACC.2015.7171129

Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions. / Pourkargar, Davood Babaei; Armaou, Antonios.
ACC 2015 - 2015 American Control Conference. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2619-2624 7171129 (Proceedings of the American Control Conference; Vol. 2015-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - We focus on adaptive wave motion suppression of fluid flows in the presence of unknown parameters. The suppression problem is addressed by low-dimensional adaptive nonlinear output feedback controller synthesis. We employed adaptive proper orthogonal decomposition to recursively compute the set of empirical basis functions needed by the Galerkin projection to derive updated reduced order models that can be used as the basis for Lyapunov-based adaptive output feedback controller design. A static observer is applied to estimate the state modes of the system required by the adaptive controller. The effectiveness of the proposed adaptive wave motion suppression method is illustrated on a generalized form of the Korteweg-de Vries-Burgers (KdVB) equation which can adequately describe the wave motions in a wide range of fluid flow processes.

AB - We focus on adaptive wave motion suppression of fluid flows in the presence of unknown parameters. The suppression problem is addressed by low-dimensional adaptive nonlinear output feedback controller synthesis. We employed adaptive proper orthogonal decomposition to recursively compute the set of empirical basis functions needed by the Galerkin projection to derive updated reduced order models that can be used as the basis for Lyapunov-based adaptive output feedback controller design. A static observer is applied to estimate the state modes of the system required by the adaptive controller. The effectiveness of the proposed adaptive wave motion suppression method is illustrated on a generalized form of the Korteweg-de Vries-Burgers (KdVB) equation which can adequately describe the wave motions in a wide range of fluid flow processes.

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Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions

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