Modularity-based control structure selection for process networks: An extension to distributed parameter systems

Lixia Kang; Manjiri Moharir; Ali Almansoori; Prodromos Daoutidis

doi:10.23919/ACC.2017.7963107

Modularity-based control structure selection for process networks: An extension to distributed parameter systems

Lixia Kang, Manjiri Moharir, Ali Almansoori, Prodromos Daoutidis

Chemical and Petroleum Engineering

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

2 Scopus citations

Abstract

This paper deals with obtaining the optimal control configuration for process networks comprising lumped and distributed parameter systems. Equation graphs that capture structural interactions among the input and output variables of first-order hyperbolic PDE systems with different types of actuations are proposed, which are combined with equation graphs of lumped parameter systems. Using these equation graphs, parameters that quantify structural coupling (relative degrees, characteristic indices) are calculated, on the basis of which, the optimal decentralized control configuration is identified. Agglomerative hierarchical clustering is then applied to obtain candidates for block-decentralized control configurations. A modularity maximization algorithm is used to select the optimal block-decentralized control configuration.

Original language	British English
Title of host publication	2017 American Control Conference, ACC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1145-1150
Number of pages	6
ISBN (Electronic)	9781509059928
DOIs	https://doi.org/10.23919/ACC.2017.7963107
State	Published - 29 Jun 2017
Event	2017 American Control Conference, ACC 2017 - Seattle, United States Duration: 24 May 2017 → 26 May 2017

Publication series

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

Conference

Conference	2017 American Control Conference, ACC 2017
Country/Territory	United States
City	Seattle
Period	24/05/17 → 26/05/17

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10.23919/ACC.2017.7963107

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Kang, L., Moharir, M., Almansoori, A., & Daoutidis, P. (2017). Modularity-based control structure selection for process networks: An extension to distributed parameter systems. In 2017 American Control Conference, ACC 2017 (pp. 1145-1150). Article 7963107 (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2017.7963107

@inproceedings{8fb7976603d44337afe87c69b261a45e,

title = "Modularity-based control structure selection for process networks: An extension to distributed parameter systems",

abstract = "This paper deals with obtaining the optimal control configuration for process networks comprising lumped and distributed parameter systems. Equation graphs that capture structural interactions among the input and output variables of first-order hyperbolic PDE systems with different types of actuations are proposed, which are combined with equation graphs of lumped parameter systems. Using these equation graphs, parameters that quantify structural coupling (relative degrees, characteristic indices) are calculated, on the basis of which, the optimal decentralized control configuration is identified. Agglomerative hierarchical clustering is then applied to obtain candidates for block-decentralized control configurations. A modularity maximization algorithm is used to select the optimal block-decentralized control configuration.",

author = "Lixia Kang and Manjiri Moharir and Ali Almansoori and Prodromos Daoutidis",

note = "Publisher Copyright: {\textcopyright} 2017 American Automatic Control Council (AACC).; 2017 American Control Conference, ACC 2017 ; Conference date: 24-05-2017 Through 26-05-2017",

year = "2017",

month = jun,

day = "29",

doi = "10.23919/ACC.2017.7963107",

language = "British English",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1145--1150",

booktitle = "2017 American Control Conference, ACC 2017",

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}

Kang, L, Moharir, M, Almansoori, A & Daoutidis, P 2017, Modularity-based control structure selection for process networks: An extension to distributed parameter systems. in 2017 American Control Conference, ACC 2017., 7963107, Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers Inc., pp. 1145-1150, 2017 American Control Conference, ACC 2017, Seattle, United States, 24/05/17. https://doi.org/10.23919/ACC.2017.7963107

Modularity-based control structure selection for process networks: An extension to distributed parameter systems. / Kang, Lixia; Moharir, Manjiri; Almansoori, Ali et al.
2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1145-1150 7963107 (Proceedings of the American Control Conference).

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

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AU - Almansoori, Ali

AU - Daoutidis, Prodromos

PY - 2017/6/29

Y1 - 2017/6/29

N2 - This paper deals with obtaining the optimal control configuration for process networks comprising lumped and distributed parameter systems. Equation graphs that capture structural interactions among the input and output variables of first-order hyperbolic PDE systems with different types of actuations are proposed, which are combined with equation graphs of lumped parameter systems. Using these equation graphs, parameters that quantify structural coupling (relative degrees, characteristic indices) are calculated, on the basis of which, the optimal decentralized control configuration is identified. Agglomerative hierarchical clustering is then applied to obtain candidates for block-decentralized control configurations. A modularity maximization algorithm is used to select the optimal block-decentralized control configuration.

AB - This paper deals with obtaining the optimal control configuration for process networks comprising lumped and distributed parameter systems. Equation graphs that capture structural interactions among the input and output variables of first-order hyperbolic PDE systems with different types of actuations are proposed, which are combined with equation graphs of lumped parameter systems. Using these equation graphs, parameters that quantify structural coupling (relative degrees, characteristic indices) are calculated, on the basis of which, the optimal decentralized control configuration is identified. Agglomerative hierarchical clustering is then applied to obtain candidates for block-decentralized control configurations. A modularity maximization algorithm is used to select the optimal block-decentralized control configuration.

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M3 - Conference contribution

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SP - 1145

EP - 1150

BT - 2017 American Control Conference, ACC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 24 May 2017 through 26 May 2017

ER -

Kang L, Moharir M, Almansoori A, Daoutidis P. Modularity-based control structure selection for process networks: An extension to distributed parameter systems. In 2017 American Control Conference, ACC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1145-1150. 7963107. (Proceedings of the American Control Conference). doi: 10.23919/ACC.2017.7963107

Modularity-based control structure selection for process networks: An extension to distributed parameter systems

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