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 Engineering and Materials Science

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

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	English (US)
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 - Jun 29 2017
Event	2017 American Control Conference, ACC 2017 - Seattle, United States Duration: May 24 2017 → May 26 2017

Publication series

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

Other

Other	2017 American Control Conference, ACC 2017
Country/Territory	United States
City	Seattle
Period	5/24/17 → 5/26/17

Bibliographical note

Publisher Copyright:
© 2017 American Automatic Control Council (AACC).

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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

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

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, 5/24/17. https://doi.org/10.23919/ACC.2017.7963107

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

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

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