Decentralised model predictive control with asymptotically positive realness

Tuan, HD; Savkin, A; Nguyen, NT; Nguyen, HT

Decentralised model predictive control with asymptotically positive realness

Tuan, HD

Savkin, A Nguyen, NT

Nguyen, HT

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Control and Automation, ICCA, 2013, pp. 822 - 827
Issue Date:: 2013-08-26

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Field	Value	Language
dc.contributor.author	Tuan, HD https://orcid.org/0000-0003-0292-6061	en_US
dc.contributor.author	Savkin, A	en_US
dc.contributor.author	Nguyen, NT https://orcid.org/0000-0002-9958-9876	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.date.issued	2013-08-26	en_US
dc.identifier.citation	IEEE International Conference on Control and Automation, ICCA, 2013, pp. 822 - 827	en_US
dc.identifier.isbn	9781467347075	en_US
dc.identifier.issn	1948-3449	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28044
dc.description.abstract	This paper presents a novel distributed model predictive control strategy for a large-scale system consisting of interconnected subsystems. A constructive method of online stabilisation that is applicable to the model predictive controllers (MPC) is developed to facilitate the control strategy. The system stability is achievable by the newly introduced asymptotically positive realness constraint (APRC) for MPC. Simulations are provided to demonstrate the efficacy of the presented stability constraint. © 2013 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Control and Automation, ICCA	en_US
dc.relation.isbasedon	10.1109/ICCA.2013.6565006	en_US
dc.title	Decentralised model predictive control with asymptotically positive realness	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	Hangzhou, China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper presents a novel distributed model predictive control strategy for a large-scale system consisting of interconnected subsystems. A constructive method of online stabilisation that is applicable to the model predictive controllers (MPC) is developed to facilitate the control strategy. The system stability is achievable by the newly introduced asymptotically positive realness constraint (APRC) for MPC. Simulations are provided to demonstrate the efficacy of the presented stability constraint. © 2013 IEEE.

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http://hdl.handle.net/10453/28044