Quadratic MPC with ℓ<inf>0</inf>-input constraint

Aguilera, RP; Delgado, R; Dolz, D; Agüero, JC

Quadratic MPC with ℓ<inf>0</inf>-input constraint

Aguilera, RP

Delgado, R Dolz, D Agüero, JC

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Publication Type:: Conference Proceeding
Citation:: IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, 19 pp. 10888 - 10893
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Aguilera, RP https://orcid.org/0000-0003-4166-8341	en_US
dc.contributor.author	Delgado, R	en_US
dc.contributor.author	Dolz, D	en_US
dc.contributor.author	Agüero, JC	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, 19 pp. 10888 - 10893	en_US
dc.identifier.isbn	9783902823625	en_US
dc.identifier.issn	1474-6670	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121415
dc.description.abstract	© IFAC. In this paper we propose a novel quadratic model predictive control technique that constrains the number of active inputs at each control horizon instant. This problem is known as sparse control. We use an iterative convex optimization procedure to solve the corresponding optimization problem subject to sparsity constraints defined by means of the ℓ0-norm. We also derive a sufficient condition on the minimum number of active of inputs that guarantees the exponential stability of the closed-loop system. A simulation example illustrates the benefits of the control design method proposed in the paper.	en_US
dc.relation.ispartof	IFAC Proceedings Volumes (IFAC-PapersOnline)	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Quadratic MPC with ℓ<inf>0</inf>-input constraint	en_US
dc.type	Conference Proceeding
utslib.citation.volume	19	en_US
utslib.for	0906 Electrical and Electronic Engineering	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
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	19	en_US

Abstract:

© IFAC. In this paper we propose a novel quadratic model predictive control technique that constrains the number of active inputs at each control horizon instant. This problem is known as sparse control. We use an iterative convex optimization procedure to solve the corresponding optimization problem subject to sparsity constraints defined by means of the ℓ0-norm. We also derive a sufficient condition on the minimum number of active of inputs that guarantees the exponential stability of the closed-loop system. A simulation example illustrates the benefits of the control design method proposed in the paper.

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http://hdl.handle.net/10453/121415