Please use this identifier to cite or link to this item: https://doi.org/10.1109/CDC.2009.5400339
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dc.titleLinear systems with chance constraints: Constraint-admissible set and applications in predictive control
dc.contributor.authorWang, C.
dc.contributor.authorOng, C.-J.
dc.contributor.authorSim, M.
dc.date.accessioned2013-10-09T06:19:30Z
dc.date.available2013-10-09T06:19:30Z
dc.date.issued2009
dc.identifier.citationWang, C., Ong, C.-J., Sim, M. (2009). Linear systems with chance constraints: Constraint-admissible set and applications in predictive control. Proceedings of the IEEE Conference on Decision and Control : 2875-2880. ScholarBank@NUS Repository. https://doi.org/10.1109/CDC.2009.5400339
dc.identifier.isbn9781424438716
dc.identifier.issn01912216
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44239
dc.description.abstractMaximal constraint-admissible sets have been widely used in the study of linear systems with hard constraints. This paper proposes a generalization of the maximal constraint-admissible set to the case where chance or probabilistic constraints are present in a linear system. Properties of the probabilistic constraint-admissible set are discussed and it is shown that the maximal chance constraint-admissible set is not time invariant. An inner approximation to the maximal set is then proposed to ensure its invariance property. This approximate set is then applied in the design of a model predictive controller for a linear system with additive disturbances and chance constraints. Feasibility and stability of the resultant closed-loop system are discussed. ©2009 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CDC.2009.5400339
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentMECHANICAL ENGINEERING
dc.contributor.departmentDECISION SCIENCES
dc.contributor.departmentSINGAPORE-MIT ALLIANCE
dc.description.doi10.1109/CDC.2009.5400339
dc.description.sourcetitleProceedings of the IEEE Conference on Decision and Control
dc.description.page2875-2880
dc.description.codenPCDCD
dc.identifier.isiut000336893603062
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