Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2010.2041994
DC FieldValue
dc.titleModel predictive control using segregated disturbance feedback
dc.contributor.authorWang, C.
dc.contributor.authorOng, C.-J.
dc.contributor.authorSim, M.
dc.date.accessioned2013-10-09T06:19:05Z
dc.date.available2013-10-09T06:19:05Z
dc.date.issued2010
dc.identifier.citationWang, C., Ong, C.-J., Sim, M. (2010). Model predictive control using segregated disturbance feedback. IEEE Transactions on Automatic Control 55 (4) : 831-840. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2010.2041994
dc.identifier.issn00189286
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44223
dc.description.abstractThis paper proposes a new control parametrization under the model predictive control (MPC) framework for constrained linear discrete-time systems with bounded disturbances. The proposed parametrization takes the form of a special piecewise affine disturbance feedback in an effort to reduce conservatism. It is a generalization of linear disturbance feedback parametrization, introduced in the recent literature. Numerical computations and stability properties of the resulting MPC problem using the proposed parametrization are discussed. When the disturbance set and the problem data satisfy mild assumptions, the associated finite-horizon optimization can be computed efficiently and exactly. The advantage of the proposed parametrization over linear disturbance feedback is illustrated via numerical examples. © 2006 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TAC.2010.2041994
dc.sourceScopus
dc.subjectModel predictive control (MPC)
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.contributor.departmentDECISION SCIENCES
dc.contributor.departmentSINGAPORE-MIT ALLIANCE
dc.description.doi10.1109/TAC.2010.2041994
dc.description.sourcetitleIEEE Transactions on Automatic Control
dc.description.volume55
dc.description.issue4
dc.description.page831-840
dc.description.codenIETAA
dc.identifier.isiut000276251300002
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