Publication:
An offline formulation of MPC for LPV systems using linear matrix inequalities

dc.contributor.authorP. Bumroongsrien_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-11-09T02:30:47Z
dc.date.available2018-11-09T02:30:47Z
dc.date.issued2014-01-01en_US
dc.description.abstractAn offline model predictive control (MPC) algorithm for linear parameter varying (LPV) systems is presented. The main contribution is to develop an offline MPC algorithm for LPV systems that can deal with both time-varying scheduling parameter and persistent disturbance. The norm-bounding technique is used to derive an offline MPC algorithm based on the parameter-dependent state feedback control law and the parameter-dependent Lyapunov functions. The online computational time is reduced by solving offline the linear matrix inequality (LMI) optimization problems to find the sequences of explicit state feedback control laws. At each sampling instant, a parameter-dependent state feedback control law is computed by linear interpolation between the precomputed state feedback control laws. The algorithm is illustrated with two examples. The results show that robust stability can be ensured in the presence of both time-varying scheduling parameter and persistent disturbance. © 2014 P. Bumroongsri.en_US
dc.identifier.citationJournal of Applied Mathematics. Vol.2014, (2014)en_US
dc.identifier.doi10.1155/2014/786351en_US
dc.identifier.issn16870042en_US
dc.identifier.issn1110757Xen_US
dc.identifier.other2-s2.0-84900993079en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/34131
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84900993079&origin=inwarden_US
dc.subjectMathematicsen_US
dc.titleAn offline formulation of MPC for LPV systems using linear matrix inequalitiesen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84900993079&origin=inwarden_US

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