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dc.contributor.authorPatil, BVen
dc.contributor.authorLing, KVen
dc.contributor.authorMaciejowski, Janen
dc.date.accessioned2018-09-05T11:06:36Z
dc.date.available2018-09-05T11:06:36Z
dc.date.issued2018-01-18en
dc.identifier.isbn9781509028733en
dc.identifier.issn0743-1546
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/279143
dc.description.abstract© 2017 IEEE. In this paper, we compare the performance of Bernstein global optimization algorithm based nonlinear model predictive control (NMPC) with a power system stabilizer and linear model predictive control (MPC) for the excitation control of a single machine infinite bus power system. The control simulation studies with Bernstein algorithm based NMPC show improvement in the system damping and settling time when compared with respect to a power system stabilizer and linear MPC scheme. Further, the efficacy of the Bernstein algorithm is also compared with global optimization solver BMIBNB from YALMIP toolbox in terms of NMPC scheme and results are found to be satisfactory.
dc.description.sponsorshipNational Research Foundation, Singapore.
dc.titleOptimal nonlinear model predictive control based on Bernstein polynomial approachen
dc.typeConference Object
prism.endingPage4369
prism.publicationDate2018en
prism.publicationName2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017en
prism.startingPage4363
prism.volume2018-Januaryen
dc.identifier.doi10.17863/CAM.26523
dcterms.dateAccepted2017-07-12en
rioxxterms.versionofrecord10.1109/CDC.2017.8264303en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2018-01-18en
dc.contributor.orcidMaciejowski, Jan [0000-0001-8281-8364]
rioxxterms.typeConference Paper/Proceeding/Abstracten
pubs.funder-project-idNational Research Foundation Singapore (via Cambridge Centre for Advanced Research and Education in Singapore (CARES)) (unknown)
rioxxterms.freetoread.startdate2019-01-18


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