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dc.contributor.authorDang, Thuy Ven
dc.contributor.authorLing, KVen
dc.contributor.authorMaciejowski, Janen
dc.date.accessioned2015-05-26T13:09:23Z
dc.date.available2015-05-26T13:09:23Z
dc.date.issued2015-07-17en
dc.identifier.citationEuropean Control Conference 2015, 3446 - 3451. doi:10.1109/ECC.2015.7331067en
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/247975
dc.description.abstractWe propose an algorithm for solving quadratic programming (QP) problems with inequality and equality constraints arising from linear MPC. The proposed algorithm is based on the ‘alternating direction method of multipliers’ (ADMM), with the introduction of slack variables. In comparison with algorithms available in the literature, our proposed algorithm can handle the so-called sparse MPC formulation with general inequality constraints. Moreover, our proposed algorithm is suitable for implementation on embedded platforms where computational resources are limited. In some cases, our algorithm is division-free when certain fixed matrices are computed offline. This enables our algorithm to be implemented in fixed-point arithmetic on a FPGA. In this paper, we also propose heuristic rules to select the step size of ADMM for a good convergence rate.
dc.languageEnglishen
dc.language.isoenen
dc.publisherIEEE
dc.titleEmbedded ADMM-based QP Solver for MPC with polytopic constraintsen
dc.typeConference Object
dc.description.versionThis is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ECC.2015.7331067en
prism.endingPage3451
prism.publicationDate2015en
prism.publicationNameEuropean Control Conferenceen
prism.startingPage3446
rioxxterms.versionofrecord10.1109/ECC.2015.7331067en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2015-07-17en
dc.contributor.orcidMaciejowski, Jan [0000-0001-8281-8364]
rioxxterms.typeConference Paper/Proceeding/Abstracten


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