Distributed Nonlinear Model Predictive Control by Sequential Linearization and Accelerated Gradient Method

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creativework.keywordsConstraints, Distributed control, Interconnected systems, Nonlinear systems, Predictive control
creativework.publisherElsevier B.V.en
dc.contributor.authorGrancharova A.
dc.contributor.authorJohansen T.A.
dc.contributor.authorPetrova V.
dc.date.accessioned2024-07-10T14:27:03Z
dc.date.accessioned2024-07-10T14:48:34Z
dc.date.available2024-07-10T14:27:03Z
dc.date.available2024-07-10T14:48:34Z
dc.date.issued2016-01-01
dc.description.abstractA suboptimal approach to distributed NMPC for nonlinear interconnected systems subject to constraints is proposed. The objective is to develop a computationally efficient approach. The suggested method is based on a sequential linearization of the nonlinear system dynamics and finding a suboptimal solution of the resulting Quadratic Programming problem by using distributed iterations of the dual accelerated gradient method. The benefits of the approach are reduced complexity of the on-line computations, and simple software implementation, which makes it appropriate for embedded distributed convex NMPC. The proposed method is illustrated with simulations on the model of a quadruple-tank system.
dc.identifier.doi10.1016/j.ifacol.2016.07.408
dc.identifier.issn2405-8963
dc.identifier.scopusSCOPUS_ID:84991038713en
dc.identifier.urihttps://rlib.uctm.edu/handle/123456789/405
dc.language.isoen
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84991038713&origin=inward
dc.titleDistributed Nonlinear Model Predictive Control by Sequential Linearization and Accelerated Gradient Method
dc.typeConference Paper
oaire.citation.issue7
oaire.citation.volume49
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