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dc.contributor.authorMehne, SHH
dc.contributor.authorMirjalili, S
dc.date.accessioned2020-11-05T23:28:09Z
dc.date.available2020-11-05T23:28:09Z
dc.date.issued2020
dc.identifier.isbn9783030121266
dc.identifier.doi10.1007/978-3-030-12127-3_9
dc.identifier.urihttp://hdl.handle.net/10072/399017
dc.description.abstractA direct numerical method for optimal feedback control design of general nonlinear systems is presented in this chapter. The problem is generally infinite dimensional. In order to convert it to a finite dimensional optimization problem, a collocation type method is proposed. The collocation approach is based on approximating the control input function as a series of given base functions with unknown coefficients. Then, the optimal control problem is converted to the problem of finding a finite set of coefficients. To solve the resulting optimization problem, a new nature-inspired optimization paradigm known as Moth Flame Optimizer (MFO) is used. Validation and evaluating of accuracy of the method are performed via implementing it on some well known benchmark problems. Investigations presented in this chapter reveals the efficiency of the method and its benefits with respect to other numerical approaches. The chapter also consideres an in-depth literratur review and analysis of MFO.
dc.description.peerreviewedYes
dc.publisherSpringer International Publishing
dc.publisher.placeCham, Switzerland
dc.relation.ispartofbooktitleNature-Inspired Optimizers: Theories, Literature Reviews and Applications
dc.relation.ispartofchapter9
dc.relation.ispartofpagefrom143
dc.relation.ispartofpageto166
dc.relation.ispartofseriesStudies in Computational Intelligence
dc.subject.fieldofresearchOptimisation
dc.subject.fieldofresearchArtificial intelligence
dc.subject.fieldofresearchControl engineering, mechatronics and robotics
dc.subject.fieldofresearchMachine learning
dc.subject.fieldofresearchcode490304
dc.subject.fieldofresearchcode4602
dc.subject.fieldofresearchcode4007
dc.subject.fieldofresearchcode4611
dc.titleMoth-flame optimization algorithm: Theory, literature review, and application in optimal nonlinear feedback control design
dc.typeBook chapter
dc.type.descriptionB1 - Chapters
dcterms.bibliographicCitationMehne, SHH; Mirjalili, S, Moth-flame optimization algorithm: Theory, literature review, and application in optimal nonlinear feedback control design, Nature-Inspired Optimizers: Theories, Literature Reviews and Applications, 2020, pp. 143-166
dc.date.updated2020-11-05T23:18:52Z
gro.hasfulltextNo Full Text
gro.griffith.authorMirjalili, Seyedali


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