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Study of the stability of multidimensional systems using genetic algorithms

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dc.contributor.author Mastorakis, NE en
dc.contributor.author Gonos, IF en
dc.date.accessioned 2014-03-01T01:48:47Z
dc.date.available 2014-03-01T01:48:47Z
dc.date.issued 1999 en
dc.identifier.uri http://hdl.handle.net/123456789/25593
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-4944221801&partnerID=40&md5=1d2a7f678fbe09d4734dffafec8231ff en
dc.subject.other Constraint theory en
dc.subject.other Functions en
dc.subject.other Genetic algorithms en
dc.subject.other Mathematical models en
dc.subject.other Polynomials en
dc.subject.other Problem solving en
dc.subject.other Theorem proving en
dc.subject.other Discrete variables en
dc.subject.other Multidimensional systems en
dc.subject.other Schur stability en
dc.subject.other System stability en
dc.title Study of the stability of multidimensional systems using genetic algorithms en
heal.type journalArticle en
heal.publicationDate 1999 en
heal.abstract The study of the Stability of m-dimensional systems is a difficult problem especially when m≥3. There exist only a few results and, unfortunately, there does not exist any practical criterion. In this brief, the stability of an m-dimensional system is dealt as a minimization problem of the absolute value of its characteristic polynomial over the boundaries of its variables (i.e. on the m unit circles). In this minimization, we seek for a global minimum. It is known that all the numerical algorithms and all the artificial neural networks' techniques can not guarantee the convergence to the total (global) minimum. On the contrary, genetic algorithms provide us the advantage of the convergence to the global minimum without the requirement of the differentiability nor of the objective function neither of the constraints. So, the problem of the stability of an m-D (multidimensional) system is reduced to a minimization problem of the absolute value of its characteristic polynomial over the boundaries of its variables which is solved via an appropriate genetic algorithm (GA). Numerical examples are presented. en
heal.publisher World Scientific and Engineering Academy and Society en
heal.journalName Computational Intelligence and Applications en
dc.identifier.spage 29 en
dc.identifier.epage 36 en


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