Discrete methods for optimal control problems

Chryssoverghi, I

dc.contributor.author	Chryssoverghi, I	en
dc.date.accessioned	2014-03-01T01:18:53Z
dc.date.available	2014-03-01T01:18:53Z
dc.date.issued	2003	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15244
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-35248826475&partnerID=40&md5=329323670ad6e08acfa156e2898e0863	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	APPROXIMATION	en
dc.title	Discrete methods for optimal control problems	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	We consider a constrained optimal control problem, which we formulate in classical and in relaxed form. In order to approximate this problem numerically, we apply various discretization schemes on either of these two forms and study the behavior in the limit of discrete optimality and necessary conditions for optimality. We then propose discrete mixed gradient penalty methods that use classical or relaxed discrete controls and progressively refine the discretization, thus reducing computing time and memory. In addition, when the discrete adjoint state is not defined or difficult to calculate, we propose discrete methods that use approximate adjoints and derivatives. The result is that in relaxed methods accumulation points of generated sequences satisfy continuous strong relaxed optimality conditions, while in classical methods they satisfy weak optimality conditions. © Springer-Verlag Berlin Heidelberg 2003.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.isi	ISI:000182433500022	en
dc.identifier.volume	2542	en
dc.identifier.spage	205	en
dc.identifier.epage	212	en