Fuzzy adaptive-predictive decentralized control of discrete time interconnected systems

Tzafestas, S; Kyriannakis, E; Apostolikas, G

dc.contributor.author	Tzafestas, S	en
dc.contributor.author	Kyriannakis, E	en
dc.contributor.author	Apostolikas, G	en
dc.date.accessioned	2014-03-01T01:51:52Z
dc.date.available	2014-03-01T01:51:52Z
dc.date.issued	2002	en
dc.identifier.issn	01371223	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/26492
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0036995281&partnerID=40&md5=3af35f01db424cf71a4735cecb6a20c2	en
dc.subject.other	Computer simulation	en
dc.subject.other	Control system synthesis	en
dc.subject.other	Discrete time control systems	en
dc.subject.other	Fuzzy control	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Knowledge based systems	en
dc.subject.other	Large scale systems	en
dc.subject.other	Mathematical models	en
dc.subject.other	Membership functions	en
dc.subject.other	Predictive control systems	en
dc.subject.other	Discrete time interconnected systems	en
dc.subject.other	Fuzzy adaptive-predictive decentralized control	en
dc.subject.other	Fuzzy rule base	en
dc.subject.other	Model-based predictive control	en
dc.subject.other	Decentralized control	en
dc.title	Fuzzy adaptive-predictive decentralized control of discrete time interconnected systems	en
heal.type	journalArticle	en
heal.publicationDate	2002	en
heal.abstract	This paper proposes an approach for the design of discrete-time decentralized control systems with m-step delay sharing information pattern, employing model-based predictive control (MBPC) combined with fuzzy prediction for the interconnections among the subsystems. A state space model is used at each control station to predict the corresponding subsystem output over a long-range time period. The interaction trajectories are considered to be non-linear functions of the states of the subsystems. For all cases the interconnections and the necessary predictions for them are estimated by an appropriate adaptive fuzzy identifier based on the generation of linguistic IF-THEN rules and the on-line construction of a common fuzzy rule base. Representative computer simulation results are provided and compared for nontrivial example systems.	en
heal.journalName	Systems Science	en
dc.identifier.volume	28	en
dc.identifier.issue	1	en
dc.identifier.spage	5	en
dc.identifier.epage	24	en