Event-triggered control for discrete-time systems

Eqtami, A; Dimarogonas, DV; Kyriakopoulos, KJ

dc.contributor.author	Eqtami, A	en
dc.contributor.author	Dimarogonas, DV	en
dc.contributor.author	Kyriakopoulos, KJ	en
dc.date.accessioned	2014-03-01T02:46:47Z
dc.date.available	2014-03-01T02:46:47Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32853
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-77957806211&partnerID=40&md5=1f5d165774a158080907af70da247143	en
dc.relation.uri	http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5531089	en
dc.relation.uri	http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05531089	en
dc.subject	Continuous Time	en
dc.subject	Discrete Time System	en
dc.subject	Measurement Error	en
dc.subject	Model Predictive Control	en
dc.subject	Input To State Stable	en
dc.subject.other	Continuous monitoring	en
dc.subject.other	Continuous time	en
dc.subject.other	Control laws	en
dc.subject.other	Discrete time system	en
dc.subject.other	Event-triggered	en
dc.subject.other	Input to state stable	en
dc.subject.other	Model-predictive control approach	en
dc.subject.other	Digital control systems	en
dc.subject.other	Measurement errors	en
dc.subject.other	Model predictive control	en
dc.subject.other	Potential flow	en
dc.subject.other	Predictive control systems	en
dc.subject.other	Discrete time control systems	en
dc.title	Event-triggered control for discrete-time systems	en
heal.type	conferenceItem	en
heal.identifier.secondary	5531089	en
heal.publicationDate	2010	en
heal.abstract	In this paper, event-triggered strategies for control of discrete-time systems are proposed and analyzed. Similarly to the continuous-time case, the plant is assumed input-to-state stable with respect to measurement errors and the control law is updated once a triggering condition involving the norm of a measurement error is violated. The results are also extended to a self-triggered formulation, where the next control updates are decided at the previous ones, thus relaxing the need for continuous monitoring of the measurement error. The overall framework is then used in a novel Model Predictive Control approach. The results are illustrated through simulated examples. © 2010 AACC.	en
heal.journalName	Proceedings of the 2010 American Control Conference, ACC 2010	en
dc.identifier.spage	4719	en
dc.identifier.epage	4724	en