File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: A synthesis approach to predictive control for networked control systems

TitleA synthesis approach to predictive control for networked control systems
Authors
KeywordsNetworked Control Systems
Predictive Control
Stabilit
Issue Date2014
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001331
Citation
The 33rd Chinese Control Conference (CCC 2014), Nanjing, China, 28-30 July 2014. In Chinese Control Conference, 2014, p. 7715-7720 How to Cite?
AbstractThis paper studies a synthesis approach to predictive control for networked control systems with data loss and quantization. An augmented Markov jump linear model with polytopic uncertainties is modeled to describe the quantization errors and possible data loss. Based on this model, a predictive control synthesis approach is developed, which involves online optimization of a infinite horizon objective and conditions to deal with system constraints. The proposed MPC algorithm guarantees closed-loop mean-square stability and constraints satisfaction. © 2014 TCCT, CAA.
Persistent Identifierhttp://hdl.handle.net/10722/217500
ISBN
ISSN
2020 SCImago Journal Rankings: 0.152

 

DC FieldValueLanguage
dc.contributor.authorZou, Y-
dc.contributor.authorLam, J-
dc.contributor.authorNiu, Y-
dc.contributor.authorLi, D-
dc.date.accessioned2015-09-18T06:01:04Z-
dc.date.available2015-09-18T06:01:04Z-
dc.date.issued2014-
dc.identifier.citationThe 33rd Chinese Control Conference (CCC 2014), Nanjing, China, 28-30 July 2014. In Chinese Control Conference, 2014, p. 7715-7720-
dc.identifier.isbn978-988156384-2-
dc.identifier.issn1934-1768-
dc.identifier.urihttp://hdl.handle.net/10722/217500-
dc.description.abstractThis paper studies a synthesis approach to predictive control for networked control systems with data loss and quantization. An augmented Markov jump linear model with polytopic uncertainties is modeled to describe the quantization errors and possible data loss. Based on this model, a predictive control synthesis approach is developed, which involves online optimization of a infinite horizon objective and conditions to deal with system constraints. The proposed MPC algorithm guarantees closed-loop mean-square stability and constraints satisfaction. © 2014 TCCT, CAA.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://www.ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001331-
dc.relation.ispartofChinese Control Conference-
dc.rights©2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectNetworked Control Systems-
dc.subjectPredictive Control-
dc.subjectStabilit-
dc.titleA synthesis approach to predictive control for networked control systems-
dc.typeConference_Paper-
dc.identifier.emailLam, J: jlam@hku.hk-
dc.identifier.authorityLam, J=rp00133-
dc.description.naturepostprint-
dc.identifier.doi10.1109/ChiCC.2014.6896286-
dc.identifier.scopuseid_2-s2.0-84907943577-
dc.identifier.hkuros254433-
dc.identifier.spage7715-
dc.identifier.epage7720-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 151207-
dc.identifier.issnl1934-1768-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats