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Article: A novel dual-mode predictive control strategy for constrained Wiener systems

TitleA novel dual-mode predictive control strategy for constrained Wiener systems
Authors
KeywordsAsymptotic Stability
Dual-Mode Control
Input Constraint
Predictive Control
Process Control
Subspace Method
Issue Date2010
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/5510
Citation
International Journal Of Robust And Nonlinear Control, 2010, v. 20 n. 9, p. 975-986 How to Cite?
AbstractIn process industry, there exist many Wiener systems with input magnitude constraints for which, however, most of the existing control algorithms cannot guarantee to have sufficiently large regions of asymptotic stability. In this paper, the subspace method is applied to separate the nonlinear and linear blocks in a constrained multi-input/multi-output (MIMO) Wiener system and a novel dual-mode nonlinear model predictive control algorithm is developed to maximize the region of the asymptotic stability. Simulation results are presented to demonstrate the virtues of this new control algorithm. The limitation is the requirement that the state and input matrices of the Wiener system's linear block should be accurately identified. Copyright © 2009 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/157069
ISSN
2015 Impact Factor: 2.527
2015 SCImago Journal Rankings: 2.134
ISI Accession Number ID
Funding AgencyGrant Number
National Natural Science Foundation of China (NNSFC)60704041
Research Fund for the Doctoral Program of Higher Education (RFDP)20070487090
Funding Information:

Contract/grant sponsor: National Natural Science Foundation of China (NNSFC); contract/grant number: 60704041

References

 

DC FieldValueLanguage
dc.contributor.authorZhang, HTen_US
dc.contributor.authorChen, Gen_US
dc.contributor.authorChen, MZQen_US
dc.date.accessioned2012-08-08T08:45:12Z-
dc.date.available2012-08-08T08:45:12Z-
dc.date.issued2010en_US
dc.identifier.citationInternational Journal Of Robust And Nonlinear Control, 2010, v. 20 n. 9, p. 975-986en_US
dc.identifier.issn1049-8923en_US
dc.identifier.urihttp://hdl.handle.net/10722/157069-
dc.description.abstractIn process industry, there exist many Wiener systems with input magnitude constraints for which, however, most of the existing control algorithms cannot guarantee to have sufficiently large regions of asymptotic stability. In this paper, the subspace method is applied to separate the nonlinear and linear blocks in a constrained multi-input/multi-output (MIMO) Wiener system and a novel dual-mode nonlinear model predictive control algorithm is developed to maximize the region of the asymptotic stability. Simulation results are presented to demonstrate the virtues of this new control algorithm. The limitation is the requirement that the state and input matrices of the Wiener system's linear block should be accurately identified. Copyright © 2009 John Wiley & Sons, Ltd.en_US
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/5510en_US
dc.relation.ispartofInternational Journal of Robust and Nonlinear Controlen_US
dc.subjectAsymptotic Stabilityen_US
dc.subjectDual-Mode Controlen_US
dc.subjectInput Constrainten_US
dc.subjectPredictive Controlen_US
dc.subjectProcess Controlen_US
dc.subjectSubspace Methoden_US
dc.titleA novel dual-mode predictive control strategy for constrained Wiener systemsen_US
dc.typeArticleen_US
dc.identifier.emailChen, MZQ:mzqchen@hku.hken_US
dc.identifier.authorityChen, MZQ=rp01317en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1002/rnc.1491en_US
dc.identifier.scopuseid_2-s2.0-77953004172en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77953004172&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume20en_US
dc.identifier.issue9en_US
dc.identifier.spage975en_US
dc.identifier.epage986en_US
dc.identifier.isiWOS:000278418200002-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridZhang, HT=7409192616en_US
dc.identifier.scopusauthoridChen, G=36012928800en_US
dc.identifier.scopusauthoridChen, MZQ=35085827300en_US

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