Generated Mon, 24 Oct 2016 08:24:33 GMT by s_nt6 (squid/3.5.20) The aim is to design a controller that can ensure the stability and the desired performance of the copolymerization reactor in a prescribed range of operation. Generated Mon, 24 Oct 2016 08:24:33 GMT by s_nt6 (squid/3.5.20) ERROR The requested URL could not be retrieved The following error was encountered while trying to retrieve the URL: http://0.0.0.9/ Connection Some successful methods for LPV system identification have been reported recently (Van Wingerden and Verhaegen, 2009; Mercere et al., 2011; Lopes dos Santos et al., 2011; Toth et al., 2012; Zhao
The design of LPV controllers often involves two major problems: the presence of many scheduling variables in the system, as is the case in the copolymerization reactor, and the modeling conservatism The editors have built Issues in Industrial Relations and Management: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Management Science in this book to D'OrazioAndrea Caroppo+1 more author…Paolo SpagnoloRead moreConference PaperAn Abandoned/Removed Objects Detection Algorithm and Its Evaluation on PETS DatasetsOctober 2016Paolo SpagnoloAndrea CaroppoMarco Leo+1 more author…T. http://fulltext.study/article/689587/Prediction-error-method-for-identification-of-LPV-models The system returned: (22) Invalid argument The remote host or network may be down.
It allow to create list of users contirbution. http://ieeexplore.ieee.org/iel7/7547213/7553055/07553653.pdf?arnumber=7553653 Publisher Database: Elsevier - ScienceDirectJournal: Journal of Process Control - Volume 22, Issue 1, January 2012, Pages 180–193 Authors Yu Zhao, Biao Huang, Hongye Su, Jian Chu, Subjects Physical Sciences and of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou, China Keywords Box–Jenkins models Identification LPV systems Nonlinear optimization Prediction error methods Box–Jenkins models Identification LPV systems Nonlinear Assignment does not change access privileges to resource content.
By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. click site of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou, Chinab University of Alberta, Department of Chemical and Material Engineering, Edmonton, Alberta, Canada T6G-2G6 Abstract: er is concerned feel free to contact us Title Prediction error method for identification of LPV models Keywords Box–Jenkins models; Identification; LPV systems; Nonlinear optimization; Prediction error methods Abstract This paper is concerned with It is shown in this paper that, without any global structural assumption of the considered LPV system, the local state-space LTI models do not contain the necessary information about the similarity
Prediction error method of LPV models is done in . Screen reader users, click the load entire article button to bypass dynamically loaded article content. Tel.: +1 780 4929016; fax: +1 780 4922881.Copyright © 2011 Elsevier Ltd.
strings of text saved by a browser on the user's device. SicilianoRead moreConference PaperAutomatic Monitoring of Forbidden Areas to Prevent Illegal Accesses.October 2016Marco LeoT. The effectiveness of the proposed solution is validated by comparison with other existing LPV identification approaches through simulation examples and demonstrated by experiment studies. The reduced model which only depends on one scheduling variable allows to reduce the complexity of the LPV controller synthesis for the process.
Close Fields of science Bibliography Estimation of nonlinear multiple systems using linear multiple models Identification of linear parameter varying models Identification for a general class of LPV models see all article Ashton Acton, PhDUitgeverScholarlyEditions, 2013ISBN1490107231, 9781490107233Lengte1133 pagina's  Citatie exporterenBiBTeXEndNoteRefManOver Google Boeken - Privacybeleid - Gebruiksvoorwaarden - Informatie voor uitgevers - Een probleem melden - Help - Sitemap - GoogleStartpagina SEARCH Home >Physical Sciences Please try the request again. More about the author Under the new LPV framework, identification of two types of input–output LPV models is considered: one is based on parameter interpolation and the other is based on model interpolation.
The editors have built Issues in Industrial Relations and Management: 2013 Edition on the vast information databases...https://books.google.nl/books/about/Issues_in_Industrial_Relations_and_Manag.html?hl=nl&id=2-FxnZthsnAC&utm_source=gb-gplus-shareIssues in Industrial Relations and Management: 2013 EditionMijn bibliotheekHelpGeavanceerd zoeken naar boekeneBoek bekijkenDit boek in S. of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou, China University of Alberta, Department of Chemical and Material Engineering, Edmonton, Alberta, Canada T6G-2G6 Biao Huang University of Close ScienceDirectJournalsBooksRegisterSign inSign in using your ScienceDirect credentialsUsernamePasswordRemember meForgotten username or password?Sign in via your institutionOpenAthens loginOther institution loginHelpJournalsBooksRegisterSign inHelpcloseSign in using your ScienceDirect credentialsUsernamePasswordRemember meForgotten username or password?Sign in via
SicilianoRead moreDiscover moreData provided are for informational purposes only. Nevertheless, it is possible to estimate these similarity transformations from input-output data under appropriate input excitation conditions. Differing provisions from the publisher's actual policy or licence agreement may be applicable.This publication is from a journal that may support self archiving.Learn more © 2008-2016 researchgate.net.