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Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-540-78482-1_9
DC FieldValue
dc.titleMultivariable process identification
dc.contributor.authorWang, Q.-G.
dc.contributor.authorYe, Z.
dc.contributor.authorCai, W.-J.
dc.contributor.authorHang, C.-C.
dc.date.accessioned2014-06-17T02:58:06Z
dc.date.available2014-06-17T02:58:06Z
dc.date.issued2008
dc.identifier.citationWang, Q.-G.,Ye, Z.,Cai, W.-J.,Hang, C.-C. (2008). Multivariable process identification. Lecture Notes in Control and Information Sciences 373 : 219-249. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-540-78482-1_9" target="_blank">https://doi.org/10.1007/978-3-540-78482-1_9</a>
dc.identifier.isbn9783540784814
dc.identifier.issn01708643
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/56743
dc.description.abstractChapters 5-7 present several new PID controller design methods for MIMO systems but all these methods are model-based. That's why system identification plays an important role in the control engineering. This chapter focuses on system identification for both SISO and MIMO systems. Several identification algorithms are presented. The biggest improvement to the existing methods is that our methods can give accurate system model even in presence of time delay, unknown initial conditions and disturbances. © 2008 Springer-Verlag Berlin Heidelberg.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-540-78482-1_9
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentDIVISION OF ENGINEERING AND TECH MGT
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1007/978-3-540-78482-1_9
dc.description.sourcetitleLecture Notes in Control and Information Sciences
dc.description.volume373
dc.description.page219-249
dc.identifier.isiutNOT_IN_WOS
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