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Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm

Two different types of switching mechanism are considered in this thesis; one is featured with abrupt/sudden switching while the other one shows gradual changing behavior in its dynamics. It is shown that, through the comparison of the identification results from the proposed method and a benchmark method, the proposed robust identification method can achieve better performance when dealing with the data set mixed with outliers.

To model the switched systems exhibiting gradual or smooth transition among different local models, in addition to estimating the local sub-systems parameters, a smooth validity (an exponential function) function is introduced to combine all the local models so that throughout the working range of the gradual switched system, the dynamics of the nonlinear process can be appropriately approximated. Verification results on a simulated numerical example and CSTR process confirm the effectiveness of the proposed Linear Parameter Varying (LPV) identification algorithm. / Process Control

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/1056
Date06 1900
CreatorsJin, Xing
ContributorsHuang, Biao (Chemical and Materials Eng.), Stevan Dubljevic (Chemical and Materials Eng.), Qing Zhao (Electrical and Computer Eng.)
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Format1050474 bytes, application/pdf
RelationAIChE Journal, 2009

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