A method for the estimation of infrequent abrupt changes in nonlinear systems

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This paper presents a framework for obtaining better performance from multiple model approaches for estimating infrequent abrupt changes in nonlinear systems. By using insight into the nature of the problem and basic probability, a procedure that greatly reduces the number of filters required by multiple model approaches is obtained. This allows for a much longer detection horizon without increasing the computational requirements and results in improved performance over standard multiple model approaches. The performance of this approach is evaluated for state/parameter estimation of a heptane to toluene aromatization process. The method is also shown to be robust to errors in the assumed noise statistics. (C) 1998 Elsevier Science Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
1998-02
Language
English
Article Type
Article
Keywords

MULTIPLE

Citation

AUTOMATICA, v.34, no.2, pp.261 - 270

ISSN
0005-1098
DOI
10.1016/S0005-1098(97)00192-1
URI
http://hdl.handle.net/10203/67819
Appears in Collection
CBE-Journal Papers(저널논문)
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