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A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification)ORCID iD: 0000-0001-5474-7060
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification)ORCID iD: 0000-0002-9368-3079
2016 (English)In: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 3060-3065, article id 7798727Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 3060-3065, article id 7798727
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Signal Processing
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-186218DOI: 10.1109/CDC.2016.7798727ISI: 000400048103040Scopus ID: 2-s2.0-85010790149ISBN: 978-1-5090-1837-6 (print)OAI: oai:DiVA.org:kth-186218DiVA, id: diva2:950982
Conference
55th IEEE Conference on Decision and Control, CDC 2016, ARIA Resort and Casino, Las Vegas, United States, 12 December 2016 through 14 December 2016
Funder
Swedish Research Council, 2015-05285EU, European Research Council, 67381
Note

QC 20170614

Available from: 2016-05-04 Created: 2016-05-04 Last updated: 2024-03-15Bibliographically approved

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Abdalmoaty, MohamedHjalmarsson, Håkan

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CiteExportLink to record
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