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A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre. (System Identification)ORCID-id: 0000-0001-5474-7060
KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre. (System Identification)ORCID-id: 0000-0002-9368-3079
2016 (engelsk)Inngår i: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 3060-3065, artikkel-id 7798727Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2016. s. 3060-3065, artikkel-id 7798727
Serie
IEEE Conference on Decision and Control, ISSN 0743-1546
HSV kategori
Forskningsprogram
Elektro- och systemteknik
Identifikatorer
URN: urn:nbn:se:kth:diva-186218DOI: 10.1109/CDC.2016.7798727ISI: 000400048103040Scopus ID: 2-s2.0-85010790149ISBN: 978-1-5090-1837-6 (tryckt)OAI: oai:DiVA.org:kth-186218DiVA, id: diva2:950982
Konferanse
55th IEEE Conference on Decision and Control, CDC 2016, ARIA Resort and Casino, Las Vegas, United States, 12 December 2016 through 14 December 2016
Forskningsfinansiär
Swedish Research Council, 2015-05285EU, European Research Council, 67381
Merknad

QC 20170614

Tilgjengelig fra: 2016-05-04 Laget: 2016-05-04 Sist oppdatert: 2017-12-04bibliografisk kontrollert

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