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Gradient-Based Recursive Maximum Likelihood Identification of Jump Markov Non-Linear Systems
University of Federal Ceara, Brazil.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Aeronaut Institute Technology, Brazil.
2017 (English)In: 2017 20TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), IEEE , 2017, p. 228-234Conference paper, Published paper (Refereed)
Abstract [en]

This paper deals with state inference and parameter identification in Jump Markov Non-Linear System. The state inference problem is solved efficiently using a recently proposed Rao-Blackwellized Particle Filter, where the discrete state is integrated out analytically. Within the RBPF framework, Recursive Maximum Likelihood parameter identification is performed using gradient ascent algorithms. The proposed learning method has the advantage over (online) Expectation Maximization methods, that it can be easily applied to cases where the probability density functions defining the Jump Markov Non-Linear System are not members of the exponential family. Two benchmark problems illustrate the parameter identification performance.

Place, publisher, year, edition, pages
IEEE , 2017. p. 228-234
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-142451DOI: 10.23919/ICIF.2017.8009651ISI: 000410938300034ISBN: 978-0-9964-5270-0 OAI: oai:DiVA.org:liu-142451DiVA: diva2:1153621
Conference
20th International Conference on Information Fusion (Fusion)
Note

Funding Agencies|CNPq - Conselho Nacional de Desenvolvimento Cientifico e Tecnologico; CISB - Centro de Pesquisa e Inovacao Sueco-Brasileiro and Saab AB; Vinnova Industry Excellence Center ELLIIT at Linkoping University

Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2017-10-31

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf