Hybrid identification of time-varying parameter with particle filtering and expectation maximization

András Hartmann, Susana Vinga, João M. Lemos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The problem of time-varying parameter identification is considered on a class of nonlinear hybrid systems. It is assumed that inputs and outputs are directly measured, and a subset of system parameters can take different values from a finite set at each time instance. An offline (batch) algorithm that combines particle filtering and the expectation maximization is introduced for the identification of such systems. The efficiency of the proposed method is illustrated through simulated examples.

Original languageEnglish
Title of host publication2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings
Pages884-889
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Platanias-Chania, Crete, Greece
Duration: 25 Jun 201328 Jun 2013

Publication series

Name2013 21st Mediterranean Conference on Control and Automation, MED 2013 - Conference Proceedings

Conference

Conference2013 21st Mediterranean Conference on Control and Automation, MED 2013
Country/TerritoryGreece
CityPlatanias-Chania, Crete
Period25/06/1328/06/13

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