A Bayesian approach to the identification of piece-wise linear output error models

A.L. Juloski, S. Weiland

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

Abstract

In this paper we develop an algorithm for the identification of piecewise linear output error models for the case where the discrete mode of the underlying hybrid system is not known. The presented algorithm is based on a Bayesian framework, i.e. unknown model parameters are treated as random variables and described with probability density functions. The identification problem is posed as a problem of computing the posterior parameter densities, given the prior densities and the observed data. A suboptimal identification algorithm is derived. Operation of the algorithm is demonstrated on an example.
Original languageEnglish
Title of host publicationProceedings of the 14th IFAC Symposium on System Identification (SYSID-2006) March 29-31, 2006, Newcastle, Australia : Vol 14.
EditorsB. Ninness, H. Hjalmarsson
Publication statusPublished - 2006
Event14th IFAC Symposium on System Identification (SYSID 2006) - Newcastle, Australia
Duration: 29 Mar 200631 Mar 2006
Conference number: 14

Conference

Conference14th IFAC Symposium on System Identification (SYSID 2006)
Abbreviated titleSYSID 2006
CountryAustralia
CityNewcastle
Period29/03/0631/03/06

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