A Bayesian framework for the identification of hybrid systems

A.L. Juloski, S. Weiland

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

Abstract

In this paper we present a framework for identification of hybrid systems, based on switched input/output (SIO) models. The property of linearity for SIO models is defined. We further define hybrid generalizations of classic linear input/output models, such as switched ARX, switched ARMAX, and switched output error models which are shown to be linear in the SIO sense, and Box-Jenkins model, which is not linear. A Bayesian algorithm for identification of linear SIO models is developed. Operation of the developed algorithm is demonstrated on an example.
Original languageEnglish
Title of host publicationProceeedings of the 17th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2006) July 24-28, 2006, Kyoto, Japan
PublisherMTNS
PagesWeA05.5-
Publication statusPublished - 2006
Event17th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2006) - Kyoto, Japan
Duration: 24 Jul 200628 Jul 2006
Conference number: 17th

Conference

Conference17th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2006)
Abbreviated titleMTNS 2006
Country/TerritoryJapan
CityKyoto
Period24/07/0628/07/06

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