Mode tracking and diagnosis of hybrid systems, an integrated approach

Rami Levy, Shai Arogeti, Danwei Wang

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

Abstract

In this paper, we integrate information from a hybrid bond agraph (HBG) model and discrete event systems (DES) into a fault diagnosis method for hybrid systems. In a pure HBG framework, mode change detection and isolation is handled by the mode change signature and the mode change signature matrix. In a DES approach, discrete states and faults are traced based on observable events and diagnosers. The integration of the two approaches is based on a new diagnoser that is driven by both, observable events and consistency indicators generated by continuous residuals. The proposed method allows not only to effectively trace the system mode, but also to decide whether this mode is faulty or normal. The new method is presented along with a theoretical example.

Original languageAmerican English
Title of host publication2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012
Pages1226-1231
Number of pages6
DOIs
StatePublished - 1 Dec 2012
Event2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012 - Guangzhou, China
Duration: 5 Dec 20127 Dec 2012

Publication series

Name2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012

Conference

Conference2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012
Country/TerritoryChina
CityGuangzhou
Period5/12/127/12/12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Mode tracking and diagnosis of hybrid systems, an integrated approach'. Together they form a unique fingerprint.

Cite this