Energy-based mode tracking of hybrid systems for FDI

Shai A. Arogeti, Danwei Wang, Chang Boon Low, Ming Luo

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Hybrid systems operate in various states, which are represented by a set of modes. In each mode, the system is governed by continuous dynamics, and different modes correspond to different continuous models. For hybrid systems, model-based fault detection and isolation is a challenging task due to the fact that the system's prevailing dynamical model and its current mode (discrete state) are mutually dependent and intertwined. In this paper, a new energy-based approach is introduced for mode tracking of hybrid systems, and its associated systematic analysis is based on a hybrid bond graph. Each system's mode is characterized by a concise energy relation that allows mode identification in the new mode tracking method.

Original languageEnglish
Pages (from-to)14-28
Number of pages15
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Volume43
Issue number1
DOIs
StatePublished - 1 Jan 2013

Keywords

  • Fault diagnosis and isolation
  • Hybrid systems
  • Model based
  • Power net (PN)

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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