Diagnosis of hybrid systems: part 2 - residual generator selection and diagnosis in the presence of unreliable residual generators

  • Authors:

  • R. Mohammadi;S. Hashtrudi-Zad;K. Khorasani

  • Affiliations:

  • Department of Electrical and Computer Engineering, Concordia University, Montréal, QC, Canada;Department of Electrical and Computer Engineering, Concordia University, Montréal, QC, Canada;Department of Electrical and Computer Engineering, Concordia University, Montréal, QC, Canada

  • Venue:
  • SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
  • Year:
  • 2009

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Abstract

We have presented a framework in [6] for fault diagnosis of hybrid systems modeled by hybrid automata and investigated the diagnosability of failure modes in hybrid automata. In this framework, we assume that there is a bank of residual generators designed for the continuous dynamics of the system. We have developed a hybrid diagnosis approach in which faults are diagnosed by integrating the information generated by the residual generators and the information at the discrete-event system representation of the system. In this paper, we study the problem of residual generator selection in hybrid automata. Moreover, we investigate fault diagnosis of hybrid systems in the presence of unreliable residual generators generating false alarms or false silence signals.