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Robust fault detection and estimation for descriptor systems based on multi-models concept

  • Habib Hamdi
  • Mickael RodriguesEmail author
  • Chokri Mechmeche
  • Naceur Benhadj Braiek
Technical Notes and Correspondence Intelligent and Information Systems

Abstract

This paper addresses the robust fault detection and estimation problem of nonlinear descriptor system with unknown inputs observers. The considered nonlinear descriptor system is transformed into an equivalent multi-models form by using the Takagi-Sugeno (T-S) approach. Two cases are considered: the first one deals with the multi-models based on measurable decision variables and the second one assumes that these decision variables are unmeasurable. Then, a residual generator based on an unknown observer is designed for both fault detection and estimation. Stability analysis and gain matrices determination are performed by resolving a set of Linear Matrices Inequalities (LMIs) for both cases. The performances of the proposed fault detection and estimation method is successfully applied to an electrical circuit.

Keywords

Descriptor multi-models fault detection and estimation Linear Matrices Inequalities (LMIs) residual generation 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Habib Hamdi
    • 1
  • Mickael Rodrigues
    • 2
    Email author
  • Chokri Mechmeche
    • 1
  • Naceur Benhadj Braiek
    • 1
  1. 1.Laboratory for Advanced Systems (LSA)Polytechnic School of TunisiaTunisTunisia
  2. 2.Laboratory Automation and Engineering Process (LAGEP), CNRS UMR 5007University Lyon1Lyon1France

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