Thursday , November 30 2023

Actuator Fault Estimation Based on LPV Unknown
Input Observer for Induction Machine

Ahmed AMRANE1*, Abdelkader LARABI2, Abdel AITOUCHE3

1 National School of Technology, Diplomatic city,
Dergana, Bordj El Kiffan, 16121, Algiers, Algeria, and
CRIStAL UMR CNRS 9189, University of Lille 1,
Lille, 59650, France.,
(*Corresponding author)

1, 2 Laboratory of Systems Electric and Industrial (LSEI),
University of Science and Technology (USTHB),
BP 32, EI Alia, Bab- Ezzouar 16111, Algiers, Algeria.
3 CRIStAL UMR CNRS 9189, Hautes études d’ingénieur HEI-Lille,
Lille, 59046, France,

ABSTRACT: This paper presents an unknown inputs observer (UIO) applied to an induction machine (IM) in order to estimate the actuator faults and the state variables. Knowing that the machine used is highly nonlinear, a model based on LPV (linear parameter varying) system of the machine is used. Indeed, using the induction machine based on LPV model, we develop the structure of an observer where the actuator faults are the unknown inputs. The conditions for convergence are based on the Lyapunov theory that will ensure the stability. Based on the LMI (Linear Matrix Inequalities), the gains of the UIO subject to actuator faults are confirmed and then ensure the efficiency of our approach. The obtained results through simulations demonstrate the effectiveness of the proposed approach.

KEYWORDS: Induction motor; unknown inputs observer; linear parameter varying (LPV); Linear Matrix Inequalities (LMI); actuator faults.


Ahmed AMRANE*, Abdelkader LARABI, Abdel AITOUCHE,
Actuator Fault Estimation Based on LPV Unknown Input Observer for Induction Machine, Studies in Informatics and Control, ISSN 1220-1766, vol. 26(3), pp. 295-304, 2017.