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.
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. https://doi.org/10.24846/v26i3y201705
All articles published by Studies in Informatics and Control (SIC) are published in accordance with the terms and conditions of the Creative Commons Attribution License (CC BY-NC-SA 4.0).