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

被引：2
|
作者：
Amrane, Ahmed [1 ,2 ,3 ]
Larabi, Abdelkader [3 ]
Aitouche, Abdel [4 ]
机构：
[1] Natl Sch Technol, Algiers 16121, Algeria
[2] Univ Lille 1, CRIStAL UMR CNRS 9189, F-59650 Lille, France
[3] Univ Sci & Technol USTHB, Lab Syst Elect & Ind, BP 32, Algiers 16111, Algeria
[4] Hautes Etud Ingenieur HEI Lille, CRIStAL UMR CNRS 9189, F-59046 Lille, France
来源：
STUDIES IN INFORMATICS AND CONTROL | 2017年 / 26卷 / 03期
关键词：
Induction motor; Unknown inputs observer; Linear parameter varying (LPV); Linear Matrix Inequalities (LMI); Actuator faults; NONLINEAR-SYSTEMS; SENSOR;
D O I：
10.24846/v26i3y201705
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：295 / 304
页数：10
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