scholarly journals TakagiSugeno Fuzzy Observer Design for Induction Motors with unmeasurable Decision Variables: State Estimation and Sensor Fault Detection

2011 ◽  
Vol 23 (4) ◽  
pp. 44-51 ◽  
Author(s):  
M. Allouche ◽  
M. Chaabane ◽  
M. Souissi ◽  
D. Mehdi ◽  
F. Tadeo
Keyword(s):  
Fault Detection ◽  
State Estimation ◽  
Induction Motors ◽  
Observer Design ◽  
Sensor Fault ◽  
Fuzzy Observer ◽  
Decision Variables ◽  
Sensor Fault Detection

Steady-state speed sensor fault detection in induction motors with uncertain parameters: A matter of algebraic equations

2018 ◽  
Vol 80 ◽  
pp. 125-137 ◽  
Author(s):  
Cristiano Maria Verrelli ◽  
Emilio Lorenzani ◽  
Raffaele Fornari ◽  
Michele Mengoni ◽  
Luca Zarri
Keyword(s):  
Steady State ◽  
Fault Detection ◽  
Induction Motors ◽  
Uncertain Parameters ◽  
Algebraic Equations ◽  
Sensor Fault ◽  
Speed Sensor ◽  
Sensor Fault Detection

Adaptive Observer Design for Sensor Fault Detection and Reconstruction

2019 ◽  
Vol 20 (9) ◽  
pp. 515-523
Author(s):  
N. Bedioui ◽  
R. Houimli ◽  
M. Besbes
Keyword(s):  
Fault Detection ◽  
Sufficient Conditions ◽  
Main Idea ◽  
Observer Design ◽  
Adaptive Observer ◽  
Linear Matrix ◽  
Sensor Fault ◽  
Sensor Fault Detection ◽  
Robust Adaptive ◽  
The Stability

A new approach is presented for sensor fault detection reconstruction and state estimation. The system considered is linear polytopic parameter-vary ing (LPV) system. The main idea is the design of a novel robust adaptive observer based on and polyquadratic formulation with a new set of relaxation. Sufficient conditions are given by a set of Linear Matrix Inequalities (LMI) in order to guarantee the stability of the system and the asymptotic convergence of the fault error. A simulation example has been studied to illustrate the proposed methods by detecting constant and variable sensor fault.

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