Unknown input observer design for fault sensor estimation applied to induction machine
From MaRDI portal
Publication:1997852
DOI10.1016/j.matcom.2018.09.018OpenAlexW2895836654MaRDI QIDQ1997852
Ahmed Amrane, Abdelkader Larabi, Abdel Aitouche
Publication date: 6 March 2021
Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.matcom.2018.09.018
induction motorsensor faultslinear matrix inequalities (LMI)linear parameter varying (LPV)unknown inputs observer
Operations research and management science (90Bxx) Controllability, observability, and system structure (93Bxx)
Related Items
Integration of genetic algorithm tuned adaptive fading memory Kalman filter with model predictive controller for active fault-tolerant control of cement kiln under sensor faults with inaccurate noise covariance ⋮ A novel robust fault estimation observer design for semi‐Markovian jump systems with partially bounded transition rate
Cites Work
- An accurate model of squirrel cage induction machines under stator faults.
- Neural networks application for induction motor faults diagnosis.
- Detection filter design for LPV systems -- a geometric approach.
- Fault detection and isolation in non-linear systems by using oversized neural networks
- Passive robust fault detection using fuzzy parity equations
- Convergence analysis of back-EMF MRAS observers used in sensorless control of induction motor drives
- An induction machine and power electronic test system on a field-programmable gate array
