New approach for stability improvement of speed-sensorless induction-motor controls at zero frequency using multirate adaptive observer

2006 ◽  
Vol 153 (4) ◽  
pp. 544 ◽  
Author(s):  
N. Yamaguchi ◽  
M. Hasegawa ◽  
S. Doki ◽  
S. Okuma
Keyword(s):  
Induction Motor ◽  
Adaptive Observer ◽  
Speed Sensorless ◽  
New Approach ◽  
Motor Controls ◽  
Zero Frequency

Adaptive observer design for a class of nonlinear systems. Application to speed sensorless induction motor

Automatica ◽  
2018 ◽  
Vol 90 ◽  
pp. 239-247 ◽  
Author(s):  
Mondher Farza ◽  
Mohammed M’Saad ◽  
Tomas Ménard ◽  
Ali Ltaief ◽  
Tarak Maatoug
Keyword(s):  
Nonlinear Systems ◽  
Induction Motor ◽  
Observer Design ◽  
Adaptive Observer ◽  
Speed Sensorless

Neural Adaptive Kalman Filter for Sensorless Vector Control of Induction Motor

2017 ◽  
Vol 8 (4) ◽  
pp. 1841
Author(s):  
Ghlib Imane ◽  
Messlem Youcef ◽  
Gouichiche Abdelmadjid ◽  
Chedjara Zakaria
Keyword(s):  
Kalman Filter ◽  
Vector Control ◽  
Induction Motor ◽  
Classical Method ◽  
Adaptive Observer ◽  
Estimation Accuracy ◽  
Adaptive Kalman Filter ◽  
Speed Sensorless ◽  
Field Oriented Vector Control ◽  
Computationally Intensive

This paper presents a novel neural adaptive Kalman filter for speed sensorless field oriented vector control of induction motor. The adaptive observer proposed here is based on MRAS (model reference adaptive system) technique, where the linear Kalman filter calculate the stationary components of stator current and the rotor flux and the rotor speed  is calculated with an adaptive mechanism. Moreover, to improve the performance of the PI classical controller under different conditions, a novel adaptation scheme based on ADALINE (ADAptive LInear NEuron) neural network is used. It offers a solution to the PI parameters to stabilize automatically about their optimum values and speed estimation to converge quicker to the real. The proposed adaptive Kalman filter represents a good comprise between estimation accuracy and computationally intensive. The simulation results showed the robustness, efficiency, and superiority of the proposed scheme compared to the classical method even in low speed region.

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