scholarly journals Fault Tolerant Control Using Artificial Neural Network for Induction Machine

2019 ◽  
Vol 74 (2-4) ◽  
pp. 47-55
Author(s):  
F. Mekhalfia ◽  
D.E. Khodja ◽  
S. Chakroune
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fault Tolerant ◽  
Induction Machine ◽  
Fault Tolerant Control ◽  
Artificial Neural

scholarly journals Adaptive fault-tolerant model for improving cloud computing performance using artificial neural network

2020 ◽  
Vol 170 ◽  
pp. 929-934
Author(s):  
Awatif Ragmani ◽  
Amina Elomri ◽  
Noreddine Abghour ◽  
Khalid Moussaid ◽  
Mohammed Rida ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Cloud Computing ◽  
Fault Tolerant ◽  
Computing Performance ◽  
Artificial Neural

scholarly journals Artificial neural network vector controlled common high-side switch asymmetric converter fed switched reluctance motor drive

2021 ◽  
Vol 24 (2) ◽  
pp. 697
Author(s):  
Ashok Kumar Kolluru ◽  
Malligunta Kiran Kumar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Machine ◽  
Switched Reluctance Motor ◽  
Switched Reluctance ◽  
Reluctance Machine ◽  
Reluctance Motor ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
The Cost

<p>The best alternative machine for synchronous and induction machine is switched reluctance machine for various applications. An artificial neural network (ANN) based vector controller is implemented for novel converter to drive switched reluctance motor (SRM) in this paper. To reduce the cost and simplified the controller an effective configuration of converter is proposed with only 4 pulse-withmodulation (PWM) based switches. The 6 pole stator and 4 pole rotor machine is considered in this paper to present results based on MATLAB. The ripples in torque are reduced by proposing vector controller by using novel configuration of converter. Generally SRM machines are having high ripples in torque, hence less number of switches will be feasible solution to drive the machine in order to reduce ripples. The proposed controller can also help to operate system with less ripples in torque since the controller having both torque and flux hysteresis controllers. The extensive results are presented on Simulink platform to validate the proposed method under both steady state as well as transient conditions.</p>

scholarly journals vector control of Induction machine using distributed delay neural flux observers

2019 ◽  
Author(s):  
Daniel Igbokwe
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Vector Control ◽  
Induction Motor ◽  
Electric Vehicle ◽  
Induction Machine ◽  
Distributed Delay ◽  
Artificial Neural

Vector control of induction motor, has gaineddominance due to the improvement of computing hardware and the extended use of induction motor beyond industrial uses such asthe electric vehicle, and automated medicalmachinery. The removal of the flux sensorsnecessitates the use of estimators to estimatethe flux of induction machine. This paper usethe artificial neural network to estimate theflux of the induction motor along the directand quadrature axis, and make it available forfeedback. Distributed delay neural networkswhich are more suited for time series problems is used in place of plain feed forwardneural networks.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

2004 ◽  
Vol 171 (4S) ◽  
pp. 502-503
Author(s):  
Mohamed A. Gomha ◽  
Khaled Z. Sheir ◽  
Saeed Showky ◽  
Khaled Madbouly ◽  
Emad Elsobky ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Analysis ◽  
Renal Stones ◽  
Neural Network Analysis ◽  
Artificial Neural Network Analysis ◽  
Artificial Neural
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