Artificial Neural Network-Based Control of Switched Reluctance Motor for Torque Ripple Reduction
Joint Authors
Tariq, Iqra
Muzzammel, Raheel
Alqasmi, Umar
Raza, Ali
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-31, 31 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-07
Country of Publication
Egypt
No. of Pages
31
Main Subjects
Abstract EN
Switched reluctance motor is acquiring major attention because of its simple design, economic development, and reduced dependability.
These attributes make switched reluctance motors superior to other variable speed machines.
The major challenge associated with the development of a switched reluctance motor is its high torque ripple.
Torque ripple produces noise and vibration, resulting in degradation of its performance.
Various techniques are developed to cope with torque ripples.
Practically, there exists not a single mature technique for the minimization of torque ripples in switched reluctance motors.
In this research, a switched reluctance motor is modelled and analysed.
Its speed and current control are implemented through artificial neural networks.
Artificial neural network is found to be a promising technique as compared with other techniques because of its accuracy, reduced complexity, stability, and generalization.
The Levenberg–Marquardt algorithm is utilized in artificial neural networks due to its fast and stable convergence for training and testing.
It is found from research that artificial neural network-based improved control shows better performance of the switched reluctance motor.
Realization of this technique is further validated from its mean square error analysis.
Operating parameters of the switched reluctance motor are improved significantly.
Simulation environment is created in Matlab/Simulink.
American Psychological Association (APA)
Tariq, Iqra& Muzzammel, Raheel& Alqasmi, Umar& Raza, Ali. 2020. Artificial Neural Network-Based Control of Switched Reluctance Motor for Torque Ripple Reduction. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-31.
https://search.emarefa.net/detail/BIM-1202488
Modern Language Association (MLA)
Tariq, Iqra…[et al.]. Artificial Neural Network-Based Control of Switched Reluctance Motor for Torque Ripple Reduction. Mathematical Problems in Engineering No. 2020 (2020), pp.1-31.
https://search.emarefa.net/detail/BIM-1202488
American Medical Association (AMA)
Tariq, Iqra& Muzzammel, Raheel& Alqasmi, Umar& Raza, Ali. Artificial Neural Network-Based Control of Switched Reluctance Motor for Torque Ripple Reduction. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-31.
https://search.emarefa.net/detail/BIM-1202488
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202488