Adaptive neural network internal model control for PMSM speed regulation
Joint Authors
Furayjat, Zaynab
Zribi, Ali
Chtourou, Muhammad
Source
Issue
Vol. 14, Issue 2 (30 Jun. 2018), pp.118-126, 9 p.
Publisher
Publication Date
2018-06-30
Country of Publication
Algeria
No. of Pages
9
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
In this paper, based on the combination of particle swarm optimization (PSO) algorithm and neural network (NN), an adaptive neural network internal model control (NNIMC) is designed for a permanent magnet synchronous motor (PMSM).
Firstly, in order to accelerate the convergent speed and to prevent problems of trapping in local minimum, PSO algorithm is applied in feedforward neural network to optimize the NN model's and the NN controller’s parameters.
For the adaptation of the learning algorithm of the NN controller, gradient descent method is used, secondly, to achieve high-performance speed tracking.
The robustness and effectiveness of the proposed PMSM drive scheme is confirmed by simulation tests in the MATLAB/SIMULINK.
American Psychological Association (APA)
Furayjat, Zaynab& Zribi, Ali& Chtourou, Muhammad. 2018. Adaptive neural network internal model control for PMSM speed regulation. Journal of Electrical Systems،Vol. 14, no. 2, pp.118-126.
https://search.emarefa.net/detail/BIM-835151
Modern Language Association (MLA)
Furayjat, Zaynab…[et al.]. Adaptive neural network internal model control for PMSM speed regulation. Journal of Electrical Systems Vol. 14, no. 2 (2018), pp.118-126.
https://search.emarefa.net/detail/BIM-835151
American Medical Association (AMA)
Furayjat, Zaynab& Zribi, Ali& Chtourou, Muhammad. Adaptive neural network internal model control for PMSM speed regulation. Journal of Electrical Systems. 2018. Vol. 14, no. 2, pp.118-126.
https://search.emarefa.net/detail/BIM-835151
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 126
Record ID
BIM-835151