A review on soft computing techniques used in induction motor drive application
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<div align="center"><table width="590" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="387"><p>In this paper, hybrid models based on fuzzy systems and neural networks are reviewed. A fuzzy inference system is explicitly represented by expertise for induction motor drives, incorporating the learning capability of artificial neural networks. Researchers have been attracted to neuro-fuzzy techniques for training and inference in induction motor drives due to their efficiency. According to the classification of research articles from 2000 to 2020, this article presents a review of different artificial neural network techniques, fuzzy and neuro-fuzzy systems. The main objective is to provide a concise overview of current neuro-fuzzy research and to enable readers to identify appropriate methods according to their research interests.</p><p> </p></td></tr></tbody></table></div>
Publication details
- DOI
- 10.11591/ijpeds.v15.i2.pp753-768
- OpenAlex
- W4393964827
- Document type
- article
- Language
- EN
- Source
- International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
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