Speed Control of Induction Motor using Artificial Neural Network

[1] K. J. Astrm. Introduction to Control. Department of Automatic Control, Lund Institute of Technology, 2004.
[2] J. M. Maciejowski, Predictive Control with Constraints. Pearson Education Limited, 2002.
[3] Johan Akesson and Per Hagander. Integral action-a disturbance observer approach. Proceeding of the 7th European Control Conference, ECC’03, Sept. 1-4, 2003.
[4] E. A. Mendrela and E. Gierczac, “Double-winding rotary-linear induction motor”, IEEE Transactions of Energy Conversion, vol. EC-2, no. 1, pp. 47-54, 1987.
[5]J. Fleszar and E. Mendrela, “Twin-armature rotary-linear induction motor”, IEE PROC., vol. 130, no. 3, pp. 186-192, May 1983.
[6] Y. Sangsefidi, S. Ziaeinejad and A. Mehrizi-Sani, “A new two-motor drive to control a two-phase induction motor and a DC motor,” 2015 IEEE International Electric Machines & Drives Conference (IEMDC), Coeur d’Alene, ID, USA, pp. 818-822,
doi: 10.1109/IEMDC. 2015.7409154, 2015.
[7] C. Li, D. Xu and G. Wang, “High efficiency remanufacturing of induction motors with interior permanent-magnet rotors and synchronous-reluctance rotors,” 2017 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC
Asia-Pacific), Harbin, pp. 1-6, doi: 10.1109/ITEC-AP.2017.8080993, 2017.
[8] P. V. Patil and S. A. Naveed, “Implementation of VFD Application for Speed Control of Induction Motor,” 2020 International Conference on Smart Innovations in Design, Environment, Management, Planning and Computing (ICSIDEMPC),
Aurangabad, India, pp. 168-170, doi: 10.1109/ICSIDEMPC49020.2020.9299636, 2020.
[9] Z. Hailong, G. Wenyan and J. Bo, “Machine Learning and Lexicon Based Methods for Sentiment Classification: A Survey,” 2014 11th Web Information System and Application Conference, Tianjin, pp. 262-265, doi: 10.1109/WISA.2014.55, 2014.
[10] P. Parvathi and T. S. Jyothis, “Identifying Relevant Text from Text Document Using Deep Learning,” 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET), Kottayam, India, pp. 1-4, doi:
10.1109/ICCSDET.2018.8821192, 2018.
[11] F. Wei, H. Qin, S. Ye and H. Zhao, “Empirical Study of Deep Learning for Text Classification in Legal Document Review,” 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, pp. 3317-3320,
doi: 10.1109/BigData.2018.8622157, 2018.
[12] E. Phaisangittisagul, Y. Koobkrabee, K. Wirojborisuth, T. Ratanasrimetha and S. Aummaro, “Target Advertising Classification using Combination of Deep Learning and Text model,” 2019 10th International Conference of Information and
Communication Technology for Embedded Systems (IC-ICTES), Bangkok, Thailand, pp. 1-4, doi: 10.1109/ICTEmSys.2019.8695956, 2019.
[13] Winda Kurnia Sari, Dian Palupi Rini and Reza Firsandaya Malik, “Text Classification Using Long Short- Term Memory”, International Conference on Electrical Engineering and Computer Science (ICECOS) 2019.