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The Effect of Different Decision-Making Methods on Multi-Objective Optimisation of Predictive Torque Control Strategy

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Arshad, M. H., Abido, M. A., Salem, A. and Elsayed, A. H. (2019). Weighting Factors Optimization of Model Predictive Torque Control of Induction Motor Using NSGA-II With TOPSIS Decision Making. IEEE Access, 7, pp. 177595–177606. doi: 10.1109/ACCESS.2019.2958415.10.1109/ACCESS.2019.2958415 Search in Google Scholar

Davari, S. A., Norambuena, M., Nekoukar, V., Garcia, C. and Rodriguez, J. (2020). Even-Handed Sequential Predictive Torque and Flux Control. IEEE Transactions on Industrial Electronics, 67(9), pp. 7334–7342. doi: 10.1109/TIE.2019.2945274.10.1109/TIE.2019.2945274 Search in Google Scholar

Davari, S. A., Nekoukaar, V., Garcia, C. and Rodriguez, J. (2021). Online Weighting Factor Optimization by Simplified Simulated Annealing for Finite Set Predictive Control. IEEE Transactions on Industrial Informatics, 17(1), pp. 31–40. doi: 10.1109/TII.2020.2981039.10.1109/TII.2020.2981039 Search in Google Scholar

Guazzelli, P. R., de Andrade Pereira, W. C., de Oliveira, C. M., de Castro, A. G. and de Aguiar, M. L. (2019). Weighting Factors Optimization of Predictive Torque Control of Induction Motor by Multiobjective Genetic Algorithm. IEEE Transactions on Power Electronics, 34(7), pp. 6628–6638. doi: 10.1109/TPEL.2018.2834304.10.1109/TPEL.2018.2834304 Search in Google Scholar

Gürel, A. and Zerdali, E. (2021). Metaheuristic Optimization of Predictive Torque Control for Induction Motor Control. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 11(1). doi: 10.28948/ngumuh.969734.10.28948/ngumuh.969734 Search in Google Scholar

Kouro, S., Cortes, P., Vargas, R., Ammann, U. and Rodriguez, J. (2009). Model Predictive Control—A Simple and Powerful Method to Control Power Converters. IEEE Transactions on Industrial Electronics, 56(6), pp. 1826–1838. doi: 10.1109/TIE.2008.2008349.10.1109/TIE.2008.2008349 Search in Google Scholar

Muddineni, V. P., Bonala, A. K. and Sandepudi, S. R. (2021). Grey Relational Analysis-Based Objective Function Optimization for Predictive Torque Control of Induction Machine. IEEE Transactions on Industry Applications, 57(1), pp. 835–844. doi: 10.1109/TIA.2020.3037875.10.1109/TIA.2020.3037875 Search in Google Scholar

Muddineni, V. P., Sandepudi, S. R. and Bonala, A. K. (2017). Finite Control Set Predictive Torque Control for Induction Motor Drive with Simplified Weighting Factor Selection Using TOPSIS Method. IET Electric Power Applications, 11(5), pp. 749–760. doi: 10.1049/iet-epa.2016.0503.10.1049/iet-epa.2016.0503 Search in Google Scholar

Nemec, M., Nedeljković, D. and Ambrožič, V. (2007). Predictive Torque Control of Induction Machines using Immediate Flux Control. IEEE Transactions on Industrial Electronics, 54(4), pp. 2009–2017. doi: 10.1109/TIE.2007.895133.10.1109/TIE.2007.895133 Search in Google Scholar

Rodriguez, J., Kennel, R. M., Espinoza, J. R., Trincado, M., Silva, C. A. and Rojas, C. A. (2012). High-Performance Control Strategies for Electrical Drives: An Experimental Assessment. IEEE Transactions on Industrial Electronics, 59(2), pp. 812–820. doi: 10.1109/TIE.2011.2158778.10.1109/TIE.2011.2158778 Search in Google Scholar

Rodriguez, J., Kazmierkowski, M. P., Espinoza, J. R., Zanchetta, P., Abu-Rub, H., Young, H. A. and Rojas, C. A. (2013). State of the Art of Finite Control Set Model Predictive Control in Power Electronics. IEEE Transactions on Industrial Informatics, 9(2), pp. 1003–1016. doi: 10.1109/TII.2012.2221469.10.1109/TII.2012.2221469 Search in Google Scholar

Rojas, C. A., Rodriguez, J., Villarroel, F., Espinoza, J. R., Silva, C. A. and Trincado, M. (2013). Predictive Torque and Flux Control Without Weighting Factors. IEEE Transactions on Industrial Electronics, 60(2), pp. 681–690. doi: 10.1109/TIE.2012.2206344.10.1109/TIE.2012.2206344 Search in Google Scholar

Rojas, C. A., Rodriguez, J. R., Kouro, S. and Villarroel, F. (2017). Multiobjective Fuzzy-Decision-Making Predictive Torque Control for an Induction Motor Drive. IEEE Transactions on Power Electronics, 32(8), pp. 6245–6260. doi: 10.1109/TPEL.2016.2619378.10.1109/TPEL.2016.2619378 Search in Google Scholar

Stando, D. and Kazmierkowski, M. P. (2020). Simple Technique of Initial Speed Identification for Speed-Sensorless Predictive Controlled Induction Motor Drive. Power Electronics and Drives, 5(1), pp. 189–198. doi: 10.2478/pead-2020-0014.10.2478/pead-2020-0014 Search in Google Scholar

Wang, F., Li, S., Mei, X., Xie, W., Rodriguez, J. and Kennel, R. M. (2015). Model-based Predictive Direct Control Strategies for Electrical Drives: An Experimental Evaluation of PTC and PCC Methods. IEEE Transactions on Industrial Informatics, 11(3), pp. 671–681. doi: 10.1109/TII.2015.2423154.10.1109/TII.2015.2423154 Search in Google Scholar

Wang, F., Zhang, Z., Mei, X., Rodriguez, J. and Kennel, R. (2018). Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control. Energies, 11(1), pp. 120. doi: 10.3390/en11010120.10.3390/en11010120 Search in Google Scholar

Wang, F., Xie, H., Chen, Q., Davari, S. A., Rodriguez, J. and Kennel, R. (2020). Parallel Predictive Torque Control for Induction Machines Without Weighting Factors. IEEE Transactions on Power Electronics, 35(2), pp. 1779–1788. doi: 10.1109/TPEL.2019.2922312.10.1109/TPEL.2019.2922312 Search in Google Scholar

Zerdali, E. and Barut, M. (2017). The Comparisons of Optimized Extended Kalman Filters for Speed-Sensorless Control of Induction Motors. IEEE Transactions on Industrial Electronics, 64(6), pp. 4340–4351. doi: 10.1109/TIE.2017.2674579.10.1109/TIE.2017.2674579 Search in Google Scholar

Zhang, Y. and Yang, H. (2015). Model-Predictive Flux Control of Induction Motor Drives With Switching Instant Optimization. IEEE Transactions on Energy Conversion, 30(3), pp. 1113–1122. doi: 10.1109/TEC.2015.2423692.10.1109/TEC.2015.2423692 Search in Google Scholar

eISSN:
2543-4292
Lingua:
Inglese
Frequenza di pubblicazione:
Volume Open
Argomenti della rivista:
Computer Sciences, Artificial Intelligence, Engineering, Electrical Engineering, Electronics