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Predictive control of induction motors using cascaded artificial neural network

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Abstract

In recent years, Model Predictive Torque Control (MPTC) has gained popularity as a powerful method of controlling Induction Motors (IMs). There are, however, some factors such as the weighted coefficient that must be taken into account to attain satisfactory performance at different operation points for stator flux. As of now, an empirical procedure has been used for tuning the weighting factor in MPTC, which is not as effective. Model Predictive Flux Control (MPFC) is proposed in this paper, which eliminates complicated process of predicting the stator current by using the flux vectors as control variables. In order to get over these obstacles, a novel Model Predictive Control (MPC) method utilizing a Cascaded Artificial Neural Network (ANN) is proposed in this research. As a result, the control complexity is diminished and weighting factor in standard MPTC is eliminated. In-depth evaluations and comparisons of MPTC and MPFC are conducted, covering low-speed function, dynamic response, and steady-state performance. In contract to traditional approaches, the preferred method has much lower computational cost, virtuous dynamic response, and superior steady-state performance. The overall proposed work is simulated using MATLAB/SIMULINK platform and experimental tests performed on 3Φ VSI fed IM drives are used to verify the efficacy of proposed approach.

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References

  1. Gonzalez-Prieto I, Zoric I, Duran MJ, Levi E (2019) Constrained model predictive control in nine-phase induction motor drives. IEEE Trans Energy Convers 34(4):1881–1889

    Article  Google Scholar 

  2. Wang F, Zhang Z, Mei X, Rodríguez J, Kennel R (2018) Advanced control strategies of induction machine: field oriented control, direct torque control and model predictive control. Energies 11(1):120

    Article  Google Scholar 

  3. Dan H, Zeng P, Xiong W, Wen M, Su M, Rivera M (2021) Model predictive control-based direct torque control for matrix converter-fed induction motor with reduced torque ripple. CES Trans. Electr. Mach. Syst. 5(2):90–99

    Article  Google Scholar 

  4. Wróbel K, Serkies P, Szabat K (2020) Model predictive base direct speed control of induction motor drive—continuous and finite set approaches. Energies 13(5):1193

    Article  Google Scholar 

  5. Zhang Y, Xia B, Yang H (2017) Performance evaluation of an improved model predictive control with field oriented control as a benchmark. IET Electr Power Appl 11(5):677–687

    Article  Google Scholar 

  6. Wang F, Mei X, Tao P, Kennel R, Rodriguez J (2017) Predictive field-oriented control for electric drives. Chin. J. Electr. Eng. 3(1):73–78

    Article  Google Scholar 

  7. Yan Y, Wang S, Xia C, Wang H, Shi T (2016) Hybrid control set-model predictive control for field-oriented control of VSI-PMSM. IEEE Trans Energy Convers 31(4):1622–1633

    Article  Google Scholar 

  8. Karlovsky P, Lettl J (2018) Induction motor drive direct torque control and predictive torque control comparison based on switching pattern analysis. Energies 11(7):1793

    Article  Google Scholar 

  9. Habibullah M, Lu DD, Xiao D, Rahman MF (2016) A simplified finite-state predictive direct torque control for induction motor drive. IEEE Trans Ind Electron 63(6):3964–3975

    Article  Google Scholar 

  10. Sun X, Li T, Zhu Z, Lei G, Guo Y (2021) Zhu J (2021) Speed sensorless model predictive current control based on finite position set for PMSHM drives. IEEE Trans Transp Electr 7(4):2743–2752

    Article  Google Scholar 

  11. Sun X, Li T, Yao M, Lei G, Guo Y, Zhu J (2021) Improved finite-control-set model predictive control with virtual vectors for PMSHM drives. IEEE Trans Energy Convers 37(3):1885–1894

    Google Scholar 

  12. Li T, Sun X, Lei G, Guo Y, Yang Z, Zhu J (2022) Finite-control-set model predictive control of permanent magnet synchronous motor drive systems—An overview. IEEE/CAA J Autom Sin 9(12):2087–2105

    Article  Google Scholar 

  13. Zhang Y, Xia B, Yang H, Rodriguez J (2016) Overview of model predictive control for induction motor drives. Chin J Electr Eng 2(1):62–76

    Article  Google Scholar 

  14. Garcia C, Rodriguez J, Silva C, Rojas C, Zanchetta P, Abu-Rub H (2016) Full predictive cascaded speed and current control of an induction machine. IEEE Trans Energy Convers 31(3):1059–1067

    Article  Google Scholar 

  15. Bouguenna IF, Tahour A, Kennel R, Abdelrahem M (2021) Multiple-vector model predictive control with fuzzy logic for PMSM electric drive systems. Energies 14(6):1727

    Article  Google Scholar 

  16. Wang D, Shen ZJ, Yin X, Tang S, Liu X, Zhang C, Wang J, Rodriguez J, Norambuena M (2021) Model predictive control using artificial neural network for power converters. IEEE Trans Ind Electron 69(4):3689–3699

    Article  Google Scholar 

  17. Zhang Y, Bai Y, Yang H (2017) A universal multiple-vector-based model predictive control of induction motor drives. IEEE Trans Power Electron 33(8):6957–6969

    Article  Google Scholar 

  18. Yang X, Liu G, Le VD, Le CQ (2019) A novel model-predictive direct control for induction motor drives. IEEJ Trans Electr Electron Eng 14(11):1691–1702

    Article  Google Scholar 

  19. Odhano S, Bojoi R, Formentini A, Zanchetta P, Tenconi A (2017) Direct flux and current vector control for induction motor drives using model predictive control theory. IET Electr Power Appl 11(8):1483–1491

    Article  Google Scholar 

  20. Zhang Y, Yang H, Xia B (2015) Model predictive torque control of induction motor drives with reduced torque ripple. IET Electr Power Appl 9(9):595–604

    Article  Google Scholar 

  21. Farah N, Talib MH, Ibrahim Z, Abdullah Q, Aydoğdu Ö, Rasin Z, Jidin A, Lazi JM (2020) Analysis and investigation of different advanced control strategies for high-performance induction motor drives. TELKOMNIKA (Telecommun Comput Electron Control) 18(6):3303–3314

    Article  Google Scholar 

  22. Lu Z, Zhang R, Hu L, Gan L, Lin J, Gong P (2019) Model predictive control of induction motor based on amplitude–phase motion equation. IET Power Electron 12(9):2400–2406

    Article  Google Scholar 

  23. Zhang Y, Yang H (2015) Two-vector-based model predictive torque control without weighting factors for induction motor drives. IEEE Trans Power Electron 31(2):1381–1390

    Article  Google Scholar 

  24. Abbasi MA, Husain AR, Idris NR, Anjum W, Bassi H, Rawa MJ (2020) Predictive flux control for induction motor drives with modified disturbance observer for improved transient response. IEEE Access 8:112484–112495

    Article  Google Scholar 

  25. Tamimi J (2018) Simulation of three-phase induction motor using nonlinear model predictive control technique. Cogent Eng 5(1):1516489

    Article  Google Scholar 

  26. Jin T, Song H, Mon-Nzongo DL, Ipoum-Ngome PG, Liao H, Zhu M (2022) Virtual three-level model predictive flux control with reduced computational burden and switching frequency for induction motors. IEEE Trans Power Electron 38(2):1571–1582

    Article  Google Scholar 

  27. Stando D, Kazmierkowski MP (2020) Simple technique of initial speed identification for speed-sensorless predictive controlled induction motor drive. Power Electron Drives 5(1):189–198

    Article  Google Scholar 

  28. Gao H, Wu B, Xu D, Zargari NR (2020) Two-vector based low-complexity model predictive flux control for current-source inverter-fed induction motor drive. IET Electr Power Appl 14(9):1631–1641

    Article  Google Scholar 

  29. Kazraji SM, Feyzi MR, Sharifian MB, Tohidi S (2017) Fuzzy predictive force control (FPFC) for speed sensorless control of single-side linear induction motor. Eng, Technol Appl Sci Res 7(6):2132–2138

    Article  Google Scholar 

  30. Stando D, Kazmierkowski MP (2020) Constant switching frequency predictive control scheme for three-level inverter-fed sensorless induction motor drive. Bull Pol Acad Sci Tech Sci 68(5):1057–1068

    Google Scholar 

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Funding

This study was not funded in any way by the authors.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, India

    Thanuja Penthala & Saravanan Kaliaperumal

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  1. Thanuja Penthala
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  2. Saravanan Kaliaperumal
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Contributions

Conceptualization contributed by Thanuja Penthala. Data Curation contributed by Thanuja Penthala. Methodology contributed by Saravanan Kaliaperumal & Thanuja Penthala. Project administration contributed by Saravanan Kaliaperumal. Supervision contributed by Saravanan Kaliaperumal. Validation contributed by Saravanan Kaliaperumal. Writing—original draft contributed by Thanuja Penthala. Writing—review & editing contributed by Saravanan Kaliaperumal & Thanuja Penthala.

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Correspondence to Saravanan Kaliaperumal.

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Penthala, T., Kaliaperumal, S. Predictive control of induction motors using cascaded artificial neural network. Electr Eng 106, 2985–3000 (2024). https://doi.org/10.1007/s00202-023-02122-9

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  • DOI: https://doi.org/10.1007/s00202-023-02122-9

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