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Parameters Estimation for Sensorless Control of Induction Motor Drive Using Modify GA and CSA Algorithm

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AETA 2018 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application (AETA 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 554))

Abstract

This paper presents methods for estimating CB-MRAS model parameters such as K1(CB), K2(CB), K3(CB), Ti(CB), KLm, KTr by binary Genetic Algorithm (GA), real number GA, modify GA, and CucKoo Search Algorithm (CSA). The first part of the paper is the vector model of the induction motor and the CB-MRAS model for estimating parameters by the above algorithms; the second part is the detailed way to implement the algorithms; the third part is simulation and as a result of the simulation, the results show that it is possible to estimate the parameters of this model by the modify GA or CSA algorithm.

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References

  1. Haupt, R.L., Haupt, S.E.: Practical Genetic Algorithms, 2nd edn. A Wiley-Interscience, New York (2004)

    MATH  Google Scholar 

  2. Brandstetter, P., Dobrovsky, M., Kuchar, M.: Implementation of genetic algorithm in control structure of induction motor A.C. drive. In: Advances in Electrical and Computer Engineering, vol. 14, no. 4 (2014)

    Google Scholar 

  3. Thao, N.T.P., Thang, N.T.: Environmental economic load dispatch with quadratic fuel cost function using CucKoo search algorithm. Int. J. u-and e-Serv. Sci. Technol. 7(2), 199–210 (2014)

    Article  Google Scholar 

  4. Datta, M., Rafiq, M.A., Ghosh, B.C.: Genetic algorithm based fast speed response induction motor drive without speed encoder. In: POWERENG 2007, Setubal, Portugal (2007)

    Google Scholar 

  5. Brandstetter, P.: Sensorless control of induction motor using modified MRAS. Int. Rev. Electr. Eng. IREE 7(3), 4404–4411 (2012)

    Google Scholar 

  6. Saghafinia, A., Ping, H.W., Rahman, M.A.: High performance induction motor drive using hybrid fuzzy-PI and PI controllers: a review. Int. Rev. Electr. Eng. IREE 5(5), 2000–2012 (2010)

    Google Scholar 

  7. Girovsky, P., Timko, J., Zilkova, J.: Shaft sensor-less FOC control of an induction motor using neural estimators. Acta Polytechnica Hungarica 9(4), 31–45 (2012)

    Google Scholar 

  8. Rajasekhar, A., Abraham, A., Jatoth, R.K.: Controller tuning using a Cauchy mutated artificial bee colony algorithm. In: Advances in Intelligent and Soft Computing, vol. 87, pp. 11–18. Springer, Berlin (2011)

    Google Scholar 

  9. Tran, T.C., Brandstetter, P., Duy, V.H., Dong, C., Tran, C.D., Ho, S.D.: Estimate parameters of induction motor using ANN and GA algorithm. In: AETA: Recent Advances in Electrical Engineering and Related Sciences (2017)

    Google Scholar 

  10. Yang, X.-S., Deb, S.: CucKoo search via Lévy flights. In: Proceedings of World Congress on Nature & Biologically Inspired Computing (NaBic 2009), India, pp. 210–214 (2009)

    Google Scholar 

  11. Ben Regaya, C., Zaafouri, A., Chaari, A.: Electric drive control with rotor resistance and rotor speed observers based on fuzzy logic. Math. Prob. Eng. 2014, 9 (2014)

    Article  Google Scholar 

  12. Megherbi, A.C., Megherbi, H., Benmahamed, K., Aissaoui, A.G., Tahour, A.: Parameter identification of induction motors using variable-weighted cost function of genetic algorithms. J. Electr. Eng. Technol. 5(4), 597–605 (2010)

    Article  Google Scholar 

  13. Timer, J., Adžic, E., Porobic, V., Marcetic, D.: Influence of rotor time constant error on IFOC control structure. Electronics 13(1) (2009)

    Google Scholar 

  14. Eissa, M.M., Virk, G.S., AbdelGhany, A.M., Ghith, E.S.: Optimum induction motor speed control technique using genetic algorithm. Am. J. Intell. Syst. 3(1), 1–12 (2013)

    Google Scholar 

  15. Chacko, S., Bhende, C.N., Jain, S., Nema, R.K.: Rotor resistance estimation of vector controlled induction motor drive using GA/PSO tuned fuzzy controller. Int. J. Electr. Eng. Inf. 8(1), 218 (2016)

    Google Scholar 

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Acknowledgement

This paper was supported by the projects: Centre for Intelligent Drives and Advance Machine control (CIDAM) project, Reg. No. TE02000103 funded by the Technology Agency of the Czech Republic and Project Reg. No. SP2018/162 funded by the Student Grant Competition of VSB – Technical University of Ostrava.

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Authors and Affiliations

  1. Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, 19 Nguyen Huu Tho Street, Tan Phong Ward, District 7, Ho Chi Minh City, Vietnam

    Thinh Cong Tran, Cuong Dinh Tran, Sang Dang Ho & Pham Nhat Phuong

  2. Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15/2172, 708 33, Ostrava-Poruba, Czech Republic

    Thinh Cong Tran, Pavel Brandstetter, Cuong Dinh Tran, Sang Dang Ho, Minh Chau Huu Nguyen & Pham Nhat Phuong

Authors
  1. Thinh Cong Tran
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  2. Pavel Brandstetter
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  3. Cuong Dinh Tran
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  4. Sang Dang Ho
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  5. Minh Chau Huu Nguyen
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  6. Pham Nhat Phuong
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Corresponding author

Correspondence to Thinh Cong Tran .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Faculty of Electrical Engineering, VŠB-TUO, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

  2. Department of Electronics, Faculty of Electrical Engineering, VŠB-TUO, Ostrava, Czech Republic

    Pavel Brandstetter

  3. International Cooperation, Research and Training Institute, Ton Duc Thang University, Ho Chi Minh, Vietnam

    Tran Trong Dao

  4. Department of Automatic Control, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Vo Hoang Duy

  5. Department of Mechanical Design Engineering, Pukyong National University, Busan, Korea (Republic of)

    Sang Bong Kim

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Tran, T.C., Brandstetter, P., Tran, C.D., Ho, S.D., Nguyen, M.C.H., Phuong, P.N. (2020). Parameters Estimation for Sensorless Control of Induction Motor Drive Using Modify GA and CSA Algorithm. In: Zelinka, I., Brandstetter, P., Trong Dao, T., Hoang Duy, V., Kim, S. (eds) AETA 2018 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2018. Lecture Notes in Electrical Engineering, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-030-14907-9_57

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  • DOI: https://doi.org/10.1007/978-3-030-14907-9_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14906-2

  • Online ISBN: 978-3-030-14907-9

  • eBook Packages: EngineeringEngineering (R0)

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