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

  • Thinh Cong TranEmail author
  • Pavel Brandstetter
  • Cuong Dinh Tran
  • Sang Dang Ho
  • Minh Chau Huu Nguyen
  • Pham Nhat Phuong
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 554)


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.


A.C. drive Induction motor Vector control Modify Genetic Algorithm Estimating parameters Model CSA Optimization 



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.


  1. 1.
    Haupt, R.L., Haupt, S.E.: Practical Genetic Algorithms, 2nd edn. A Wiley-Interscience, New York (2004)zbMATHGoogle Scholar
  2. 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. 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)CrossRefGoogle Scholar
  4. 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. 5.
    Brandstetter, P.: Sensorless control of induction motor using modified MRAS. Int. Rev. Electr. Eng. IREE 7(3), 4404–4411 (2012)Google Scholar
  6. 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. 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. 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. 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. 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. 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)CrossRefGoogle Scholar
  12. 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)CrossRefGoogle Scholar
  13. 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. 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. 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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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Thinh Cong Tran
    • 1
    • 2
    Email author
  • Pavel Brandstetter
    • 2
  • Cuong Dinh Tran
    • 1
    • 2
  • Sang Dang Ho
    • 1
    • 2
  • Minh Chau Huu Nguyen
    • 2
  • Pham Nhat Phuong
    • 1
    • 2
  1. 1.Faculty of Electrical and Electronics EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam
  2. 2.Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of OstravaOstrava-PorubaCzech Republic

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