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Parameter identification of bidirectional IPT system using chaotic asexual reproduction optimization

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Abstract

Bidirectional inductive power transfer (IPT) system facilitates contactless power transfer between two sides and across an air gap, through weak magnetic coupling. Typically, this system constitutes a high-order resonant circuit and, as such, is difficult to design and control. In this study, a novel technique for parameter identification of bidirectional IPT system is presented by using chaotic asexual reproduction optimization (CARO). The asexual reproduction optimization (ARO) is a novel kind of evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. The CARO employs chaotic sequence to enhance ARO’s global searching ability. The parameter identification of a bidirectional IPT system is posed as an optimization process with an objective function minimizing the errors between the estimated and measured value. The implementation of the CARO-based parameter identification technique is analyzed in detail. Simulations are used to test the robustness and generalization ability of the proposed technique.

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References

  1. Wang, C.S., Steilau, O.H., Covic, G.A.: Design considerations for a contactless electric vehicle battery charger. IEEE Trans. Ind. Electron. 52, 1308–1314 (2005)

    Article  Google Scholar 

  2. Madawala, U.K., Thrimawithana, D.J., Kularatna, N.: An ICPT-supercapacitor based hybrid system for surge free power transfer. IEEE Trans. Ind. Electron. 54, 3287–3297 (2007)

    Article  Google Scholar 

  3. Kim, Y.H., Jin, K.H.: A contactless power transfer system using a series-series-parallel resonant converter. Int. J. Electron. 99, 885–897 (2012)

    Article  Google Scholar 

  4. Madawala, U.K., Thrimawithana, D.J.: A bidirectional inductive power interface for electric vehicles in V2G systems. IEEE Trans. Ind. Electron. 58, 4789–4796 (2011)

  5. Swain, A.K., Neath, M.J., Madawala, U.K., Thrimawithana, D.J.: A dynamic multivariable state-space model for bidirectional inductive power transfer systems. IEEE Trans. Power Electron. 27, 4772–4780 (2012)

    Article  Google Scholar 

  6. Zang, H., Zhang, S., Hapeshi, K.: A review of nature-inspired algorithms. J. Bionic Eng. 7, S232–S237 (2010)

    Article  Google Scholar 

  7. Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evolut. Comput. 1, 53–66 (1997)

    Article  Google Scholar 

  8. Chandra Mohan, B., Baskaran, R.: A survey: ant colony optimization based recent research and implementation on several engineering domain. Expert Syst. Appl. 39, 4618–4627 (2012)

    Article  Google Scholar 

  9. Zhang, C., Ouyang, D., Ning, J.: An artificial bee colony approach for clustering. Expert Syst. Appl. 37, 4761–4767 (2010)

    Article  Google Scholar 

  10. Karaboga, D., Basturk, B.: On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 8, 687–697 (2008)

    Article  Google Scholar 

  11. Xu, Z.D., Guo, Y.F., Wang, S.A., Huang, X.H.: Optimization analysis on parameters of multi-dimensional earthquake isolation and mitigation device based on genetic algorithm. Nonlinear Dyn. 72, 757–765 (2013)

    Article  Google Scholar 

  12. Mokeddem, D., Khellaf, A.: Optimal feeding profile for a fuzzy logic controller in a bioreactors using genetic algorithm. Nonlinear Dyn. 67, 2835–2845 (2012)

    Article  MathSciNet  Google Scholar 

  13. Gandomi, A.H., Yang, X.S., Alavi, A.H.: Mixed variable structural optimization using Firefly Algorithm. Comput. Struct. 89, 2325–2336 (2011)

    Article  Google Scholar 

  14. Yuan, X.F., Dai, X.S., Zhao, J.Y., He, Q.: On a novel multi-swarm fruit fly optimization algorithm and its application. Appl. Math. Comput. 233, 260–271 (2014)

    Article  MathSciNet  Google Scholar 

  15. Farasat, A., Menhaj, M.B., Mansouri, T., Moghadam, M.R.S.: ARO: a new model-free optimization algorithm inspired from asexual reproduction. Appl. Soft Comput. 10, 1284–1292 (2010)

    Article  Google Scholar 

  16. Mansouri, T., Farasat, A., Menhaj, M.B., Moghadam, M.R.S.: ARO: s new model free optimization algorithm for real time applications inspired by the asexual reproduction. Expert Syst. Appl. 38, 4866–4874 (2011)

    Article  Google Scholar 

  17. Khanteymoori, A.R., Menhaj, M.B., Homayounpour, M.M.: Structure learning in Bayesian networks using asexual reproduction optimization. ETRI J. 33, 39–49 (2011)

    Article  Google Scholar 

  18. Asl, A.N., Menhaj, M.B., Sajedin, A.: Control of leader-follower formation and path planning of mobile robots using Asexual Reproduction Optimization (ARO). Appl. Soft Comput. 14, 563–576 (2014)

    Article  Google Scholar 

  19. Yuan, X.F., Yang, Y.M., Wang, H.: Improved parallel chaos optimization algorithm. Appl. Math. Comput. 219, 3590–3599 (2012)

    Article  MathSciNet  Google Scholar 

  20. Acharjee, P., Goswami, S.K.: Chaotic particle swarm optimization based robust load flow. Int. J. Electr. Power Energ. Syst. 32, 141–146 (2010)

    Article  Google Scholar 

  21. Gao, Z., Liao, X.Z.: Rational approximation for fractional-order system by particle swarm optimization. Nonlinear Dyn. 67, 1387–1395 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  22. Ma, Z.S.: Chaotic populations in genetic algorithms. Appl. Soft Comput. 12, 2409–2424 (2012)

    Article  Google Scholar 

  23. Wei, Z., Ge, F.Z., Lu, Y., Li, L.X., Yang, Y.X.: Chaotic ant swarm for the traveling salesman problem. Nonlinear Dyn. 65, 271–281 (2011)

  24. Li, Y., Wen, Q., Zhang, B.: Chaotic ant swarm optimization with passive congregation. Nonlinear Dyn. 68, 129–136 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  25. Chahkandi, V., Yaghoobi, M., Veisi, G.: CABC-CSA: a new chaotic hybrid algorithm for solving optimization problems. Nonlinear Dyn. 73, 475–484 (2013)

    Article  MathSciNet  Google Scholar 

  26. Alatas, B.: Chaotic harmony search algorithms. Appl. Math. Comput. 216, 2687–2699 (2010)

    Article  MATH  Google Scholar 

  27. Baykasoglu, A.: Design optimization with chaos embedded great deluge algorithm. Appl. Soft Comput. 12, 1055–1067 (2012)

    Article  Google Scholar 

  28. Willcox, S., Moltschaniwskyj, N.A., Crawford, C.: Asexual reproduction in scyphistomae of Aurelia sp.: Effects of temperature and salinity in an experimental study. J. Exp. Mar. Biol. Ecol. 353, 107–114 (2007)

    Article  Google Scholar 

  29. Martinez, V.G., Menger, G.J., Zoran, M.J.: Regeneration and asexual reproduction share common molecular changes: upregulation of a neural glycoepitope during morphallaxis in Lumbriculus. Mech. Dev. 122, 721–732 (2005)

    Article  Google Scholar 

  30. Yuan, X.F., Li, S.T., Wang, Y.N., Sun, W., Wu, L.H.: Parameter identification of electronic throttle using a novel hybrid optimization algorithm. Nonlinear Dyn. 63, 549–557 (2011)

    Article  Google Scholar 

  31. Yang, D.X., Liu, Z.J., Zhou, J.L.: Chaos optimization algorithms based on chaotic maps with different probability distribution and search speed for global optimization. Comm. Nonlinear Sci. Numer. Simulat. 19, 1229–1246 (2014)

    Article  MathSciNet  Google Scholar 

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant No. 61104088; and Young Teachers Promotion Program of Hunan University.

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Correspondence to Xiaofang Yuan.

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Yuan, X., Xiang, Y., Wang, Y. et al. Parameter identification of bidirectional IPT system using chaotic asexual reproduction optimization. Nonlinear Dyn 78, 2113–2127 (2014). https://doi.org/10.1007/s11071-014-1585-9

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  • DOI: https://doi.org/10.1007/s11071-014-1585-9

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