Three-objective antenna optimization by means of kriging surrogates and domain segmentation - Publication - Bridge of Knowledge

Your account

login

Search

Three-objective antenna optimization by means of kriging surrogates and domain segmentation

Abstract

In this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples required for surrogate model identification. The generalized segmentation technique works for any number of design objectives. Here, it is demonstrated using a three-objective case study of a UWB monopole optimized for best in-band reflection, minimum gain variability, and minimum size. The numerical results indicate that segmentation leads to reducing the cost of initial Pareto identification by around 21 percent as compared to the conventional surrogate-assisted approach.

Citations

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Authors (2)

Cite as

Full text

download paper
downloaded 9 times
Publication version
Accepted or Published Version
License
Copyright (2018 Warsaw Univ. of Technology, IEEE)

Keywords

Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
2018 22nd International Microwave and Radar Conference (MIKON) strony 348 - 351
Language:
English
Publication year:
2018
Bibliographic description:
Kozieł S., Bekasiewicz A.: Three-objective antenna optimization by means of kriging surrogates and domain segmentation// 2018 22nd International Microwave and Radar Conference (MIKON)/ : , 2018, s.348-351
DOI:
Digital Object Identifier (open in new tab) 10.23919/mikon.2018.8405222
Bibliography: test
  1. S. Nikolaou and M. A. B. Abbasi, -Design and development of a compact UWB monopole antenna with easily-controllable return loss,‖ IEEE Trans. Ant. Propag., vol. 65, no. 4, pp 2063-2067, 2017. open in new tab
  2. J. Liu, K.P. Esselle, S.G. Hay, and S. Zhong, -Effects of printed UWB antenna miniaturization on pulse fidelity and pattern stability,‖ IEEE Trans. Ant. Prop., vol. 62, no. 8, pp 3903-3910, 2014. open in new tab
  3. A. Bekasiewicz and S. Koziel, -Structure and computationally- efficient simulation-driven design of compact UWB monopole antenna,‖ IEEE Antennas and Wirel. Propag. Lett., vol. 14, pp. 1282- 1285, 2015. open in new tab
  4. M.A. Haq and S. Koziel, -A novel miniaturized uwb monopole with five-section stepped-impedance feed line,‖ Microwave Opt. Tech. Lett., 2017.
  5. L. Li, S.W. Cheung, and T.I. Yuk, -Compact MIMO antenna for portable devices in UWB applications,‖ IEEE Trans. Antennas Prop., vol. 61, no. 8, pp. 4257-4264, 2013. open in new tab
  6. M. N. Shakib, M. Moghavvemi, and W. N. L. Mahadi, -Design of a compact planar antenna for ultra-wideband operation,‖ Applied Computational Electromagnetics Society Journal, vol. 20, no. 2, pp 222- 229, 2015. open in new tab
  7. M. Manohar, R. S. Kshetrimayum, and A. K. Gogoi, -Printed monopole antenna with tapered feed line, feed region and patch for super wideband applications,‖ IET Microw. Antennas propag., vol. 8, Iss. 1, pp 39-45, 2014. open in new tab
  8. B. Tian, Z. Li, C. Wang, -Boresight gain optimization of an UWB monopole antenna using FDTD and genetic algorithm,‖ IEEE Int. Conf. Ultra-Wideband, pp. 1-4, 2010. open in new tab
  9. J. Nocedal, S.J. Wright, Numerical Optimization, Springer, 2006. open in new tab
  10. X.-S. Yang, K.-T. Ng, S.H. Yeung, and K.F. Man, -Jumping genes multiobjective optimization scheme for planar monopole ultrawideband antenna,‖ IEEE Trans. Antennas Prop., vol. 56, no. 12, pp. 3659-3666, 2008. open in new tab
  11. D. Ding and G. Wang, -Modified multiobjective evolutionary algorithm based on decomposition for antenna design,‖ IEEE Trans. Antennas Prop., vol. 61, no. 10, pp. 5301-5307, Oct. 2013. open in new tab
  12. S. Chamaani, S.A. Mirtaheri, and M.S. Abrishamian, -Improvement of time and frequency domain performance of antipodal Vivaldi antenna using multi-objective particle swarm optimization,‖ IEEE Trans. Antennas Prop., vol. 59, no. 5 pp. 1738-1742, May 2011. open in new tab
  13. M. Ghassemi, M. Bakr, and N. Sangary, -Antenna design exploiting adjoint sensitivity-based geometry evolution,‖ IET Microwaves Ant. Prop., vol. 7, no. 4, pp. 268-276, 2013. open in new tab
  14. S. Koziel, and S. Ogurtsov, Antenna design by simulation-driven optimization, Springer, New York, 2014. open in new tab
  15. N.V. Queipo, R.T. Haftka, W. Shyy, T. Goel, R. Vaidynathan, and P.K. Tucker, -Surrogate-based analysis and optimization,‖ Prog. Aerospace Sci., vol. 41, no. 1, pp. 1-28, Jan. 2005. open in new tab
  16. K. Deb., Multi-objective optimization using evolutionary algorithms, New York: John Wiley & Sons, 2001. open in new tab
  17. S. Koziel and S. Ogurtsov, -Multi-objective design of antennas using variable-fidelity simulations and surrogate models,‖ IEEE Trans. Antennas Prop., vol. 61, no. 12, pp. 5931-5939, Dec. 2013. open in new tab
  18. S. Koziel, and A. Bekasiewicz, -Low-cost multi-objective optimization and experimental validation of UWB MIMO antenna,‖ Eng. Comp., vol. 33, no. 4, pp. 1246-1268, 2016. open in new tab
  19. S. Koziel and A. Bekasiewicz, -Computationally efficient two-objective optimization of compact microwave couplers through corrected domain patching,‖ Metrology and Measurement Systems, 2017. open in new tab
  20. S. Koziel, A. Bekasiewicz, Q.S. Cheng, and S. Li, -Accelerated multi- objective design optimization of antennas by surrogate modeling and domain segmentation,‖ IEEE European Ant. Prop. Conf., 2017. open in new tab
  21. M.A. Haq, S. Koziel, and Q.S. Cheng, -EM-driven size reduction of UWB antennas with ground plane modifications,‖ Int. Applied Computational Electromagnetics Society (ACES China) Symposium, 2017.
  22. CST Microwave Studio, ver. 2016. CST AG, Bad Nauheimer Str. 19, D- 64289 Darmstadt, Germany, 2016. open in new tab
Verified by:
Gdańsk University of Technology

seen 62 times

Recommended for you

Multi-objective design optimization of antennas for reflection, size, and gain variability using kriging surrogates and generalized domain segmentation

2018

Accelerated multi-objective design optimization of antennas by surrogate modeling and domain segmentation

2017

Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation

2020

Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas

2018
Meta Tags