volume | PIER Journals

Abstract

A method based on adaptive-network-based fuzzy inference system (ANFIS) is presented for the analysis of conductor-backed asymmetric coplanar waveguides (CPWs). Four optimization algorithms, hybrid learning, simulated annealing, genetic, and least-squares, are used to determine optimally the design parameters of the ANFIS. The results of ANFIS models are compared with the results of conformal mapping technique, a commercial electromagnetic simulator IE3D, and the experimental works realized in this study. There is very good agreement among the results of ANFIS models, quasi-static method, IE3D, and experimental works. The proposed ANFIS models are not only valid for conductor-backed asymmetric CPWs but also valid for conductor-backed symmetric CPWs.

1. Simons, R. N., Coplanar Waveguide Circuits, Components and Systems, John Wiley and Sons, 2001.
doi:10.1002/0471224758

2. Ghione, G. and C. U. Naldi, "Coplanar waveguides for MMIC applications: Effect of upper shielding, conductor backing, finite-extent ground planes, and line-to-line coupling," IEEE Transactions on Microwave Theory and Techniques,, Vol. 35, No. 3, 260-267, 1987.
doi:10.1109/TMTT.1987.1133637 Google Scholar

3. Shih, Y. C., "Broadband characterization of conductor-backed coplanar waveguide using accurate on-wafer measurement techniques," Microwave Journal, Vol. 34, No. 4, 95-105, 1991. Google Scholar

4. Fang, S. J. and B. S. Wang, "Analysis of asymmetric coplanar waveguide with conductor backing," IEEE Transactions on Microwave Theory and Techniques, Vol. 47, No. 2, 238-240, 1999.
doi:10.1109/22.744300 Google Scholar

5. Karpuz, C. and A. Gorur, "Effect of upper shielding and conductor backing on quasi static parameters of asymmetric coplanar waveguides," Int. J. RF and Microwave CAE, Vol. 9, 394-402, 1999. Google Scholar

6. Ghione, G. and C. U. Naldi, "Parameters of coplanar waveguides with lower ground plane," Electronic Letters, Vol. 19, No. 18, 734-735, 1983.
doi:10.1049/el:19830500 Google Scholar

7. Cheng, K. K. M. and J. K. A. Everard, "A new technique for the quasi-TEM analysis of conductor-backed coplanar waveguide structures," IEEE Transactions on Microwave Theory and Techniques, Vol. 41, No. 9, 1589-1592, 1993.
doi:10.1109/22.245682 Google Scholar

8. Shih, Y. C. and T. Itoh, "Analysis of conductor-backed coplanar waveguide," Electronic Letters, Vol. 18, No. 12, 538-540, 1982.
doi:10.1049/el:19820365 Google Scholar

9. Neto, A. G., C. S. D. Rocha, D. Bajon, and H. Baudrand, "Analysis of the conductor-backed coplanar waveguide by an alternative formulation of the transverse resonance technique," SBMO/IEEE MTT-S Int., 851-855, 1995.
doi:10.1109/SBMOMO.1995.509726 Google Scholar

10. Hotta, M., Y. Qian, and T. Itoh, "Efficient FDTD analysis of conductor-backed CPW's with reduced leakage loss," IEEE Transactions on Microwave Theory and Techniques, Vol. 47, No. 8, 1585-1587, 1999.
doi:10.1109/22.780412 Google Scholar

11. Yildiz, C., K. Guney, M. Turkmen, and S. Kaya, "Analysis of conductor-backed coplanar waveguides using adaptive-network-based fuzzy inference system models," Microwave and Optical Technology Letters, Vol. 51, No. 2, 439-455, 2009.
doi:10.1002/mop.24059 Google Scholar

12. Jang, J.-S. R., "ANFIS: Adaptive-network-based fuzzy inference system," IEEE Transactions on Systems Man and Cybernetics, Vol. 23, No. 3, 665-685, 1993.
doi:10.1109/21.256541 Google Scholar

13. Jang, J.-S. R., C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice-Hall, 1997.

14. Ozer, S., K. Guney, and A. Kaplan, "Calculation of the characteristic impedance and effective dielectric constant of coplanar waveguide with the use of fuzzy inference systems," Proc. of 8th TAINN'99, Istanbul, Turkey, 187-196, 1999. Google Scholar

15. Tayarani , M. and Y. Kami, "Qualitative analysis in engineering electromagnetics: An application to general transmission lines," IEICE Trans. on Electronics, Vol. E84C, No. 3, 364-375, 2001. Google Scholar

16. Miraftab, V. and R. R. Mansour, "Computer-aided tuning of microwave filters using fuzzy logic," IEEE MTT-S Digest, 1117-1120, 2002. Google Scholar

17. Ubeyli, E. D. and I. Guler, "Adaptive neuro-fuzzy inference system to compute quasi-TEM characteristic parameters of microshield lines with practical cavity sidewall profiles," Neurocomputing, Vol. 70, No. 1--3, 196-204, 2006. Google Scholar

18. Rahouyi, E. B., J. Hinojosa, and J. Garrigos, "Neurofuzzy modeling techniques for microwave components," IEEE Microwave and Wireless Components Letters, Vol. 16, No. 2, 72-74, 2006.
doi:10.1109/LMWC.2005.863245 Google Scholar

19. Miraftab, V. and R. R. Mansour, "EM-based microwave circuit design using fuzzy logic techniques," IEE Proc. Microwave Antennas Propag., Vol. 153, No. 6, 495-501, 2006.
doi:10.1049/ip-map:20050190 Google Scholar

20. Hinojosa, J. and G. Dome'nech-Asensi, "Space-mapped neuro-fuzzy optimization for microwave device modeling," Microwave and Optical Technology Letters, Vol. 49, No. 6, 1328-1334, 2007.
doi:10.1002/mop.22460 Google Scholar

21. Hinojosa, J., G. Dome'nech-Asensi, and J. Martı'nez-Alajarı'n, "Development of VHDL-AMS neuro-fuzzy behavioral models for RF/microwave passive components," Int. J. RF and Microwav CAE, Vol. 17, No. 3, 335-344, 2007.
doi:10.1002/mmce.20228 Google Scholar

22. Koziel, S. and J. W. Bandler, "A space-mapping approach to microwave device modeling exploiting fuzzy systems," IEEE Transactions on Microwave Theory and Techniques, Vol. 55, No. 12, 2539-2547, 2007.
doi:10.1109/TMTT.2007.909605 Google Scholar

23. Yildiz, C., K. Guney, M. Turkmen, and S. Kaya, "Adaptive neuro-fuzzy models for the quasi-static analysis of microstrip line," Microwave and Optical Technology Letters, Vol. 50, No. 5, 1191-1196, 2008.
doi:10.1002/mop.23322 Google Scholar

24. Turkmen, M., S. Kaya, C. Yildiz, and K. Guney, "Adaptive neurofuzzy models for conventional coplanar waveguides," Progress In Electromagnetics Research B, Vol. 6, 93-107, 2008.
doi:10.2528/PIERB08031208 Google Scholar

25. Gaoua, S., L. Ji, Z. Cheng, F. A. Mohammadi, and M. C. E. Yagoub, "Fuzzy neural-based approaches for e±cient RF/microwave transistor modeling," Int. J. RF and Microwave CAE, Vol. 19, No. 1, 128-139, 2009.
doi:10.1002/mmce.20323 Google Scholar

26. Kirkpatrick, S., C. D. Gelatt, Jr., and M. P. Vecchi, "Optimization by simulated annealing," Science, Vol. 220, No. 4598, 671-680, 1983.
doi:10.1126/science.220.4598.671 Google Scholar

27. Goldberg, D., Genetic Algorithms in Search, Optimization, and Machine Learning, Reading, Addison-Wesley, 1989.

28. Holland, J., Adaptation in Natural and Artificial Systems, University of Michigan Press, 1975.

29. Dennis, J. E., Nonlinear Least-Squares, State of the Art in Numerical Analysis, 269-312, Academic Press, 1977.

30. Marquardt, D. W., "An algorithm for least-squares estimation of nonlinear parameters," J. Soc. Ind. Appl. Math., Vol. 11, 431-441, 1963.
doi:10.1137/0111030 Google Scholar

31. Zeland Software Inc., IE3D, , Version 12.12, www.zeland.com., 2007.

Prof. Mustafa Turkmen

Dr. Celal Yildiz

Professor Kerim Guney

Dr. Sabri Kaya