Abstract
Circuit design centering is one of the most important problems concerning the optimal design of circuits. Circuit design centering seeks nominal values of designable circuit parameters that maximize the probability of satisfying the design specifications (yield function). Design centering can be performed geometrically by finding the center of the feasible region (region in the designable parameter space where the design specifications are satisfied), or by maximizing the yield function explicitly. For all cases, the high expense of circuit simulations required obstructs the design centering process, especially for microwave circuits. To overcome this, computationally cheap surrogate-based models (e.g., space mapping, response surfaces, kriging, and neural networks) can be used for approximating the response functions or the yield function itself. In this chapter the design centering problem is formulated as an optimization problem, and the estimation of the yield function through several sampling techniques is explained. The difficulties facing the design centering process, especially for microwave circuits, are discussed, and the role of surrogate-based models in overcoming these difficulties is demonstrated. Special interest is devoted to space mapping surrogates and microwave circuit design centering. Some of the important surrogate-based circuit design centering approaches are reviewed with an overview of their theoretical bases. Tutorial and practical circuit examples are given to show the effectiveness of these approaches.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdel-Malek, H.L., Bandler, J.W.: Yield optimization for arbitrary statistical distributions: part I—theory. IEEE Trans. Circuits Syst. 27, 245–253 (1980)
Abdel-Malek, H.L., Hassan, A.S.O.: The ellipsoidal technique for design centering and region approximation. IEEE Trans. Comput.-Aided Des. 10, 1006–1014 (1991)
Abdel-Malek, H.L., Hassan, A.S.O., Bakr, M.H.: Statistical circuit design with the use of a modified ellipsoidal technique. Int. J. Microw. Millimeter Waves Comput.-Aided Eng. 7, 117–129 (1997)
Abdel-Malek, H.L., Hassan, A.S.O., Bakr, M.H.: A boundary gradient search technique and its application in design centering. IEEE Trans. Comput.-Aided Des. 18(11), 1654–1661 (1999)
Abdel-Malek, H.L., Hassan, A.S.O., Soliman, E.A., Dakroury, S.A.: The ellipsoidal technique for design centering of microwave circuits exploiting space-mapping interpolating surrogates. IEEE Trans. Microw. Theory Tech. 54(10), 3731–3738 (2006)
Allen, P.E., Holberg, D.R.: CMOS Analog Circuit Design, 2nd edn. Oxford University Press, Oxford (2002)
Antreich, K.J., Graeb, H.E., Wieser, C.U.: Circuit analysis and optimization driven by worst-case distances. IEEE Trans. Comput.-Aided Des. 13, 57–71 (1994)
Bakr, M.H., Bandler, J.W., Madsen, K., Søndergaard, J.: An introduction to the space mapping technique. Optim. Eng. 2, 369–384 (2001)
Bandler, J.W., Abdel-Malek, H.L.: Optimal centering, tolerancing and yield determination via updated approximations and cuts. IEEE Trans. Circuits Syst. 25, 853–871 (1978)
Bandler, J.W., Chen, S.H.: Circuit optimization: the state of the art. IEEE Trans. Microw. Theory Tech. 36, 424–443 (1988)
Bandler, J.W., Seviora, R.E.: Computation of sensitivities for noncommensurate networks. IEEE Trans. Circuit Theory CT-18, 174–178 (1971)
Bandler, J.W., Zhang, Q.J., Song, J., Biernacki, R.M.: FAST gradient based yield optimization of nonlinear circuits. IEEE Trans. Microw. Theory Tech. 38, 1701–1710 (1990)
Bandler, J.W., Biernacki, R.M., Chen, S.H., Grobelny, P.A., Hemmers, R.H.: Space mapping technique for electromagnetic optimization. IEEE Trans. Microw. Theory Tech. 42, 2536–2544 (1994)
Bandler, J.W., Cheng, Q.S., Dakroury, S.A., Hailu, D.M., Madsen, K., Mohamed, A.S., Pedersen, F.: Space mapping interpolating surrogates for highly optimized EM-based design of microwave devices. In: IEEE MTT-S Int. Microwave Symp. Dig., Fort Worth, TX, vol. 3, pp. 1565–1568 (2004)
Bandler, J.W., Cheng, Q.S., Dakroury, S.A., Mohamed, A.S., Bakr, M.H., Madsen, K., Søndergaard, J.: Space mapping: the state of the art. IEEE Trans. Microw. Theory Tech. 52, 337–361 (2004)
Broyden, C.G.: A class of methods for solving nonlinear simultaneous equations. Math. Comput. 19, 577–593 (1965)
Cheng, Q.S., Bandler, J.W., Koziel, S., Bakr, M.H., Ogurtsov, S.: The state of the art of microwave CAD: EM-based optimization and modeling. Int. J. RF Microw. Comput.-Aided Eng. 20, 475–491 (2010)
Conn, A.R., Toint, Ph.L.: An algorithm using quadratic interpolation for unconstrained derivative free optimization. In: Di Pillo, G., Giannes, F. (eds.) Nonlinear Optimization and Applications, pp. 27–47. Plenum Publishing, New York (1996)
Conn, A.R., Scheinberg, K., Toint, Ph.L.: A derivative free optimization algorithm in practice. In: Proceedings of 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, St. Louis, MO (1998)
De Boor, C., Ron, A.: Computational aspects of polynomial interpolation in several variables. Math. Comput. 58, 705–727 (1992)
De Klerk, E.: Aspects of Semidefinite Programming: Interior-Point Algorithms and Selected Applications. Kluwer Academic, New York (2002)
Director, S.W., Hachtel, G.D., Vidigal, L.M.: Computationally efficient yield estimation procedures based on simplicial approximation. IEEE Trans. Circuits Syst. 25, 121–130 (1978)
Elias, N.J.: Acceptance sampling: an efficient accurate method for estimating and optimizing parametric yield. IEEE J. Solid-State Circuits 29, 323–327 (1994)
Fortran90 Software Repository. http://www.nag.co.uk/nagware/examples.asp
Giunta, A.A., Wojtkiewicz, S.F. Jr., Eldred, M.S.: Overview of modern design of experiments methods for computational simulations. In: Proceedings of the 41st AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV (2003). AIAA-2003-0649
Graeb, H.: Analog Design Centering and Sizing. Springer, Amsterdam (2007)
Hassan, A.S.O.: Normed distances and their applications in optimal circuit design. Optim. Eng. 4, 197–213 (2003)
Hassan, A.S.O.: Design centering and region approximation via primal-dual interior-point technique. J. Eng. Appl. Sci. 51(2), 195–212 (2004)
Hassan, A.S.O., Rabie, A.A.: Design centering using parallel-cuts ellipsoidal technique. J. Eng. Appl. Sci. 47, 221–239 (2000)
Hassan, A.S.O., Abdel-Malek, H.L., Rabie, A.A.: Design centering and polyhedral region approximation via parallel-cuts ellipsoidal technique. Eng. Optim. 36(1), 37–49 (2004)
Hassan, A.S.O., Abdel-Malek, H.L., Rabie, A.A.: None-derivative design centering algorithm using trust region optimization and variance reduction. Eng. Optim. 38, 37–51 (2006)
Hassan, A.S.O., Mohamed, A.S., El-Sharabasy, A.Y.: Statistical microwave circuit optimization via a non-derivative trust region approach and space mapping surrogates. In: IEEE MTT-S Int. Microw. Symp. Dig., Baltimore, MD, USA (2011)
Hassan, A.S.O., Abdel-Naby, A.: A new hybrid method for optimal circuit design using semi-definite programming. Eng. Optim. 1–16 (2011)
Hocevar, D.E., Lightner, M.R., Trick, T.N.: A study of variance reduction techniques for estimating circuit yields. IEEE Trans. Comput.-Aided Des. 2(3), 180–192 (1983)
Hocevar, D.E., Lightner, M.R., Trick, T.N.: An extrapolated yield approximation for use in yield maximization. IEEE Trans. Comput.-Aided Des. 3, 279–287 (1984)
Keramat, M., Kielbasa, R.: A study of stratified sampling in variance reduction techniques for parametric yield estimations. IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process. 45(5), 575–583 (1998)
Koziel, S., Bandler, J.W., Madsen, K.: A space-mapping frame work for engineering optimization: theory and implementation. IEEE Trans. Microw. Theory Tech. 54(10), 3721–3730 (2006)
Marcuvitz, N.: Waveguide Handbook, 1st edn. McGraw-Hill, New York (1951)
Matthaei, G.L., Young, L., Jones, E.M.T.: Microwave Filters, Impedance-Matching Networks, and Coupling Structures, 1st edn. McGraw-Hill, New York (1964)
McKay, M.D., Beckman, R.J., Conover, W.J.: A comparison of three methods for selecting values of input variables in analysis of output from a computer code. Technometrics 21(2), 239–245 (1979)
Metropolis, N., Ulam, S.: The Monte-Carlo method. J. Am. Stat. Assoc. 44, 335–341 (1949)
Moré, J.J., Sorensen, D.C.: Computing a trust region step. SIAM J. Sci. Stat. Comput. 4(3), 553–572 (1983)
Powell, M.J.D.: UOBYQA. Unconstrained optimization by quadratic approximation. Math. Program. 92, 555–582 (2002)
Powell, M.J.D.: The NEWUOA software for unconstrained optimization without derivatives. In: Di Pillo, G., Roma, M. (eds.) Large-Scale Nonlinear Optimization, pp. 255–297. Springer, New York (2006)
Powell, M.J.D.: Developments of NEWUOA for unconstrained minimization without derivatives. Technical Report, DAMTP 2007INA05, Department of Applied Mathematics and Theoretical Physics, Cambridge University, UK (2007)
Sapatnekar, S.S., Vaidya, P.M., Kang, S.: Convexity-based algorithms for design centering. IEEE Trans. Comput.-Aided Des. 13(12), 1536–1549 (1994)
Sauer, Th., Xu, Y.: On multivariate Lagrange interpolation. Math. Comput. 64, 1147–1170 (1995)
Seifi, A., Ponnambalam, K., Vlach, J.: A unified approach to statistical design centering of integrated circuits with correlated parameters. IEEE Trans. Circuits Syst. 46, 190–196 (1999)
Singhal, K., Pinel, J.F.: Statistical design centering and tolerancing using parametric sampling. IEEE Trans. Circuits Syst. 28, 692–702 (1981)
Soliman, E.A., Bakr, M.H., Nikolova, N.K.: An adjoint variable method for sensitivity calculations of multiport devices. IEEE Trans. Microw. Theory Tech. 52, 589–599 (2004)
Soliman, E.A.: Rapid frequency sweep technique for MoM planar solvers. IEE Proc. Microw. Antennas Propag. 151, 277–282 (2004)
Soliman, E.A., Bakr, M.H., Nikolova, N.K.: Accelerated gradient-based optimization of planar circuits. IEEE Trans. Antennas Propag. 53, 880–883 (2005)
Styblinski, M.A., Oplaski, L.J.: Algorithms and software tools for IC yield optimization based on fundamental fabrication parameters. IEEE Trans. Comput.-Aided Des. 5, 79–89 (1986)
Toh, K.-C.: Primal-dual path-following algorithms for determinant maximization problems with linear matrix inequalities. Comput. Optim. Appl. 14, 309–330 (1999)
Vandenberghe, L., Boyd, S., Wu, S.-P.: Determinant maximization with linear matrix inequality constraints. SIAM J. Matrix Anal. Appl. 19, 499–533 (1998)
Vandenberghe, L., Boyd, S.: Applications of semidefinite programming. Appl. Numer. Math. 29, 283–299 (1999)
Wojciechowski, J.M., Vlach, J.: Ellipsoidal method for design centering and yield estimation. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 12, 1570–1579 (1993)
Wojciechowski, J., Opalski, L., Zantyniski, K.: Design centering using an approximation to the constraint region. IEEE Trans. Circuits Syst. 51(3), 598–607 (2004)
Yu, T., Kang, S.M., Hajj, I.N., Trick, T.N.: Statistical performance modeling and parametric yield estimation of MOS VLSI. IEEE Trans. Comput.-Aided Des. 6, 1013–1022 (1987)
Zaabab, A.H., Zhang, Q.J., Nakhla, M.: A neural network modeling approach to circuit optimization and statistical design. IEEE Trans. Microw. Theory Tech. 43, 1349–1358 (1995)
Zhao, W., De, A., Donoro, D.G., Zhang, Y., Sarkar, T.K.: Antenna optimization by using NEWUOA. In: IEEE Antennas, Propag. Int. Symp., APSURSI 09 (2009)
Acknowledgements
The authors would like to thank Prof. Slawomir Koziel, School of Science and Engineering, Reykjavik University, for his invitation to contribute to this book. The authors also would like to acknowledge the contributions to the original work by Prof. Hany Abdel-Malek, Dr. Azza Rabie, Dr. Sameh Dakroury, Dr. Ahmed Abdel-Naby, and Eng. Ahmed El-Sharabasy, Faculty of Engineering, Cairo University, which have been reviewed in this chapter.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Hassan, AK.S.O., Mohamed, A.S.A. (2013). Surrogate-Based Circuit Design Centering. In: Koziel, S., Leifsson, L. (eds) Surrogate-Based Modeling and Optimization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7551-4_2
Download citation
DOI: https://doi.org/10.1007/978-1-4614-7551-4_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-7550-7
Online ISBN: 978-1-4614-7551-4
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)