Space mapping surrogate‐based microwave circuit design centering using a new statistical technique

Abstract

Design centering is an optimal design process that seeks for the values of system parameters which maximize the probability of satisfying the design specifications (yield function). In this article, a derivative-free trust region (TR) optimization approach is combined with the generalized space mapping technique to develop a new space mapping (SM) surrogate-based statistical technique for design centering of computationally expensive microwave circuits. The TR optimization approach is well suited for expensive objective functions that have some uncertainty in their values or subject to statistical variations. The principal operation relies on building and successively updating quadratic surrogate models to be optimized instead of the objective function over TRs employing the truncated conjugate gradients. The approach constructs the initial quadratic surrogate model using fewer data points, then updates the surrogate model using a weighted least squares fitting that gives more emphasis to points close to the current center point. Integrating the TR optimization approach with the generalized space mapping technique results in a novel statistical design centering technique for the microwave circuits with a great reduction in computations and simulations needed for the yield optimization process. Design of practical microwave circuits is presented to indicate the effectiveness of the new design centering technique.

Microwave systems design centering exploiting space mapping technology and modified trust region algorithm

“…The statistical design centering approach maximizes the yield function explicitly. [1][2][3][4]11 It is worth to mention that the statistical estimation accuracy of the yield values is not affected by the number of parameters and/or performance features; however, it depends only on the sample size.…”

“…Due to its importance, system design centering has been discussed and developed by many researchers in several publications. [1][2][3][4][5][6][7][8][9][10][11][12][13] Generally, design centering approaches can be categorized into two main classes, namely, geometrical and statistical approaches. For geometrical approaches, the yield function is implicitly optimized by fetching the feasible region center and use it to approximate the design center.…”

“…1,[5][6][7][8][9][10]12 On the other hand, statistical approaches utilize statistical analysis approaches to explicitly optimize the yield function with no restrictions on the problem size. [1][2][3][4]11 In general, yield function value at a given nominal parameter values could be estimated by generating a set of sample points in the design parameter space using a predefined probability distribution of the system parameters. The system is simulated for each sample point where the acceptable systems percentage provides a suitable estimate of the yield function value.…”

“…1 To overcome this problem, the exact calculations using the simulator (high fidelity accurate model) could be performed, instead, using a cheaper surrogate model. 1,3,7,10 Space mapping (SM) technology 17,18 introduces efficient SM surrogate models that can be used to reduce the simulation cost. SM technology exploits fast, yet inaccurate, cheap coarse models to construct SM surrogate models that replace the time-consuming, computationally CPU intensive full-wave fine models.…”

Editorial for the special issue on advances in simulation‐driven modeling and optimization of microwave/RF circuits

“…The largest number of papers is devoted to surrogate modeling methodologies and computationally efficient surrogate‐assisted design optimization. In particular, application of space mapping methodology is considered in Rodrigues et al for automated design of microwave filters, whereas Hassan et al describe space mapping for low‐cost design centering of microwave circuits. In Rayas‐Sanchez et al, EM‐based optimization of microstrip and SIW interconnects is presented using low‐order polynomial surrogates.…”