Mohamed H. Bakr

A trust region aggressive space mapping algorithm for EM optimization

A new robust algorithm for EM optimization of microwave circuits is presented. The algorithm integrates a trust region methodology with aggressive space mapping (ASM). A new automated multipoint parameter extraction process is implemented. EM optimization of a double-folded stub filter and of an HTS filter illustrate our new results.

Neural space-mapping optimization for EM-based design

We propose, for the first time, neural space-mapping (NSM) optimization for electromagnetic based design. NSM optimization exploits our space-mapping (SM)-based neuromodeling techniques to efficiently approximate the mapping. A novel procedure that does not require troublesome parameter extraction to predict the next point is proposed. The initial mapping is established by performing upfront fine-model analyses at a reduced number of base points. Coarse-model sensitivities are exploited to select those base points. Huber optimization is used to train, without testing points, simple SM-based neuromodels at each NSM iteration. The technique is illustrated by a high-temperature superconducting quarter-wave parallel coupled-line microstrip filter and a bandstop microstrip filter with quarter-wave resonant open stubs.

A hybrid aggressive space mapping algorithm for EM optimization

We present a novel, hybrid aggressive space mapping (HASM) optimization algorithm. HASM is a hybrid approach exploiting both the trust region aggressive space mapping (TRASM) algorithm and direct optimization. It does not assume that the final space-mapped design is the true optimal design and is robust against severe misalignment between the coarse and the fine models. The algorithm is based on a novel lemma that enables smooth switching from the TRASM optimization to direct optimization and vice versa. The new algorithm has been tested on several microwave filters and transformers.

Accelerated Microwave Design Optimization With Tuning Space Mapping

We introduce a tuning space-mapping technology for microwave design optimization. The general tuning space-mapping algorithm is formulated, which is based on a so-called tuning model, as well as on a calibration process that translates the adjustment of the tuning model parameters into relevant updates of the design variables. The tuning model is developed in a fast circuit-theory based simulator and typically includes the fine model data at the current design in the form of the properly formatted scattering parameter values. It also contains a set of tuning parameters, which are used to optimize the model so that it satisfies the design specification. The calibration process may involve analytical formulas that establish the dependence of the design variables on the tuning parameters. If the formulas are not known, the calibration process can be performed using an auxiliary space-mapping surrogate model. Although the tuning space mapping can be considered to be a specialized case of the standard space-mapping approach, it can offer even better performance because it enables engineers to exploit their experience within the context of efficient space mapping. Our approach is demonstrated using several microwave design optimization problems.

Adjoint techniques for sensitivity analysis in high-frequency structure CAD

There is a revival of the interest in adjoint sensitivity analysis techniques. This is partly because current computer-aided-design software based on full-wave electromagnetic (EM) solvers remains too slow for the purposes of practical high-frequency structure design despite the increasing capacity of computers. The adjoint-variable methods for design sensitivity analysis offer computational speed and accuracy. They can be used for efficient gradient-based optimization, in tolerance and yield analysis. Adjoint-based sensitivity analysis for circuits has been well studied and extensively covered in the microwave literature. In comparison, sensitivities with full-wave analysis techniques have attracted little attention, and there have been few applications into feasible and versatile algorithms. We review adjoint-variable methods used in high-frequency structure design with both circuit analysis techniques and full-wave EM analysis techniques. A brief discussion on adjoint-based sensitivity analysis for nonlinear dynamic systems is also included.

Sensitivity analysis with the FDTD method on structured grids

We propose an adjoint-variable approach to design-sensitivity analysis with time-domain methods based on structured grids. Unlike conventional adjoint-based methods, it does not require analytical derivatives of the system matrices. It is simple to implement with existing computational algorithms such as the finite-difference time-domain (FDTD) technique. The resulting FDTD algorithm produces the response and its gradient in the design parameter space with two simulations regardless of the number of design parameters. The proposed method is validated by the adjoint-based FDTD analysis of waveguide structures with metallic boundaries.

A hybrid aggressive space-mapping algorithm for EM optimization

We present a novel, hybrid aggressive space mapping (HASM) optimization algorithm. HASM is a hybrid approach exploiting both the trust region aggressive space mapping (TRASM) algorithm and direct optimization. It does not assume that the final space-mapped design is the true optimal design and is robust against severe misalignment between the coarse and the fine models. The algorithm is based on a novel lemma that enables smooth switching from the TRASM optimization to direct optimization and vice versa. The new algorithm has been tested on several microwave filters and transformers.

Feasible adjoint sensitivity technique for EM design optimization

The adjoint variable method for frequency domain design sensitivity analysis is proposed for the optimization of wire and printed structures analyzed by the Method of Moments (MoM). We focus on the construction of the adjoint system using a feasible technique which requires only minor modifications of existing MoM codes. The solution to the adjoint problem is obtained with very little overhead once the original problem is solved. The gradient of the objective function is consequently computed through a single analysis regardless of the number of the design parameters. The concept is illustrated through the design of a Yagi-Uda array and a rectangular patch antenna using suitable MoM simulators.

An Introduction to the Space Mapping Technique

The space mapping technique is intended for optimization of engineering models which involve very expensive function evaluations. It is assumed that two different models of the same physical system are available: Besides the expensive model of primary interest (denoted the fine model), access to a cheaper (coarse) model is assumed which may be less accurate.The main idea of the space mapping technique is to use the coarse model to gain information about the fine model, and to apply this in the search for an optimal solution of the latter. Thus the technique iteratively establishes a mapping between the parameters of the two models which relate similar model responses. Having this mapping, most of the model evaluations can be directed to the fast coarse model.In many cases this technique quickly provides an approximate optimal solution to the fine model that is sufficiently accurate for engineering purposes. Thus the space mapping technique may be considered a preprocessing technique that perhaps must be succeeded by use of classical optimization techniques. We present an automatic scheme which integrates the space mapping and classical techniques.

Space mapping optimization of microwave circuits exploiting surrogate models

A powerful new Aggressive Space Mapping (ASM) optimization algorithm is presented. It draws upon recent developments in both surrogate-based optimization and microwave device neuromodeling. Our surrogate formulation (new to microwave engineering) exploits, in a novel way, a linear frequency-space mapping. This is a powerful approach to severe response misalignments.