Space Mapping Design Framework Exploiting Tuning Elements

Inspired by the ideas of “simulator-based” tuning, implicit space mapping, and surrogate optimization, we propose an implementable microwave design framework. In this framework, we alter an electromagnetic (EM) model by embedding suitable tuning elements. The resulting tuning model is aligned with the original unaltered EM model. We then designate the aligned tuning model as surrogate for design optimization purposes. We illustrate our tuning space mapping framework using a simple microstrip line example. Several microwave examples, including a low-temperature co-fired ceramic filter demonstrate the framework's implementation and robustness.      

Space-Mapping Optimization With Adaptive Surrogate Model

The proper choice of mapping used in space-mapping optimization algorithms is typically problem dependent. The number of parameters of the space-mapping surrogate model must be adjusted so that the model is flexible enough to reflect the features of the fine model, but at the same time is not over flexible. Its extrapolation capability should allow the prediction of the fine model response in the neighborhood of the current iteration point. A wrong choice of space-mapping type may lead to poor performance of the space-mapping optimization algorithm. In this paper, we consider a space-mapping optimization algorithm with an adaptive surrogate model. This allows us to adjust the type of space-mapping surrogate model used in a given iteration based on the approximation/extrapolation capability of the model. The technique does not require any additional fine model evaluations     

Space-mapping optimization of microwave circuits exploitingsurrogate models

A powerful new space-mapping (SM) optimization algorithm is presented in this paper. It draws upon recent developments in both surrogate model-based optimization and modeling of microwave devices, SM optimization is formulated as a general optimization problem of a surrogate model. This model is a convex combination of a mapped coarse model and a linearized fine model. It exploits, in a novel way, a linear frequency-sensitive mapping. During the optimization iterates, the coarse and fine models are simulated at different sets of frequencies. This approach is shown to be especially powerful if a significant response shift exists. The algorithm is illustrated through the design of a capacitively loaded 10:1 impedance transformer and a double-folded stub filter. A high-temperature superconducting filter is also designed using decoupled frequency and SMs     

Interpolated Coarse Models for Microwave Design Optimization With Space Mapping

The efficiency of space-mapping optimization depends on the quality of the underlying coarse model, which should be sufficiently close to the fine model and cheap to evaluate. In practice, available coarse models are often cheap, but inaccurate (e.g., a circuit equivalent of the microwave structure) or accurate, but too expensive (e.g., a coarse-mesh model). In either case, the space-mapping optimization process exhibits substantial computational overhead due to the excessive fine model evaluations necessary to find a good solution if the coarse model is inaccurate, or due to the cost of the parameter extraction and surrogate optimization sub-problems if the coarse model is too expensive. In this paper, we use an interpolation technique, which allows us to create coarse models that are both accurate and cheap. This overcomes the accuracy/cost dilemma described above, permitting significant reduction of the space-mapping optimization time. Examples verify the performance of our approach.     

A space-mapping design framework

We present a comprehensive microwave design framework for implementing the original, aggressive, implicit, and response residual space-mapping (SM) approaches through widely available software. General steps and tools for possible SM implementations are elaborated. Our presentation is a reference guide for microwave designers using the SM technique. An instructive "multiple cheese-cutting" example demonstrates the SM approach to engineering design and some possible pitfalls. For the first time, an ADS framework implements the SM steps interactively. A three-section transformer example illustrates the approach, step by step. A six-section H-plane waveguide filter design emerges after four iterations, using the implicit SM and the response-residual space-mapping (RRSM) optimization entirely within the design framework. An RRSM surrogate is developed to match the fine (HFSS) model. We use sparse frequency sweeps and do not require Jacobians of the fine model.     

Microwave YIG-tuned transistor oscillator amplifier design: application to C band

An approach to the design of a microwave YIG-tuned transistor oscillator amplifier is discussed in this paper. A classic lumped-element model of the transistor is used to show that a simple but still accurate equivalent circuit can be useful in predicting the effect of transistor parameters on the tuning range of a microwave oscillator. On the other hand, this paper describes a design procedure `without model' based on the small-signal characterization of the transistor by its scattering matrix. This method is particularly suited to amplifier designing since scattering parameters are inherently power-flow parameters and well adapted to computer-aided design (CAD) and optimization techniques. A 3.0-6.5 GHz YIG-tuned transistor oscillator amplifier with 10 mW of output power illustrates the usefulness of these two methods.     

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     

基于空间映射的RF MEMS 开关建模研究

空间映射的思想是通过构造粗糙模型设计变量与精确模型设计变量之间的映射关系,获得合适的替代模型（校准后的粗糙模型）,从而简化优化过程。本文针对电容耦合式RF MEMS 开关使用初始空间映射算法进行计算和优化,经过迭代,建立了精确空间和粗糙空间的映射关系,最终得到了精确空间优化设计值,利用此映射关系,可将精确空间的优化工作放到粗糙空间进行,从而大大节省时间和电脑资源。计算结果验证了该方法的可行性和高效性。     

多层混合填充吸波材料的三目标粒子群优化

使用多层结构来离散自由空间到金属衬底之间理想的连续阻抗变化过程是吸波材料设计的重要方 法之一,较多层数的精细结构能够更好地逼近这一连续变化过程以获得更理想的吸波性能,但也会增加工程实现成 本和复杂度。因此,实际工程中往往需要在结构层数和逼近精度等诸多相互矛盾的因素之间寻求平衡。文中采用 石墨烯纳米片(GNS) / 片状羰基铁颗粒(FCI)混合填充的多层吸波材料,在由极化无关的宽带宽角吸波性能、FCI 填 充量以及最终层数这三个指标所张成的三维目标空间中,基于粒子群优化对多层吸波材料进行了优化设计。结果 显示,相比于吸波性能和磁性粒子填充量二维空间中的设计结果,在FCI 填充量仅需增加不到3. 3 wt%的情况下,即 可使所需层数下降50%并保持原有吸波能力的98%;不进行优化的GNS 填充量仅增加0. 6 wt%,层数显著减少,吸 波材料的总厚度降低了14%,综合性能也提高了27. 9%。此外,与其它不同优化策略的系统进行了对比,文中设计 为混合填充吸波材料的多目标优化提供了一定参考。     

A generalized space-mapping tableau approach to device modeling

A comprehensive framework to engineering device modeling, which we call generalized space mapping (GSM) is introduced in this paper. GSM permits many different practical implementations. As a result, the accuracy of available empirical models of microwave devices can be significantly enhanced. We present three fundamental illustrations: a basic space-mapping super model (SMSM), frequency-space-mapping super model (FSMSM) and multiple space mapping (MSM). Two variations of MSM are presented: MSM for device responses and MSM for frequency intervals. We also present novel criteria to discriminate between coarse models of the same device. The SMSM, FSMSM, and MSM concepts have been verified on several modeling problems, typically utilizing a few relevant full-wave electromagnetic simulations. This paper presents four examples: a microstrip line, a microstrip right-angle bend, a microstrip step junction, and a microstrip shaped T-junction, yielding remarkable improvement within regions of interest     

EM-based optimization exploiting partial space mapping and exact sensitivities

We present a family of robust techniques for exploiting sensitivities in electromagnetic (EM)-based circuit optimization through space mapping (SM) technology. We utilize derivative information for parameter extractions and mapping updates. We exploit a partial SM (PSM) concept, where a reduced set of parameters is sufficient for parameter extraction optimization. It reflects the idea of tuning and execution time is reduced. Upfront gradients of both EM (fine) model and coarse surrogates can initialize possible mapping approximations. We introduce several effective approaches for updating the mapping during the optimization iterations. Examples include the classical Rosenbrock function, modified to illustrate the approach, a two-section transmission-line 10:1 impedance transformer and a microstrip bandstop filter with open stubs.     

Fuzzy optimization techniques applied to the design of a digital PMSM servo drive

This paper presents a novel design approach by applying gradient optimization with fuzzy step-sizing techniques to the design of a digital permanent magnet synchronous motor (PMSM) servo drive. The servo specifications and design variables are specified and analyzed to formulate a controller optimization problem. The servo responses are then fed back to evaluate the overall system performances, which can be expressed as objective functions with respect to the servo control parameters. According to the objective functions and design specifications, the servo control parameters can be properly tuned toward their optimal values by using the proposed optimization techniques. In order to improve the convergent rate of the optimization process, a fuzzy-logic based step-size tuning strategy is presented. Because of the nonlinear property of the digital servo drives, the tuned servo control parameters may be only optimal for a particular operating point, therefore, once the optimum design is achieved, the proposed fuzzy optimizing controller can perform as an intelligent tuner for on-line gain adaptation under different loading conditions. The proposed fuzzy optimization servo tuner has been realized under a PC-MATLAB-based environment with an on-line controlled digital PMSM servo drive. Simulation and experimental results indicate that the control parameters of a digital PMSM servo drive can be optimized for its dynamic responses under various load conditions.     

基于微波均衡器测量数据库的网络优化设计

基于微波幅度均衡器测量数据库的互联子结构网络计算机辅助设计的方法结合了数据实验测量的精确性和计算机大容量、高速运算的优点，它包括子结构设计、测量数据库的建立、子结构互联网络理论和优化算法设计等多步骤。该方法在微波幅度均衡器设计、调试中得到验证和应用，具有实际的工程价值。     

新型高收敛隐式空间映射算法设计微波滤波器

该文介绍了一种高收敛隐式空间映射算法,改进了隐式空间映射算法中粗糙模型到精细模型之间参数映射。它加入粗糙模型参数选择过程,避免了粗糙模型优化中的假收敛情况,加快精细模型与设计目标的逼近速度。参数选择过程不需要增加精细模型的计算次数,提高了优化效率。该文通过设计一个发卡形滤波器,并与以前的隐式空间映射算法计算结果进行比较,优化得到了比指标性能更优越的结果。同时证明了新算法比旧算法具有更快的逼近速度和更高的优化效率的优点。     

硅基毫米波共面波导可缩放神经网络模型

随着微电子工艺技术的发展,硅基CMOS器件的截止频率已经达到毫米波频段,使硅基微波单片集成电路实现成为可能。因此,建立硅基毫米波频段共面波导结构模型使准确设计硅基微波单片集成电路成为必要。文章提出了一种基于神经网络技术的共面波导结构(CPW)毫米波可缩放模型,采用3层神经网络结构,根据共面波导的测试结果,用神经网络来学习其物理变量和测试的相应S参数空间映射关系。仿真与测试结果比较表明:基于神经网络方法建立的毫米波共面波导可缩放模型对不同几何参数CPW能够快速和准确地给出对应的CPW的S参数结果。     

Gradient-based adjoint-variable optimization of broadband microstrip antennas with mixed-order prism macroelements

This paper describes a new finite element method (FEM)-based adjoint-variable approach to design and optimization of planar microwave circuits using sensitivity analysis, with respect to small variations of their design parameters. The implementation is based on a specially developed class of mixed-order prismatic macroelements, suitable for an efficient analysis of planar microwave structures. Their use, combined with a simple probe feed model, not only reduces the overall computational effort but also facilitates a straightforward derivation of port parameter sensitivities. Explicit expressions are given for the adjoint solution and S-parameter sensitivity and the process is verified through the design and optimization of two slotted broadband microstrip patch antennas.     

Chirped Microwave Pulse Generation Based on Optical Spectral Shaping and Wavelength-to-Time Mapping Using a Sagnac Loop Mirror Incorporating a Chirped Fiber Bragg Grating

In this paper, we propose and demonstrate an approach to optically generating chirped microwave pulses with tunable chirp profile based on optical spectral shaping using a Sagnac loop filter incorporating a chirped fiber Bragg grating (CFBG) and linear wavelength-to-time mapping in a dispersive element. In the proposed approach, the optical power spectrum of an ultrashort optical pulse is shaped by a CFBG-incorporated Sagnac loop mirror that has a reflection spectral response with a linearly increasing or decreasing free spectral range. The spectrum-shaped optical pulse is then sent to a dispersive element to perform the linear wavelength-to-time mapping. A chirped microwave pulse with the pulse shape identical to that of the shaped spectrum is obtained at the output of a high-speed photodector. The central frequency and the chirp profile of the generated chirped microwave pulse can be controlled by simply tuning the time delay in the Sagnac loop mirror. A simple mathematical model to describe the chirped microwave pulse generation is developed. Numerical simulations and a proof-of-principle experiment are implemented to verify the proposed approach.      

一种微波滤波器的参数提取方法

在微波滤波器的计算机辅助调试技术中,必须要知道滤波器的状态参数。以往的方法主要是通过滤波器的耦合矩阵来求得它的状态参数,但计算起来相当复杂。介绍一种简单易行的提取滤波器状态参数的方法,该方法通过建立滤波器的等效电路模型,运用软件的优化拟合功能,从而提取出等效电路模型的参数值。实验证明,只要搭建的电路模型精确度较高,就能够迅速、准确地提取出滤波器的状态参数。     

改进粒子群优化在稳定平台多空间分析模型的应用

常规伺服系统根据电机轴系转动进行模型分析,以轴系所在的基座空间作为参照系。稳定平台的被控量以惯性空间作为参照系,因此不适合用常规伺服系统模型来建模。针对稳定平台的多参照系问题,文章采用以惯性空间作为电机轴系转动参照系的多空间分析模型,并将改进粒子群算法应用于该模型。粒子群算法作为一种群智能算法,广泛应用于参数优化。文中通过惯性权重改进和越界改进,利用改进后的粒子群算法进行稳定平台PID参数的优化和整定。通过仿真和硬件实验平台验证,结果表明:在稳定平台多空间分析模型基础之上,采用改进粒子群算法优化后的PID控制器可以使稳定平台有更高的稳定精度、更好的鲁棒性,有效地隔离了外部的震动和干扰。