基于替代模型的微波器件优化方法研究

SURROGATE-BASED MODELING AND OPTIMIZATION FOR MICROWAVE STRUCTURES

宋怡然

11749187

硕士

电子与通信工程

程庆沙

2019-05-30

2019-07-12

哈尔滨工业大学

深圳

随着新技术、新材料、新工艺设计制造的微波器件不断出现，对设计方法提出了更严峻的挑战。目前主要面临的问题是微波器件设计变量数目多，电磁仿真时间长和设计优化收敛慢等。替代模型是微波领域常用的优化方法，它解算速度快且具有一定的精确度，可以在优化过程中替代全波电磁仿真模型（或称为“精细模型”）。因此，研究基于替代模型的微波器件优化技术能大大提高优化效率，具有重要的实际意义。本文通过研究“粗糙模型”精度选取原则和替代模型构建方法，提出了一种多精度局部替代模型优化算法，该算法稳健且计算效率高，尽可能地减少在优化过程中粗糙模型和精细模型的求解次数，提高算法的优化速度和最优解精确度。本算法基于响应面近似原理，利用多精度粗糙模型的样本点仿真数据和多项式插值构建局部替代模型。在优化过程中，局部区域建模和寻优同时进行，局部区域的更新（移动方向和区域大小）由当前局部最优解出现的位置来决定。本算法引入判断因子对区域更新提供定量计算的依据，自适应地改变寻优路径和步长，使算法快速收敛于替代模型最优解。最后，利用空间映射技术对最优解所在区域的替代模型进行修正，再对其优化得到精度较高的最优设计参数。本文利用带通滤波器和紧凑型超宽带MIMO天线两个例子来验证上述多精度局部替代模型优化算法。优化结果在精细模型中的响应均能满足设计要求，验证了该算法的有效性和实用性。本文将该算法与直接优化算法等方法进行了比较，该算法不仅具有较强的算法稳定性，更重要的是，在计算成本上减少为原来的十分之一。

With the emergence of new design technologies, new materials, and new fabrication techniques in the microwave component, the design methodology faces serious challenge. At present, the main problems are as follows: the number of design variables of microwave devices is very large, the electromagnetic (EM) simulation time is very long, and the convergence speed of optimization is very slow. The surrogate model is a commonly used design optimization method in the microwave field. This method has low computational cost and relatively accurate. It can replace the EM simulation model (so-called “fine model”) in the optimization process. Therefore, it is of great practical significance to study surrogate-based optimization method for microwave devices.The thesis studies the accuracy selection principle and the surrogate construction methods. A multi-fidelity local surrogate optimization algorithm is proposed. The algorithm is robust and computational-efficient. The efficiency is achieved by reducing the number of evaluations of both the low- and high-fidelity models in the optimization process.The algorithm exploits the principle of response surface approximation. A series of local surrogates are constructed using the sample data of multi-fidelity coarse models and polynomial interpolation. In the optimization process, the local region are updated using the position of the current local optimal solution. The update (the size and moving direction of the local region) is determined by a judgment factor. A series of surrogates are constructed within each updated region and subsequently optimized. The last surrogate is then refined by space mapping technique to obtain an optimal design for the fine model.The proposed algorithm is demonstrated through design of a band-pass filter and a compact UWB MIMO antenna. The responses of the optimized fine model meet the design specification. A comparison with other design approaches, including the direct fine model optimization, is also presented. The multi-fidelity local surrogate optimization method is robust, but more importantly, it also reduces the computational cost significantly (one tenth of the direct fine model optimization).

局部替代模型 多精度优化 带通滤波器

MIMO天线 local surrogate model multi-fidelity optimization band-pass filter MIMO antenna

中文

联合培养

南方科技大学

宋怡然. 基于替代模型的微波器件优化方法研究[D]. 深圳. 哈尔滨工业大学,2019.