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Expedited Design Optimization of Antenna Input Characteristics Using Trust-Region Search with Adaptive Jacobian Updates

机译:使用具有自适应雅可比更新的信任区域搜索来加快天线输入特性的设计优化

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Reducing the number of electromagnetic (EM) simulations in the course of design closure procedures is a key to make them more practical for antenna designers. This applies to both direct and surrogate-assisted optimization algorithms. In either case, local methods such as gradient search are ultimately applied to find an improved design at either (low-or high-fidelity) level of antenna evaluation. In this paper, a simple yet robust technique to reduce the computational cost of gradient-based optimization process is proposed. Our methodology involves selective application of Jacobian updating formulas controlled by the alignment between the recent design relocation and coordinate system basis vectors, with the acceptance threshold made dependent on the algorithm convergence status. The algorithm is demonstrated to provide considerable speedup of up to 63 percent as compared to the reference trust-region-based procedure. The results are consistent across a three-antenna benchmark set with the robustness confirmed by means of statistics over multiple runs with random initial designs.
机译:在设计完成过程中减少电磁(EM)仿真的次数是使它们对天线设计人员更加实用的关键。这适用于直接和代理辅助的优化算法。无论哪种情况,最终都采用诸如梯度搜索之类的局部方法来在天线评估的(低保真或高保真)水平上找到改进的设计。本文提出了一种简单而健壮的技术来降低基于梯度的优化过程的计算成本。我们的方法包括选择性地应用由最近的设计重定位和坐标系基向量之间的对齐方式控制的雅可比更新公式,接受阈值取决于算法的收敛状态。与基于参考信任区域的过程相比,该算法被证明可提供高达63%的显着加速。结果在三天线基准测试集上是一致的,其鲁棒性是通过采用随机初始设计进行多次运行的统计数据确认的。

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