Parallel EM optimization using improved pole‐residue‐based neuro‐TF surrogate and isomorphic orthogonal DOE sampling for microwave components design

Author:

Na Wei‐Cong1,Liu Wen‐Xu1,Liu Ke1,Feng Feng2ORCID,Zhang Jia‐Nan3,Zhang Wan‐Rong1,Xie Hong‐Yun1,Jin Dong‐Yue1

Affiliation:

1. Faculty of Information Technology Beijing University of Technology Beijing China

2. Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, School of Microelectronics Tianjin University Tianjin China

3. State Key Laboratory of Millimeter Waves Southeast University Nanjing China

Abstract

AbstractDirect electromagnetic (EM) optimization for microwave components design is usually a time‐consuming process. To improve the optimization efficiency, this paper proposes a novel parallel EM optimization technique exploiting improved pole‐residue‐based neuro‐transfer function (neuro‐TF) surrogate and isomorphic orthogonal design of experiment (DOE) sampling strategy. We propose a new sampling method combining isomorphic orthogonal DOE and parallel EM simulations to generate training data for developing the neuro‐TF surrogate. This proposed sampling method can ensure the scattered distribution of data samples in the overall optimization process, thus effectively improving the surrogate accuracy and increasing the optimization speed. We also propose a new pole‐residue tracking technique for order‐changing to solve the discontinuity problem of pole/residues during the neuro‐TF surrogate development. Different from the fixed split ratio in existing pole‐residue tracking technique, the split ratio of poles and residues in the proposed technique is adaptive and determined according to the information of neighboring samples. Therefore, the continuity and smoothness of pole/residues after the splitting are improved, so as the neuro‐TF surrogate accuracy. In addition, the trust region algorithm is exploited during EM optimization to improve the convergence speed. In this way, the proposed EM optimization technique obtains the optimal solution in a shorter time with fewer iterations than the existing techniques. Two examples of EM optimizations of microwave components are used to illustrate the proposed technique.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

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