Advanced Parallel Space-Mapping-Based Multiphysics Optimization for High-Power Microwave Filters

Zhang, Wei; Feng, Feng; Liu, Wenyuan; Yan, Shuxia; Zhang, Jianan; Jin, Jing; Zhang, Qi‐Jun

doi:10.1109/tmtt.2021.3065972

Cited by 32 publications

(24 citation statements)

References 42 publications

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“…According to the reference MOP literature [45][46] [50], A is composed by the Pareto Front (PF) of all non-dominated solutions spanning the K-dimensional search space R K , the dominance of one solution, Ω (1) , over another one, Ω (2) = Ω (1) (i.e., Ω (1) ≺ Ω (2) ) being mathematically stated as follows (Fig. 1)…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…In practical scenarios, it is thus convenient to look for an alternative/approximated definition of A that complies with the following assumptions: (a) the number of entries of the PF, A, is finite (i.e., A is a bounded set) and (b) these A solutions are uniformly spread in the solution space R K so that they are representative of all possible non-dominated solutions that comply with (1). Towards this end, the concept of ε-dominance is exploited.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Towards this end, the concept of ε-dominance is exploited. Accordingly, Ω (1) is said to ε-dominate Ω (2) (i.e., Ω (1) ≺ ε Ω (2) ) if one of the following conditions holds true (Fig. 1)…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…1. According to (1), it turns out that Ω (1) ≺ Ω (3) and Ω (2) ≺ Ω (3) , but Ω (1) ⊀ Ω (2) and Ω (2) ⊀ Ω (1) (i.e., Ω (1) and Ω (2) are two non-dominated solutions). Otherwise, the solution Ω (1) ε-dominates both Ω (2) and Ω (3) (i.e., Ω (1) ≺ ε Ω (2) and Ω (1) ≺ ε Ω (3) ) according to (3), while Ω (2) ≺ ε Ω (3) .…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…The design of modern high-performance microwave devices such as filters [1], directional couplers [2], and antennas [3], generally involves a number of challenging and (sometimes) contrasting requirements on their electromagnetic (EM) behavior along with tight geometrical, weight, and cost constraints [4]. Such a synthesis problem is often formulated as a singleobjective optimization problem (SOP) whose solution is the global minimum of a cost function that quantifies the mismatch between the EM/structural features of the synthesized device and the user-defined objectives.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective System-by-Design for mm-Wave Automotive Radar Antennas

Rosatti¹,

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et al. 2022

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The computationally-efficient solution of multi-objective optimization problems (MOPs) arising in the design of modern electromagnetic (EM) microwave devices is addressed. Towards this end, a novel System-by-Design (SbD) method is developed to effectively explore the solution space and to provide the decision maker with a set of optimal trade-off solutions minimizing multiple and (generally) contrasting objectives. The proposed MO-SbD method proves a high computational efficiency, with a remarkable time saving with respect to a competitive state-of-the-art MOP solution strategy, thanks to the "smart" integration of evolutionary-inspired concepts and operators with artificial intelligence (AI) and machine learning (ML) techniques. Representative numerical results are reported to provide the interested users with useful insights and guidelines on the proposed optimization method as well as to assess its effectiveness in designing mm-wave automotive radar antennas.

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Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-Objective System-by-Design for mm-Wave Automotive Radar Antennas

Rosatti¹,

Salucci²,

L.³

et al. 2022

Preprint

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

Liu

et al. 2023

Int J Numerical Modelling

Self Cite

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Direct 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.

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