Robust Design of Dual Band/Polarization Patch Antenna Using Sensitivity Analysis and Taguchi's Method

Ko, Jae-Hyeong; Byun, Jin-Kyu; Park, Jun‐Seok; Kim, Hyeong-Seok

doi:10.1109/tmag.2010.2081663

Cited by 25 publications

(11 citation statements)

References 7 publications

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“…To accomplish variance estimation given in (6), extra sets of samples are needed to bring in. There is no doubt that there are many ways to rearrange the samples based on (6). The basic principal is holding the variable to be studied in the original place while changing the sequences of the other terms.…”

Section: Proposed Optimization Using Variance Decomposition Methodsmentioning

confidence: 99%

“…A number of robust optimization methods have been proposed to be applied to electromagnetic devices [2][3][4][5][6]. A large part of the optimization approaches use the gradient index (GI) of parameters to represent the robustness due to its simplicity and low computational cost [7].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the values obtained from SA are modified utilizing Taguchi's quality method (TM) to improve the accuracy in Ref. [6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Robust Optimization Method Utilizing the Variance Decomposition Method for Electromagnetic Devices

Wang¹,

Li²,

Chen³

2014

Journal of Magnetics

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Uncertainties in loads, materials and manufacturing quality must be considered during electromagnetic devices design. This paper presents an effective methodology for robust optimization design based on the variance decomposition in order to keep higher accuracy of the robustness prediction. Sobol' theory is employed to estimate the response variance under some specific tolerance in design variables. Then, an optimal design is obtained by adding a criterion of response variance upon typical optimization problems as a constraint of the optimization. The main contribution of this paper is that the proposed method applies the variance decomposition to obtain a more accurate variance of the response, as well save the computational cost. The performance and robustness of the proposed algorithms are investigated through a numerical experiment with both an analytic function and the TEAM 22 problem.

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Section: Proposed Optimization Using Variance Decomposition Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Robust Optimization Method Utilizing the Variance Decomposition Method for Electromagnetic Devices

Wang¹,

Li²,

Chen³

2014

Journal of Magnetics

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“…For the smaller-thebetter characteristics case, which resembles performance minimization, the SN ratio is calculated by [2] SN ratio = 10log(MSD) − ,…”

Section: Sensitivity Analysismentioning

confidence: 99%

Optimal Design of a Planar-Type Antenna with a Reduced Number of Design Parameters Using Taguchi Method and Adaptive Particle Swarm Optimization

Lee¹,

Jang²,

Kim³

2014

Journal of Electrical Engineering and Technology

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-This paper presents a method to optimize the design of a planar-type antenna and reduce the number of design parameters for rapid computation. The electromagnetic characteristics of the structure are analyzed, and Taguchi method is used to identify critical design parameters. Adaptive particle swarm optimization, which has a faster convergence rate than particle swarm optimization, is used to achieve the design goal effectively. A compact dual-band USB dongle antenna is tested to verify the advantage of the proposed method. In this case, we can use only five selected geometrical parameters instead of eighteen to accelerate the optimization of the antenna design. The 10 dB bandwidth for return loss ranges from 2.3 GHz to 2.7 GHz and from 5.1 GHz to 5.9 GHz, covering all the WiBro, Bluetooth, WiMAX, and 802.11 b/g/n WLAN bands in both simulation and measurement. The optimization process enables the antenna design to achieve the required performance with fewer design parameters.

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“…Therefore, noise factors such as tolerance levels should be considered in the design of an antenna. Taguchi's method (TM) is a well-known technique which can be used to find a robustly optimized condition against such noise factors [2]. Moreover, a method which is realized on the basis of an orthogonal array (OA) can dramatically reduce the time required to design the antenna [3].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Robust Optimization for the Design of a Smartphone Metal Frame Antenna

Lee

Hwang

et al. 2018

International Journal of Antennas and Propagation

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Hybrid robust optimization that combines a genetical swarm optimization (GSO) scheme with an orthogonal array (OA) is proposed to design an antenna robust to the tolerances arising during the fabrication process of the antenna in this paper. An inverted-F antenna with a metal frame serves as an example to explain the procedure of the proposed method. GSO is adapted to determine the design variables of the antenna, which operates on the GSM850 band (824-894 MHz). The robustness of the antenna is evaluated through a noise test using the OA. The robustness of the optimized antenna is improved by approximately 61.3% relative to that of a conventional antenna. Conventional and optimized antennas are fabricated and measured to validate the experimental results.

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Robust Design of Dual Band/Polarization Patch Antenna Using Sensitivity Analysis and Taguchi's Method

Cited by 25 publications

References 7 publications

A Robust Optimization Method Utilizing the Variance Decomposition Method for Electromagnetic Devices

A Robust Optimization Method Utilizing the Variance Decomposition Method for Electromagnetic Devices

Optimal Design of a Planar-Type Antenna with a Reduced Number of Design Parameters Using Taguchi Method and Adaptive Particle Swarm Optimization

Hybrid Robust Optimization for the Design of a Smartphone Metal Frame Antenna

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