Optimization of a 12.5 GHz Microstrip Antenna Array Using Taguchi's Method

Spasos, M.; Nilavalan, R.; Tsiakmakis, K.; Charalampidis, Nikolaos; Cheung, SW

doi:10.1155/2011/458569

Cited by 14 publications

(6 citation statements)

References 14 publications

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“…The 5x5 microstrip antenna configuration is shown in Figure 4. Spasos et al (2011) proposed this configuration. For simplicity, the array was formed as a planar array with one feed point and each patch are connected by a serial feed line.…”

Section: Problem Formulationmentioning

confidence: 99%

“…This implies that we may need more data points and different training approach or network architecture in order to improve the accuracy of the RBF which will be included in our future work. Spasos et al (2011) proposed a 12.5 GHz microstrip antenna array synthesis using Taguchi's method, with interconnected elements in order to achieve good matching (S11 < -10 dB) without using any matching networks and high gain, suitable for the 12.5 GHz broadcasting satellite service frequency bands. It was claimed to be the current state-of-the-art in this technical field.…”

Section: By 5 Microstrip Antenna Arraymentioning

confidence: 99%

“…The extreme solutions of each run will be compared. The solution with the highest gain will be the winner, and compared with results from Spasos et al (2011).…”

Section: Decision Vectormentioning

confidence: 99%

See 2 more Smart Citations

5 by 5 Microstrip Antenna Array Design by Multiobjective Differential Evolution based on Fuzzy Performance Feedback

Jariyatantiwait

Yen

2016

International Journal of Swarm Intelligence Research

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Differential evolution is often regarded as one of the most efficient evolutionary algorithms to tackle multiobjective optimization problems. The key to success of any multiobjective evolutionary algorithms (MOEAs) is maintaining a delicate balance between exploration and exploitation throughout the evolution process. In this paper, the authors develop an Improved version of the Fuzzy-based Multiobjective Differential Evolution (IFMDE) that exploits performance metrics, specifically hypervolume, spacing, and maximum spread, to measure the state of the evolution progress. They apply the fuzzy inference rules, derived from domain knowledge, to these metrics in order to dynamically adjust the associated control parameters of a chosen mutation and crossover strategy used in this algorithm. One mutation parameter controls the degree of greedy or exploitation, while another regulates the degree of diversity or exploration of the reproduction phase. On the other hand, crossover rate controls the fraction of trial vector elements inherited from the mutant vectors. In doing so collectively, the authors can appropriately adjust the degree of exploration and exploitation through performance feedback. A 5 by 5 microstrip antenna array design problem is formulated as a three-objective optimization problem. The proposed IFMDE is applied to tackle this problem under real-world complications. Since the objective evaluations of a 5 by 5 microstrip antenna array are computationally very expensive, a radial basis function neural network is trained as a surrogate model for the fitness function approximations. The experimental results demonstrate the ability of IFMDE that it can find not only one, but a set of Pareto optimal solutions, specifically in terms of side lobe level and reflection coefficient. These multiple Pareto-optimal configurations can then be chosen from by a decision maker given dynamic operating environments, constraints and uncertainties.

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Section: Problem Formulationmentioning

confidence: 99%

Section: By 5 Microstrip Antenna Arraymentioning

confidence: 99%

See 1 more Smart Citation

5 by 5 Microstrip Antenna Array Design by Multiobjective Differential Evolution based on Fuzzy Performance Feedback

Jariyatantiwait

Yen

2016

International Journal of Swarm Intelligence Research

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“…However, it is rare to come across the DoE approach in RF/microwave engineering studies, where parametric studies are intensive such as design of filter, antenna, and resonator [8], [9]. For this microwave DoE study, a resonator, one of the most practiced devices in RF applications, was chosen.…”

Section: Introductionmentioning

confidence: 99%

Analysis of an inverted square SRR via design of experiment (DoE) approach

Yarici

Öztürk

2021

Journal of Electrical Engineering

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A design of experiment (DoE) study is presented based on an investigation of the influences of the chosen geometric parameters of an Inverted Square Split Ring Resonator on its resonance frequency. A statistical software was used to determine DoE steps and the values of chosen geometrical parameters for the experiments. The determined experiments were carried out by making simulations with electromagnetic design software. The resonator simulation outputs were analyzed by using normality tests and tools of the statistical software. By using these analyses, mainly a 2-level full factorial DoE approach, the effects of the geometrical parameters (input factors), and their interactions on the resonance frequency (response factor) were presented. In the light of our findings, this study proposes a promising path for microwave studies with several advantages such as being able to understand the dynamics of an optimized RF resonator device system, designing these kinds of devices with a few experiments, and increasing the time efficiency via reducing the number of attempts.

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“…ey also exhibited the examples of linear antenna array synthesis and proved the feasibility of the method [6]. Since then, the Taguchi method has also been widely used in the electromagnetics community, such as null realization in the specific directions of array synthesis [7,8], sidelobe optimization in the circular phased array [9], array synthesis of the conformal antenna [10], and performance optimization of the elements and arrays [11][12][13][14][15]. We know that the pattern synthesis of linear arrays can be achieved by using several other optimization methods like particle swarm optimization (PSO) [16], genetic algorithm (GA) [17], convex optimization (CO) [18], and so on; therefore, comparisons between the Taguchi method and some other optimization algorithms are necessary.…”

Section: Introductionmentioning

confidence: 99%

An Improved Taguchi Algorithm Based on Fitting and Prediction for Linear Antenna Array Synthesis

Cheng

Peng

2019

International Journal of Antennas and Propagation

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In this paper, a Taguchi method based on fitting and prediction is proposed to accelerate the optimization process in antenna array synthesis. The implementation procedure combines the normal Taguchi method and the curve fitting technique. A possible solution is determined by prediction based on fitting curves. Specifically, the fitting curves are obtained by using the dynamic points calculated and updated as the Taguchi method progress and recorded in the response table necessarily produced in the procedure. Test functions are used for conducting some confirmation experiments, and the results verify the validity of the proposed method. In order to illustrate its good practicability, two linear antenna arrays with a null controlled pattern and a flat top pattern, respectively, are successfully optimized by using both of the normal Taguchi method and the proposed one. Some comparisons and discussions of their results are given in the paper, which proves that the proposed method has a better practicability, not only because it inherits the global optimization characteristics of the normal Taguchi method but also because it accelerates the convergence process.

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Optimization of a 12.5 GHz Microstrip Antenna Array Using Taguchi's Method

Cited by 14 publications

References 14 publications

5 by 5 Microstrip Antenna Array Design by Multiobjective Differential Evolution based on Fuzzy Performance Feedback

5 by 5 Microstrip Antenna Array Design by Multiobjective Differential Evolution based on Fuzzy Performance Feedback

Analysis of an inverted square SRR via design of experiment (DoE) approach

An Improved Taguchi Algorithm Based on Fitting and Prediction for Linear Antenna Array Synthesis

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