Surrogate Model Assisted Design of CSRR Structure using Genetic Algorithm for Microstrip Antenna Application
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Soft-computational approaches have enabled quicker and more efficient means for antenna design. In the present work, a genetic algorithm (GA) based method is reported for the design of complementary split ring resonator (CSRR) structures for antenna design. A multi-objective optimization problem is formulated to design the antenna. The cost function of the optimization problem is calculated from a surrogate model of the CSRR structure. The surrogate model is created first using an analytical model of the CSRR structure and then using an artificial neural network (ANN). A comparative study of the result shows that the ANN based surrogate model is more accurate compared to the surrogate model using an analytical model. An antenna with an integrated filter is built using a CSRR structure designed using the proposed method. The performance of the antenna is validated from simulation and measurement results.
KeywordsArtificial neural network, surrogate model, complementary split ring resonator, microstrip antenna, genetic algorithm, soft-computational design
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2020 vol. 29, č. 1, s. 117-124. ISSN 1210-2512
- 2020/1