Surrogate Model Assisted Design of CSRR Structure using Genetic Algorithm for Microstrip Antenna Application
Kumaresh Sarmah, Sivaranjan Goswami, Sunandan Baruah
Abstract
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 accurate as compared to the surrogate model using an analytical approach. An antenna with an integrated filter is fabricated using a CSRR structure designed applying the proposed method. The performance of the antenna is validated from the simulation and measurement results.