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Performance comparison of Differential Evolution, Genetic Algorithm and Particle Swarm Optimization in impedance matching of aperture coupled microstrip antennas

机译:孔径耦合微带天线阻抗匹配中差分演化,遗传算法和粒子群优化的性能比较

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Microstrip antennas are most widely used nowadays for microwave applications because of their numerous advantages like small size and weight, conformability, compatibility with microwave integrated circuits etc. The aperture coupled microstrip line feeding technique has many advantages like availability of a large number of adjustable parameters in the form of aperture length, width and stub parameters. Design of aperture coupled microstrip antennas using a recently developed very fast optimization algorithm namely Differential Evolution [1] is proposed in this paper. The optimization algorithm is used to determine the dimensions as well as the transmission line feed positions for optimum matching over a given range of frequencies and substrate. For use of Differential Evolution in the optimal design of aperture coupled microstrip antennas, the fitness function is evaluated using the Method of Moments technique implemented through IE3D. In addition optimal design of the antenna using other conventional optimization techniques like real coded Genetic Algorithm and Particle Swarm Optimization are done and the results and performances are compared with those obtained by Differential Evolution (DE).
机译:现在,微带天线最广泛地使用微波应用,因为它们具有小尺寸和重量,适应性,与微波集成电路等的众多优点。孔径耦合微带线馈送技术具有许多可调节参数的可用性等优点孔径长度,宽度和短截线参数的形式。使用最近开发的非常快速优化算法的光圈耦合微带天线即表示差分演进[1]。优化算法用于确定尺寸以及传输线馈送位置,以在给定范围的频率和基板上最佳匹配。为了在孔径耦合微带天线的最佳设计中使用差分演进,使用通过IE3D实现的矩技术方法来评估适合功能。此外,使用其他常规优化技术的天线的最佳设计进行了实际编码的遗传算法和粒子群优化,并将结果和性能与差分演进(DE)相比进行了比较。

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