采用粒子群算法的频率选择表面优化设计

Particle Swarm Optimization of Frequency Selective Surface

粒子群优化算法作为优秀的群体智能算法之一,已经被广泛应用于电磁优化问题中.通过与时域有限差分(FDTD)算法相结合,粒子群优化算法被运用于频率选择表面的优化设计.在此过程中,通过使用图形处理器(GPU)加速技术将FDTD算法速度提高近100倍,配合FDTD的宽频特性显著加速了优化过程.在此基础上,针对给定单元结构以及未知单元结构两种频率选择表面设计情况,分别采用带惯性权重的粒子群优化算法以及二进制离散粒子群优化算法进行优化.提出的两种优化流程在算例中得到验证与分析,证明了其可行性及高效性.

Particle swarm optimization（PSO） hasbeen successfully applied in the design andoptimization of electromagnetic structures.Combined with finite-difference time-domain（FDTD） technique,PSO algorithm was applied in the design of frequencyselective surfaces.Through theuse of graphics processing unit（GPU） acceleration,the FDTD program achieves about 100 times speedup while preserving the broad-band nature of the algorithm.Standard PSO and binary PSO algorithms were implemented to deal with known cell structure and unknown cell structure optimization respectively.The feasibility and efficiency of the proposed optimization scheme areverified by numerical results.