Design of planar microwave filters using a simple FDTD model and particle swarm optimization

Evolutionary algorithms (EA), such as the genetic algorithm (GA), have found wide popularity because of their capability of global optimum search. As an answer to the quest for faster converging evolutionary algorithms, particle swarm optimization (PSO) was introduced to the electromagnetics domain (Robinson, J. and Rahmat-Samii, Y., IEEE Trans. Antennas Propag., vol.AP-52, no.2, p.397-407, 2004). PSO is a relatively new stochastic evolutionary computation technique, based on the movement and intelligence of swarms. PSO is found to hold a superior position with respect to other evolutionary methods, such as GA. Since PSO is a very recent method, many of its capabilities are still unexplored. It benefits from the inherent simplicity of GA while it converges much faster than conventional evolutionary algorithms. The paper presents a simple and universal design procedure for planar microwave filters. To accelerate the computation phase, an equivalent circuit topology is derived from FDTD formulation. The method is fast and robust and is well suited to the fast paced engineering design environment. As a case study, a microwave band-pass filter is designed.