Vortex search algorithm for the analog active filter component selection problem
Optimal selection of passive components is one of the most crucial design steps in analog active filter design problems. As the number of possible combinations increases, it becomes infeasible to perform an exhaustive search for optimum component values. Thus, intelligent algorithms are required for a fast and optimum selection of the passive component values. In this study, a newly proposed metaheuristic, the vortex search (VS) algorithm, is utilized for this purpose. To evaluate the performance of the VS algorithm, two different analog active filter topologies, the fourth-order Butterworth low-pass filter and the state variable low-pass filter, are used. The component values of the active filter topologies are selected within three different series of (E12, E24 and E96) passive components for both the resistors and the capacitors. The results are compared to other metaheuristics such as the particle swarm optimization (PSO2011), artificial bee colony (ABC), differential evolution (DE) and harmony search (HS) algorithms. It is shown that, the VS algorithm finds the minimum fitness values for both of the active filter topologies which in turn provides the optimum component values for each of the used component series.
vortex search algorithm component selection optimization analog active filter design