State variable filter design using Particle Swarm Optimization

Abstract

Having the advantage of being very simple in concept, easy to implement and computationally efficient, Particle Swarm Optimization (PSO) algorithm is a powerful evolutionary computation tool for electronic circuit design. In this work, usage of PSO algorithm in analog active filter design is investigated. For this purpose, the performance of the algorithm has been tested on the design of a 2nd order state variable low pass active filter. PSO algorithm both minimizes the design error and estimates the component values that are compatible with either E24 or E96 series. Compared to conventional design procedure, PSO achieved smaller design error and provides a maximally flat response in the pass band.