Optimal Component Value selection for Analog Active Filter Using Differential Evolution

Abstract

This paper presents an efficient approach of designing analog active filter by selecting its component value with an optimization method known as differential evolution. Differential evolution (DE) is one of the very fast and robust evolutionary algorithms, which has shown to have superior performance for continuous global optimization and uses differential information to guide its search direction. Differential Evolution serves the dual task of efficiently optimizing the component values as well as minimizing the total design error of a 4th order Butterworth low pass active filter. The component values of the Butterworth active filter are designed in such a way so that they are E12 series compatible. Differential Evolution proves itself to be a very good optimizing tool for selecting the components of the analog active filter. The simulation results prove the efficiency of using DE for the design of analog active filter by optimizing the component values as well as design error simultaneously.