Optimal selection of components in a sixth-order butterworth low-pass filter with using grey wolf algorithm

Abstract

Selection of the appropriate components is the most crucial step in active filter design. A number of possible combinations can affect the working mechanism of the circuit as a good direction or bad direction. Therefore there are many searching algorithms. These algorithms vary from each other by the feature of requiring a fast and optimal selection of component values. In this study Grey Wolf Colony Search Algorithm (GWA) is used for utilizing the performance of the circuit. GWA imitates the intelligent predatory manner of the wolf colony to solve optimization problem. To evaluate the performance of the algorithm a sixth-order Butterworth Low-Pass filter is used. It is shown that GWA finds the optimal component values with the minimum cost function when compared with the reference filter's values.