A hybrid genetic algorithm for analog active filter component selection

Abstract

Analog filters are circuits that process electrical signals on a frequency-dependent basis. Analog filter circuits can be implemented using resistors, capacitors and inductors and they can also be implemented with only resistors and capacitors with the use of active circuit equipments. The selection of optimum component values is difficult because of the number of possible filter combinations. This paper presents an effective algorithm that hybridizes the Genetic Algorithm (GA) to form a Hybrid Genetic Algorithm (HGA) and proposes the use of Tabu Search (TS) for the analog active filter component selection. The GA has a powerful global searching ability and so is used to perform exploitation and because TS also has good local searching ability, it too is applied to perform exploitation. Thus, the proposed HGA will have very good searching ability. In this study, a band-pass Sallen-Key filter circuit was used, and the filter component values were found using HGA with LabVIEW. The results are compared to other reported state-of-the-art algorithms, such as the artificial bee colony (ABC) and differential evaluation (DE) to demonstrate the effectiveness and efficiency of the developed method. It can be said that the developed LabVIEW based HGA gives satisfactory results with regard to amplitude response, the minimum fitness values and the computational time.