Application of genetic algorithms in the design of robust active filters

This paper presents a genetic algorithm (GA) based method for designing two second-order active filters, proposed as cases of study. The GA must determine the values of the passive components (resistors and capacitors) of each filter in order to obtain a configuration that minimizes the sensitivity to variations of the same and also presents design errors minor to a defined maximum value, with respect to certain specifications. The optimization problem to be addressed by the GA is a multiobjective optimization problem. In both cases of study, the algorithm runs considering two possible scenarios with respect to the component values. The results show that the GA can get in both situations filter configurations that meet the established criteria.