Modeling and Designing a Genetically Optimized PID Controller for Separately Excited DC Motor

This paper presents an intelligent method to design a proportional-integral-derivative (PID) controller to control the speed of a separately excited DC motor (SEDCM). There are various artificial intelligent (AI) based proposed methods for tuning the parameters of a PID controller. Genetic Algorithm is a powerful optimization tool used to optimize several parameters from the given population based on natural evolution. The purpose of this paper is to obtain the suitable speed characteristics of a SEDCM by optimizing the transient response i.e. by minimizing the settling time, overshoot and the rise time using genetic algorithm (GA). In this method, integral of absolute error (IAE) is taken as the cost function. The GA optimized PID controller shows better performance with respect to settling time, rise time and percentage of overshoot than other conventional methods and adaptive fuzzy PID controller.