Tuning PID Controllers Using Artificial Intelligence Techniques Applied To DC-Motor and AVR System

Abstract

This paper investigates PID controller tuning using genetic algorithm, modified genetic algorithm and particle swarm optimization techniques. The proposed techniques are compared to PID controllers tuned by the Ziegler-Nichols technique. Closed-loop simulations are conducted using MATLAB and the genetic algorithm toolbox for two applications, a DC-Motor and an Automatic Voltage Regulator (AVR). The overshoots, rise time and settling time with the proposed techniques are shown to be better than those of the conventionally tuned PID controllers.