Genetic algorithm-based PID parameters optimization for air heater temperature control

Abstract

The main problem on PID controller design is tuning its parameters in order to generate optimal systems performance. This paper applies Genetics Algorithms (GA) for tuning PID controller of an air heater. PID controller is used to control the output temperature of the air heater. A process model of the air heater is defined based on its open loop step response. Using this model, an offline PID parameters optimization based on GA is done. The chromosome in GA represents PID parameters namely proportional gain (Kp), integral gain (Ki), and derivative gain (Kd). The objective functions are settling time and overshoot. The experimental results show that the step response of this GA-based PID controller has superior performance than its using Ziegler Nichols tuning.