Performance Comparison of Evolutionary Algorithms for Infrared Heating Control System

Abstract

This paper discusses the performance comparison of three successful evolutionary algorithms for temperature control of ceramic infrared heater. In numerous commercial as well as industrial applications, efficient temperature control becomes a fundamental task. Despite the fact ON-OFF control is the most straightforward control strategy, it is not effective for all the applications. To optimize the performance of this system, tuning parameters of PID controller are computed using evolutionary algorithms. System identification is performed first and then controllers are designed. Step test is used here to build the empirical model of infrared heater. The performances of classical PID designed using Z-N method and optimal PID controllers designed using particle swarm optimization (PSO), Differential Evolution (DE) and Artificial Bee Colony (ABC) evolutionary algorithms are compared through simulation results. To verify the simulation results, energy consumption is calculated by implementing the controllers using Arduino. DE tuned PID controller with ITAE is discovered to be an energy effective technique for temperature control of infrared heater with better settling time and peak overshoot.