Optimizing Indoor Temperature Control Using Genetic Algorithm for PID Tuning

Abstract

This study was conducted to explore ways to save energy focusing on Temperature control through genetic algorithm (GA)based on the Proportional Integral Derivation controller (PID) to obtain the best PID gain parameters (kp, ki, kd) through which the settling time, steady state error, and overshoot are improved, which showed better performance than using traditional PID because of its fast and sharp control it provided. The best results for the parameters were using integrated time absolute error (ITAE)as a GA objective function where k [0.8598 0.0669 0]. However, by using Integrated of absolute error(IAE), the best results obtained were k [12.9765 0.2534 0], It is possible to improve system’s response from using traditional PID which is considered a long time (more than 25 seconds) as compared to the PID with Genetic algorithm(GA).

      The study showed that the best results were obtained using the IAE as an objective function for GA, as the system reached the stable state in the shortest possible time.