Optimizing Non-linear PID Control with Artificial Bee Colony for Temperature Regulation in a Control Plant Trainer

This paper presents an optimization framework for tuning nonlinear PID controllers using the Artificial Bee Colony (ABC) algorithm. The proposed approach aims to improve tracking performance by systematically tuning the PID parameters to minimize tracking errors, improve stability, and ensure robustness against system disturbances. A comparative study was conducted using conventional tuning strategies and alternative metaheuristic techniques for temperature control in a didactic control plant trainer to validate the effectiveness of the proposed method. Experimental results on non-linear benchmark processes demonstrate that the proposed approach achieves superior results in transient behavior, overshoot reduction, and disturbance rejection, highlighting its potential for advanced process control applications.