The main objective of this work is to enhance tracking performance by systematically tuning PID parameters to minimize tracking errors, improve stability, and increase robustness against disturbances. In this extended study, the proposed nonlinear PID controller, tuned using the Artificial Bee Colony (ABC) algorithm, is further evaluated under sinusoidal reference tracking with an educational temperature control plant. The experimental results confirm that the ABC-tuned nonlinear PID achieves superior transient performance, reduced overshoot, and strong disturbance rejection. These findings demonstrate the controller’s effectiveness and reliability in both step-response and dynamic reference scenarios.