Non-linear PID Controller Optimization using the Artificial Bee Colony Algorithm Applied to a Small-Scale Pasteurization Plant

This paper investigates the performance of the artificial bee colony (ABC) algorithm as an alternative to finding the best optimal gain parameters for a nonlinear proportional-integral-derivative (NLPID) controller applied to the heat control in a nonlinear pasteurization process. Comparisons between a traditional PID and the NLPID optimized by ABC were carried out in terms of setpoint step changes. The experimental results reveal that the ABC-based tuned NLPID controller provides better tracking of the nonlinear dynamical system concerning convergence time, perturbation rejection, and a smoother and shorter duration of the control action. Therefore, these results demonstrate that the ABC algorithm can be used as an alternative to facilitate the tuning of the nonlinear parameters of NLPID controllers.