Performance Evaluation of Metaheuristic Algorithms for Fractional-Order PID Controller Tuning in Non-Linear Systems

The use of metaheuristic algorithms has become very popular in recent years. One of their many applications is in tuning different controllers, especially those that would require extensive effort to tune manually. In some cases, due to the complexity of the controller, it is almost impossible to adjust the parameters manually. In this work, a fractional-order PID controller (FOPID) is used to control an inverted pendulum. This is a non-linear, multivariable, and underactuated system that requires advanced techniques to achieve robust control. Three different algorithms have been implemented to compare their performance in solving this problem. The algorithms used are a Genetic Algorithm (GA), an Artificial Bee Colony algorithm (ABC), and Black Widow Optimization (BWO). The controllers have been evaluated through extensive tests on a physical model of the inverted pendulum, proving the validity of the designs. Furthermore, after running the algorithms several times, optimal configurations for the parameters of each algorithm have been obtained.