Performance comparison of Genetic Algorithm and Artificial Bee Colony Algorithm in optimizing controller parameters of a flexible manipulator

Abstract

Optimization is about finding the most suitable solution among all feasible solutions. For this purpose, many metaheuristic algorithms have been developed. Genetic Algorithm (GA) and Artificial Bee Colony (ABC) Algorithm are two popular algorithms developed for this purpose. Metaheuristic algorithms are also used in the optimization of controller parameters for flexible manipulators. In this study, parameter optimization was performed with GA and ABC Algorithms for a flexible manipulator controller. For the first comparison, the optimizations are repeated with different number of cycles, and for the second comparison, the simulations are repeated with different search space boundaries. Obtained results were compared over transient responses, maximum end point oscillations and required maximum torque values.