Quadrotor Robust Fractional-Order Control Based on a Recent Bonobo Optimization Algorithm

In recent years, quadrotors have emerged as essential roles in robotics, and their diversity and usefulness emphasize their importance. This research work presents an in-depth analysis of a quadcopter in terms of modeling, control, and optimization, where central to the operation of quadcopters and all robotics systems is the idea of stability response. This paper discusses the possibility of providing quadcopter stability by demonstrating the impact of the fractional controller in sensitive systems. The five fractional parameters for each engine are also improved using the Bonobo Optimization (BO) algorithm. The optimized results in this paper are compared with the algorithms used, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). The fractional-order proportional integral derivative (FOPID) controller has greater control power compared to its classic counterpart, PID control, as it provided improvement in minimizing overshoot by 90%, and it showed great improvement in settling and rising times using GWO 25% and BO 50% with some superiority of BO. By examining both the advantages and constraints inherent in these methodologies, we seek to advance the field forward, promoting more breakthroughs in this crucial area.