Optimized PI Control Design for Balancing Bicopter using Multi-Criteria Crow Search Algorithm

Abstract

Abstract The multi-criteria crow search algorithm proposed in this paper is a novel optimization method designed to address the control and stability challenges faced by bicopter systems. Bicopters, unmanned aerial vehicles with two rotors to use energy more efficiently, require precise control to maintain balance and maneuverability. This optimization approach leverages the Crow Search Algorithm (CSA) and aims to achieve a balanced control system for bicopters while considering multiple objectives simultaneously. The key goal of this approach is to optimize the PI control parameters employed in the bicopter system to enhance stability and maneuverability, represented by settling time and overshoot in transient response. Through a combination of exploration and exploitation, the algorithm searches for an optimal set of control parameters that satisfies these criteria, striking a better control system that can benefit from improved stability and maneuverability. As shown from the experiment, this algorithm offers a promising avenue for designing control strategies that address the inherent challenges of bicopter systems, especially after being compared to the existing approaches.