Akademik Veri Yönetim Sistemi
12th International Conference on Automation, Robotics and Applications, ICARA 2026, İstanbul, Türkiye, 5 - 07 Şubat 2026, ss.505-510, (Tam Metin Bildiri)
The gains of a quadcopter controller significantly affect overall control performance. In this study, the controller performance is improved by optimizing the control gains using the Multi-Objective Grey Wolf Optimization (MOGWO) algorithm. Since the quadcopter exhibits dynamics operating at different rates, a cascade controller structure is implemented and optimized using a multi-objective cost function based on four performance criteria. During the optimization process, 25 Paretooptimal solutions are obtained, and all simulations are conducted in the MATLAB & Simulink environment. The Pareto-optimal solutions reveal clear trade-offs among tracking error, thrust, and torque. Moreover, the Pareto analysis indicates correlations among the performance criteria, and a negative correlation is observed between tracking error and thrust-torque values. With the optimized gains, the quadcopter successfully follows a three-dimensional (3D) trajectory generated by a minimumsnap trajectory generator, achieving a total integrated squared error (ISE) of 0.2381. These results demonstrate that multiobjective optimization is an effective approach for quadcopter control under aggressive trajectories.