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Algorithms

New Research on Quadcopter Drones Offers Breakthrough Control Strategy

Strategic Insights

— 2 min read

Researchers at Nanjing University of Aeronautics and Astronautics have developed an integrated control strategy for quadcopter drones that enhances their tracking performance while resisting external wind disturbances. The innovative approach combines an optimization algorithm with fuzzy control, utilizing second-order Linear Active Disturbance Rejection Control (LADRC) controllers and fuzzy controllers. This system has been optimized using a modified crayfish optimization algorithm (MCOA), resulting in a dual-closed-loop control system that delivers exceptional tracking speed and accuracy.

Key Takeaways:

  • The proposed control strategy reduces the rise time by 52.87% in the X-channel under wind-free conditions compared to the dual-closed-loop LADRC controller.
  • The research concluded that the system reduces the maximum trajectory tracking error by 86.37% under wind-disturbed conditions compared to the dual-closed-loop fuzzy control LADRC controller.
  • The newly designed system demonstrates strong resistance to interference and stability, maintaining its performance even in the presence of external disturbances.
  • The quadcopter drone's ability to track a specified trajectory is enhanced by the integration of fuzzy logic and optimization algorithms, which reduce the maximum tracking error and improve overall stability.
  • The proof-of-concept study shows that the quadcopter drone can accurately track its target position and attitude angle, even in the presence of external wind disturbances.
  • The research has been optimized using a modified crayfish optimization algorithm (MCOA), which enhances the drone's performance and efficiency.
  • The control strategy has been implemented using a second-order Linear Active Disturbance Rejection Control (LADRC) controller, supplemented by fuzzy controllers.
  • The research was funded by the Natural Science Foundation of Jiangsu Province.

Statistics:

  • 52.87% reduction in rise time in the X-channel under wind-free conditions compared to the dual-closed-loop LADRC controller.
  • 86.37% reduction in maximum trajectory tracking error under wind-disturbed conditions compared to the dual-closed-loop fuzzy control LADRC controller.
  • 66.2% reduction in ITAE exponent, indicating improved stability and resistance to interference.
  • 20% improvement in tracking performance compared to traditional control strategies.

Sources:

  • "A Second-order Ladrc-based Control Strategy for Quadrotor Uavs Using a Modified Crayfish Optimization Algorithm and Fuzzy Logic," by Yalei Bai, Kelin Li, and Guangzhao Wang, published in Electronics, 2025;14(15).
  • Natural Science Foundation of Jiangsu Province.
  • Nanjing University of Aeronautics and Astronautics.
  • NewsRx. New Findings from Nanjing University of Aeronautics and Astronautics in Electronics Provides New Insights (A Second-order Ladrc-based Control Strategy for Quadrotor Uavs Using a Modified Crayfish Optimization Algorithm and Fuzzy Logic). Journal of Engineering. October 20, 2025; p 1835.

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