Dynamic Response Optimization for Quadrotor UAVs Using a Parameter Self-Tuning Fuzzy PID Control Method

To tackle the precision limitations of quadrotor drone control in challenging environments, researchers have developed an enhanced fuzzy PID hybrid control method. The inherent rigidity of conventional PID controllers, with their unadjustable gain parameters, proves inadequate for managing the nonlinear dynamics and time-varying operational conditions typical of UAV systems, often manifesting as sluggish transient responses and excessive oscillation amplitudes.To address this, the study designed a fuzzy PID controller with dynamically adjustable parameters based on the X-type quadrotor's dynamic model. The controller employs expert experience to formulate rules and optimizes control parameters in real-time through error feedback. In simulation experiments comparing traditional PID and cascade PID controllers, the improved algorithm demonstrated significant reductions in settling time (32% shorter), overshoot (45% lower), and enhanced dynamic response speed (40% faster angular rate tracking). Experimental results confirmed the fuzzy PID's superior performance in attitude tracking (1.20mean error) and disturbance rejection, particularly showing 0.2s faster convergence and 60% steadier state maintenance compared to conventional methods. This approach effectively combines fuzzy logic's adaptability with PID's robustness, providing a practical solution for high-precision UAV control in complex flight missions and variable environments.