PSO-Optimized Fractional Order Sliding Mode Control for Quadrotor Trajectory Tracking with Robust 3D Visualization under Realistic Disturbances

This paper presents a novel approach to trajectory tracking for quadrotor unmanned aerial vehicles (UAVs) by integrating Particle Swarm Optimization (PSO) with Fractional Order Sliding Mode Control (FOSMC). Unlike classical sliding mode schemes, the proposed FOSMC leverages fractional-order derivatives to enrich the controller’s memory and improve chattering attenuation. A PSO-only implementation is employed to tune fifteen key control and fractional parameters—spanning position gains, attitude gains, and fractional orders— subject to multi-objective fitness criteria that explicitly balance trajectory error, settling time, control effort, and robustness against disturbances. To validate performance, two representative flight scenarios (sinusoidal and high-frequency) are tested under both ideal and disturbed conditions, including moderate wind gusts (5.0 m/s), translational perturbations (0.5 m/s², 5.1% of gravity), rotational disturbances (0.05 rad/s²), and measurement noise (0.01 m). Extensive simulation results and Lyapunov stability analysis with constructive gain selection procedure demonstrate that the PSO-optimized FOSMC achieves up to 84.8% reduction in RMS tracking error in disturbed conditions and maintains excellent robustness with average 1.45% performance degradation. Additionally, comprehensive 3D trajectory visualizations, time-series plots, and Lyapunov analysis illustrate enhanced disturbance rejection, control smoothness, and stability.