Research on Trajectory Tracking Control of Inspection UAV Based on Real-Time Sensor Data

Area of Science:

• Control Engineering
• Robotics
• Aerospace Engineering

Background:

• Unmanned aerial vehicles (UAVs) are crucial for power inspection tasks.
• Environmental factors like wind gusts introduce uncertainties, affecting UAV trajectory stability.
• Existing control algorithms may struggle with the nonlinear and under-driven characteristics of inspection UAVs.

Purpose of the Study:

• To propose a sliding mode adaptive robust control algorithm for inspection UAVs.
• To address trajectory deviations caused by environmental uncertainties and system nonlinearities.
• To enhance the accuracy and robustness of UAVs in power inspection missions.

Main Methods:

• Design of a double closed-loop control system (position and attitude loops).
• Application of Lyapunov stability analysis to ensure asymptotic stability.
• Comparison with sliding-mode PID control and backstepping control algorithms.
• Implementation on a PX4-based experimental platform for outdoor testing.

Main Results:

• The proposed sliding mode adaptive robust control achieves higher trajectory tracking accuracy.
• Sliding mode PID control demonstrates good accuracy with lower computational cost.
• The control strategy effectively mitigates nonlinear interference and wind gust effects.
• Experimental validation confirms the algorithm's effectiveness and superiority.

Conclusions:

• The developed sliding mode adaptive robust control algorithm significantly improves UAV trajectory tracking.
• The control system offers a robust solution for power inspection UAVs operating in uncertain environments.
• The findings highlight the potential for enhanced efficiency and safety in automated infrastructure inspection.