Super-twisting adaptive control of a quadrotor

Area of Science:

• Robotics and Control Systems
• Aerospace Engineering
• Control Theory

Background:

• Unmanned Aerial Vehicles (UAVs) require robust control for reliable operation.
• Model uncertainties and external disturbances degrade trajectory tracking performance.
• Traditional sliding mode controllers suffer from chattering, impacting control precision.

Purpose of the Study:

• To develop a novel robust and adaptive control methodology for UAVs.
• To enhance trajectory tracking accuracy and system stability under uncertain conditions.
• To mitigate the chattering phenomenon inherent in sliding mode control.

Main Methods:

• Integration of a Super-Twisting Sliding Mode Controller (ST-SMC) with an adaptive control law.
• Real-time dynamic updating of control parameters to compensate for unmodeled dynamics.
• Lyapunov stability analysis to guarantee convergence and boundedness of control errors.

Main Results:

• The combined ST-SMC and adaptive law demonstrated superior trajectory tracking performance.
• Effective mitigation of the chattering phenomenon was achieved.
• Robustness to parametric uncertainties and external disturbances was validated through experimental flights.

Conclusions:

• The proposed hybrid control strategy offers a robust and high-performance solution for UAV trajectory tracking.
• The adaptive component effectively compensates for real-time system variations.
• Experimental validation confirms the synergistic benefits of the integrated control approach.