Backstepping-based adaptive control of a quadrotor UAV with guaranteed tracking performance

Area of Science:

• Robotics
• Control Systems Engineering
• Aerospace Engineering

Background:

• Quadrotor unmanned aerial vehicles (UAVs) require advanced control for stable flight and accurate trajectory tracking.
• Parametric uncertainties in inertia and drag significantly challenge attitude regulation in UAVs.
• Existing control methods may not fully guarantee both transient and steady-state performance.

Purpose of the Study:

• To propose novel indirect and direct adaptive control designs for quadrotor UAV trajectory tracking.
• To ensure bounded transient and steady-state tracking errors for lateral position and altitude dynamics.
• To compensate for parametric uncertainties in inertia and drag affecting attitude control.

Main Methods:

• Utilizing backstepping techniques combined with prescribed performance functions for error transformation.
• Implementing a least squares based parameter identification for indirect adaptive control.
• Employing a constructive Lyapunov analysis approach for direct adaptive control.
• Proving closed-loop system stability through rigorous Lyapunov analysis.

Main Results:

• Both proposed adaptive control designs demonstrate guaranteed transient and steady-state tracking performances.
• The control schemes effectively compensate for parametric uncertainties in inertia and drag.
• Simulation and experimental results validate the effectiveness of the developed control strategies.

Conclusions:

• The presented backstepping-based indirect and direct adaptive control schemes offer robust solutions for quadrotor UAV trajectory tracking.
• These methods ensure high tracking accuracy and stability even in the presence of system uncertainties.
• The findings contribute to the advancement of autonomous UAV navigation and control.