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Related Experiment Videos

Guidance Navigation and Control for Quadrotor UAV Using Lyapunov-Based Backstepping.

Jurek Z Sasiadek1, Ammar Shuker1, Malik M A Al-Isawi1

  • 1Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON K1S5B6, Canada.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

A new Lyapunov-based backstepping (LYP) controller offers superior control for quadrotor unmanned aerial vehicles (UAVs). It outperforms Proportional-Integral-Derivative (PID) and Fractional-Order PID (FOPID) controllers in robustness and tracking accuracy.

Keywords:
FOPIDPSObackstepping controllyapunov stabilityquadrotor UAV

Related Experiment Videos

Area of Science:

  • Robotics and Control Systems
  • Aerospace Engineering
  • Nonlinear Control Theory

Background:

  • Quadrotor unmanned aerial vehicles (UAVs) exhibit complex dynamics, including underactuation, strong coupling, and nonlinearities.
  • These characteristics, coupled with sensitivity to parameter uncertainties and external disturbances, pose significant control challenges.
  • Existing controllers like Proportional-Integral-Derivative (PID) and Fractional-Order PID (FOPID) may struggle with robust stability and precise trajectory tracking in challenging environments.

Purpose of the Study:

  • To develop and evaluate a robust Lyapunov-based backstepping (LYP) controller for quadrotor UAVs.
  • To ensure precise trajectory tracking and robust stability despite model uncertainties and external disturbances.
  • To compare the performance of the proposed LYP controller against PID and FOPID controllers.

Main Methods:

  • Implementation of a Lyapunov-based backstepping (LYP) controller with an inner- and outer-loop architecture for coupled position and attitude control.
  • Optimization of all controller gains using Particle Swarm Optimization (PSO).
  • Comparative performance analysis under nominal conditions, external disturbances, and model parameter uncertainties using time-domain metrics and Root Mean Square Error (RMSE).

Main Results:

  • The proposed LYP controller demonstrated superior robustness and improved tracking accuracy compared to PID and FOPID controllers.
  • Faster disturbance rejection capabilities were observed with the LYP controller.
  • Simulation results validated the effectiveness of the LYP controller in handling uncertainties and disturbances.

Conclusions:

  • The Lyapunov-based backstepping (LYP) controller provides a robust and effective solution for controlling underactuated quadrotor UAVs.
  • The LYP controller significantly enhances trajectory tracking precision and disturbance rejection capabilities.
  • This advanced control strategy offers a promising advancement for quadrotor UAV applications requiring high performance and reliability.