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Data Driven Model-Free Adaptive Control Method for Quadrotor Formation Trajectory Tracking Based on RISE and ISMC

Dongdong Yuan1, Yankai Wang1

  • 1School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China.

Sensors (Basel, Switzerland)
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PubMed
Summary
This summary is machine-generated.

This study introduces a data-driven, model-free adaptive control method for quadrotor formations, enhancing cooperative trajectory tracking. The approach ensures high accuracy and robustness without relying on complex UAV models.

Keywords:
data-driven model-free adaptive controlformation cooperative trajectory tracking controlimproved sliding mode controlquadrotor formationrobust integral of the signum of the error

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Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence
  • Aerospace Engineering

Background:

  • Quadrotor formation control faces challenges in complex dynamic modeling and parameter identification.
  • Existing methods often depend on accurate UAV kinematics and dynamics models, limiting adaptability.
  • Trajectory tracking for coordinated quadrotor formations requires robust and precise control strategies.

Purpose of the Study:

  • To propose a data-driven, model-free adaptive control method for quadrotor formation cooperative trajectory tracking.
  • To overcome limitations of traditional control methods that rely on detailed system models.
  • To enhance control accuracy, stability, and robustness in quadrotor formations.

Main Methods:

  • Utilized a leader-follower strategy with a robust integral of the signum of the error (RISE) controller for the leader's trajectory tracking.
  • Implemented a data-driven, model-free approach for both attitude (inner loop) and position (outer loop) control, using only input-output data.
  • Developed an improved sliding mode control (ISMC) for followers, incorporating adaptive update laws and saturation functions to eliminate model dependence and chattering.

Main Results:

  • The proposed method effectively achieves coordinated formation trajectory tracking for quadrotors.
  • Stability of the control system was rigorously proven using Lyapunov methods.
  • Numerical simulations and experimental results verified the algorithm's effectiveness, accuracy, stability, and robustness.

Conclusions:

  • The data-driven, model-free adaptive control method is highly effective for quadrotor formation cooperative trajectory tracking.
  • The controller design does not require prior knowledge of UAV kinematics and dynamics, offering significant practical advantages.
  • The approach demonstrates superior control accuracy, stability, and robustness, making it suitable for real-world applications.