International Journal of Control, Automation, and Systems 2024; 22(10): 3191-3201
https://doi.org/10.1007/s12555-024-0207-7
© The International Journal of Control, Automation, and Systems
This paper studies the learning-based finite-time distributed formation control problem for a group of fixed-wing unmanned aerial vehicles (UAVs). Using position information obtained from sensors, a novel learningbased finite-time distributed controller with a saturation function is developed. Firstly, a six-degree-of-freedom fixed-wing UAV model is established and transformed into a double-integrator model using linear feedback linearization. For practical implementations, the velocities and overloads of the controlled fixed-wing UAVs are constrained within desirable limits by injecting appropriate saturations into the loops. The finite-time formation control objective is demonstrated if the connectivity topology meets the spanning tree criterion. The Lyapunov theory is used as a fundamental tool to guarantee the stability of the closed-loop system. Furthermore, an improved learningbased finite-time distributed control scheme is proposed to obtain the approximately optimal control laws for the error systems. Finally, two numerical examples are employed to verify the theoretical results.
Keywords Distributed control, finite-time, fixed-wing unmanned aerial vehicles, saturation function.
International Journal of Control, Automation, and Systems 2024; 22(10): 3191-3201
Published online October 1, 2024 https://doi.org/10.1007/s12555-024-0207-7
Copyright © The International Journal of Control, Automation, and Systems.
Liming Sui and Zhenghong Jin*
Zhejiang University
This paper studies the learning-based finite-time distributed formation control problem for a group of fixed-wing unmanned aerial vehicles (UAVs). Using position information obtained from sensors, a novel learningbased finite-time distributed controller with a saturation function is developed. Firstly, a six-degree-of-freedom fixed-wing UAV model is established and transformed into a double-integrator model using linear feedback linearization. For practical implementations, the velocities and overloads of the controlled fixed-wing UAVs are constrained within desirable limits by injecting appropriate saturations into the loops. The finite-time formation control objective is demonstrated if the connectivity topology meets the spanning tree criterion. The Lyapunov theory is used as a fundamental tool to guarantee the stability of the closed-loop system. Furthermore, an improved learningbased finite-time distributed control scheme is proposed to obtain the approximately optimal control laws for the error systems. Finally, two numerical examples are employed to verify the theoretical results.
Keywords: Distributed control, finite-time, fixed-wing unmanned aerial vehicles, saturation function.
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