Issue |
JNWPU
Volume 43, Number 2, April 2025
|
|
---|---|---|
Page(s) | 295 - 304 | |
DOI | https://doi.org/10.1051/jnwpu/20254320295 | |
Published online | 04 June 2025 |
Robust trajectory tracking control for quadrotor UAVs with time input saturation constraints
基于有限时间四旋翼无人机输入饱和鲁棒轨迹跟踪控制
1
School of Mechatronic Engineering, Xi'an Technological University, Xi'an 710021, China
2
School of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021, China
Received:
18
March
2024
Considering the trajectory tracking challenges faced by quadrotor UAVs during flight due to input saturation, external disturbances, uncertainties in system parameters, unmodeled dynamics, etc., a finite-time input saturation robust trajectory tracking control method is proposed. To address external disturbances, a nonlinear disturbance observer is employed for real-time estimation. System parameter uncertainties are approximated using neural networks. Input saturation in the system is handled by an auxiliary system. Finite-time controllers based on backstepping design are implemented in both position and attitude control loops to control the system. By utilizing Lyapunov stability theory, it is proven that all error signals in the closed-loop system are bounded and converge. Simulation results confirm that the proposed control algorithm ensures precise trajectory tracking by quadrotor UAVs in finite time, demonstrating strong robust performance.
摘要
考虑到四旋翼无人机在飞行中因输入饱和、外部干扰、自身参数不确定性和系统的未建模动态等引起的轨迹跟踪误差较大或难以控制问题, 提出了一种基于有限时间输入饱和鲁棒轨迹跟踪控制方法。针对外部干扰, 采用非线性干扰观测器对其进行实时估计; 针对系统自身参数不确定性, 采用神经网络对其进行逼近处理; 针对系统中的输入饱和, 采用辅助系统进行处理; 在位姿控制回路基于反步法设计有限时间控制器对系统进行控制。根据Lyapunov稳定性理论证明了闭环系统的所有误差信号有界且收敛。仿真实验表明所提出的控制算法能够保证四旋翼无人机在有限时间对轨迹的精确跟踪, 并且具备较强的鲁棒性能。
Key words: quadrotor UAVs / neural network / finite-time / disturbance observer / input saturation / trajectory tracking
关键字 : 四旋翼无人机 / 神经网络 / 有限时间 / 干扰观测器 / 输入饱和 / 轨迹跟踪
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