参数未知四旋翼无人机抗阵风自适应反步控制
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齐齐哈尔大学

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TP273

基金项目:

国家自然科学基金项目(71803095);黑龙江省自然科学基金项目(LH2024G014);黑龙江省省属本科高校基本科研业务费面上项目(145409320).


Adaptive backstepping control for quadrotor UAV with unknown parameters against gusts
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National Natural Science Foundation of China ( 71803095); Natural Science foundation of Heilongjiang Province (LH2024G014); Fundamental Research Funds in Heilongjiang Provincial Universities (145409320).

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    摘要:

    针对四旋翼无人机系统陀螺效应因子与风阻系数未知, 且在实际轨迹跟踪过程中易受阵风干扰的问题, 提出了一种具有参数自适应和干扰估计的反步控制算法. 首先, 对四旋翼无人机的数学模型进行分析, 将其转化为带有阵风干扰的严格反馈形式, 并利用已知参数和状态变量误差分别设计陀螺效应因子和风阻系数的自适应学习律; 其次, 利用自适应律实时得到的参数值, 结合位姿跟踪误差及其导数分别设计位姿环的干扰估计器, 用于在控制输入中补偿阵风扰动; 然后, 利用未知参数的自适应值和阵风扰动估计值设计出反步控制算法, 并基于Lyapunov稳定性理论, 对无人机的位置环和姿态环的渐近稳定性进行了严格证明. 研究结果表明, 所提算法在部分参数未知和阵风干扰情况下能够使无人机精确跟踪期望轨迹, 增强了无人机的抗干扰性. 最后, 通过仿真实验进一步验证了所提方法的有效性.

    Abstract:

    Aiming at the unknown gyroscopic factors and drag coefficients of the quadrotor UAV system, and it is prone to be disturbed by gusts during the actual trajectory tracking process, a backstepping control with parameter adaptation and disturbance estimation is designed. Firstly, the mathematical model of the UAV is analyzed, the model is transform into a strict feedback format with gusty wind interference. And based on the known parameters and state variable errors, the adaptive learning laws for the gyroscopic factors and the drag coefficients are respectively designed. Secondly, using the parameter values obtained in real time through the adaptive law, and combining the tracking errors of position and attitude as well as their derivatives, the disturbance estimators for the position loop and the attitude loop are respectively designed, the estimated values are used to compensate for the gust disturbances in the control input. Then, a backstepping control algorithm is designed using the adaptive values of the unknown parameters and the estimated values of the gust disturbances. Based on the Lyapunov stability theory, the asymptotic stability of the position loop and attitude loop of UAV has been rigorously proven. The research results show that the proposed algorithm can enable the UAV to precisely follow the desired trajectory and enhance the anti-interference capability of UAV, when some of UAV parameters are unknown and when it is affected by gusts of wind. Finally, the effectiveness of the proposed method was further verified by simulations.

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  • 收稿日期:2025-08-02
  • 最后修改日期:2026-03-09
  • 录用日期:2026-03-10
  • 在线发布日期: 2026-03-31
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