摘要
针对具有未知外部扰动和阻力系数的时变负载四旋翼无人机系统,提出了一种复合有限时间控制策略。首先,通过牛顿-欧拉方法建立了完整的四旋翼无人机数学模型。位置环采用自适应参数校正方法对负载进行估计,并与反步递推控制相结合,在阻力系数未知情况下设计了自适应轨迹跟踪控制器。其次,采用基于扰动观测器的有限时间滑模控制器,并利用Lyapunov稳定性理论进行无人机系统位置环和姿态环渐近稳定和有限时间稳定性验证。最后,通过数值仿真进行验证。结果表明,所提控制器提高了系统的收敛速度,减少了外界扰动对系统的影响。研究方法克服了已有研究要求阻力系数和负载已知的局限性,提高了系统的抗干扰能力,对于增强四旋翼无人机的实际应用性具有一定的参考价值。
For the quadrotor unmanned aerial vehicle(UAV)system with time-varying load,the compound finite-time control strategy was proposed in the presence of unknown external disturbances and unknown drag coefficients.Firstly,a complete mathematical model of quadrotor UAV was established by Newton-Euler method.An adaptive trajectory tracking controller with unknown drag coefficient was designed by combining the adaptive parameter correction method of position loop with backstepping control to estimate load.Then,a finite-time sliding mode controller and Lyapunov stability theory were used so that the position loop and the attitude loop were proved to be asymptotically stable and finite-time stable,respectively.Finally,it was verified by numerical simulation.The results show that the proposed controller improves the system convergence rate,and reduces the influence of outside disturbance to the system.This method overcomes the limitations of known drag coefficients and load in the existing research,improves the anti-interference ability of the system,and has certain reference value for enhancing the practical application of the quadrotor UAV.
作者
武晓晶
郑文棪
吴学礼
甄然
邵士凯
WU Xiaojing;ZHENG Wenyan;WU Xueli;ZHEN Ran;SHAO Shikai(School of Electrical Engineering,Hebei University of Science and Technology,shijiazhuang,Hebei 050018,China;Hebei Provincial Research Center for Technologies in Process Engineering Automation,Shijiazhuang,Hebei 050018,China)
出处
《河北科技大学学报》
CAS
北大核心
2021年第6期579-590,共12页
Journal of Hebei University of Science and Technology
基金
国家自然科学基金(62003129,61903122)
河北省研究生创新资助项目(CXZZSS2021098)
国防基础计划研究项目
河北省重点研发计划项目(19250801D)。
关键词
自动控制理论
四旋翼无人机
时变负载
扰动观测器
反步递推控制
滑模控制
automatic control theory
quadrotor unmanned aerial vehicle(UAV)
time-varying load
disturbance observer
backstepping control
sliding mode control
