引用本文:费爱玲,李柠,李少远.固定翼无人机的自抗扰反步控制[J].控制理论与应用,2016,33(10):1296~1302.[点击复制]
FEI Ai-ling,Li Ning,Li Shao-yuan.Active disturbance rejection back-stepping control of fixed-wing unmanned aerial vehicle[J].Control Theory and Technology,2016,33(10):1296~1302.[点击复制]
固定翼无人机的自抗扰反步控制
Active disturbance rejection back-stepping control of fixed-wing unmanned aerial vehicle
摘要点击 3297  全文点击 2217  投稿时间:2015-12-23  修订日期:2016-10-12
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/CTA.2016.51006
  2016,33(10):1296-1302
中文关键词  固定翼无人机  姿态控制  速度控制  扩张状态观测器  反步法  四元数
英文关键词  fixed-wing unmanned aerial vehicle (UAV)  attitude control  velocity control  extended state observer (ESO)  back-stepping control  quaternion
基金项目  国家自然科学基金项目(61374109, 61304078, 61590925), 国家“973”计划项目(2013CB035500), 国家“863”计划项目(2015AA043102)资助.
作者单位E-mail
费爱玲 上海交通大学 falfsm@sjtu.edu.cn 
李柠* 上海交通大学 ning_li@sjtu.edu.cn 
李少远 上海交通大学  
中文摘要
      针对固定翼无人机姿态和速度控制中系统存在模型不确定性和外界扰动的情况, 本文设计了基于扩张状 态观测器的反步控制器抑制系统扰动以提高无人机的控制性能. 首先建立无人机速度误差模型和姿态误差模型, 其 中姿态误差模型采用四元数作为变量以避免欧拉角在描述姿态时存在的奇点问题和复杂三角运算; 进而设计扩张 状态观测器对系统中存在的扰动进行估计, 并将扰动估计值与控制器设计相结合, 分别设计出姿态控制器和速度控 制器来抑制扰动的影响且使无人机姿态和速度收敛到期望值. 最后基于李雅普诺夫理论证明系统的稳定性. 仿真 结果表明, 本文所设计方法能够抑制系统中存在的扰动.
英文摘要
      In this paper, attitude and velocity control problem of fixed-wing unmanned aerial vehicle (UAV) are investigated. In order to deal with model uncertainties and external disturbances, extended state observer (ESO) based on back-stepping controllers are designed to depress system disturbances so that system performance could be improved. Firstly, the velocity error model and attitude error model of fixed-wing UAV are established. Among that process quaternion is adopted to be attitude error model variables to avoid singularity and complex trigonometric operation when describing UAV attitude with euler angle. Then extended state observers are designed to estimate system disturbance. The estimated values are included in controller design procedure to depress system disturbances and ensure that attitude and velocity of fixed-wing UAV converge to the desired value. Lastly, system stability is proven through Lyapunov theory. The simulation results demonstrate that proposed method is capable to depress system disturbance.