引用本文:潘晓龙,鲜斌.小型无人直升机的无模型自适应鲁棒控制设计[J].控制理论与应用,2017,34(9):1171~1178.[点击复制]
PAN Xiao-long,BIN XIAN.Model-free adaptive robust control design for a small unmanned helicopter[J].Control Theory and Technology,2017,34(9):1171~1178.[点击复制]
小型无人直升机的无模型自适应鲁棒控制设计
Model-free adaptive robust control design for a small unmanned helicopter
摘要点击 2494  全文点击 1542  投稿时间:2017-01-14  修订日期:2017-05-04
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DOI编号  10.7641/CTA.2017.70029
  2017,34(9):1171-1178
中文关键词  无人直升机  数据驱动  无模型自适应控制
英文关键词  unmanned helicopter  data-driven control  model-free adaptive control
基金项目  天津市应用基础与前沿技术研究计划重点项目(14JCZDJC31900), 天津市科技支撑计划重点项目(15ZCZDGX00810), 天津市科技计划项目 (14RCHZGX00862), 国家自然科学基金项目(60804004, 90916004)资助.
作者单位E-mail
潘晓龙 天津大学  
鲜斌* 天津大学 xbin@tju.edu.cn 
中文摘要
      本文针对小型无人直升机的姿态控制问题, 考虑到现有基于模型的控制方法对系统动力学模型的依赖性, 以及未建模动态对系统控制性能的影响, 设计了一种新的基于数据驱动的无模型自适应鲁棒控制律. 通过基于数据 驱动的设计方法, 降低了控制器对直升机动力学模型先验知识的依赖, 补偿了未建模不确定性的影响. 仅利用无人 直升机的输入输出数据, 即可实现对无人直升机系统的稳定姿态控制. 然后本文结合离散滑模控制设计, 补偿了未 知外界扰动的影响, 提高了系统的鲁棒性, 并通过理论证明了控制误差的收敛性和闭环系统的稳定性. 最后, 在本研 究组自主开发的无人直升机飞行控制实验平台上, 进行了无人机实时控制实验. 实验结果表明, 本文所提出的控制 算法取得了很好的姿态控制效果, 并对系统不确定性和外界风扰动具有良好的鲁棒性.
英文摘要
      A new model-free adaptive robust control law based on data-driven methodology is proposed for the attitude control of a small-size unmanned helicopter. Different from most exiting model based control algorithms which required exact dynamic model knowledge of the helicopter, the proposed control law depends only on the input and output data of the helicopters.By using the data-driven methodology, the dependence of the control algorithm on the prior knowledge of the helicopter dynamics model is reduced and the influence of the system uncertainties are compensated. The controller designing depends only on the measured input and output data of the unmanned helicopter, and the sliding mode reaching law improves the robustness of the system. Finally, real-time experiments are performed on a helicopter attitude control testbed.The experiment results show that the control scheme proposed in this paper achieves good control performance with good robustness with respect to system uncertainties and external wind disturbances.