| 引用本文: | 韩晓薇,鲜斌,杨森.无人机吊挂空运系统的自适应控制设计[J].控制理论与应用,2020,37(5):999~1006.[点击复制] |
| HAN Xiao-wei,XIAN Bin,YANG Sen.Adaptive controller design for an unmanned quadrotor transportation system[J].Control Theory and Technology,2020,37(5):999~1006.[点击复制] |
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| 无人机吊挂空运系统的自适应控制设计 |
| Adaptive controller design for an unmanned quadrotor transportation system |
| 摘要点击 1672 全文点击 878 投稿时间：2019-03-25 修订日期：2019-07-22 |
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| DOI编号 10.7641/CTA.2019.90181 |
| 2020,37(5):999-1006 |
| 中文关键词 四旋翼无人机 运输系统 模型不确定性 神经网络 减摆控制 |
| 英文关键词 quadrotor unmanned aerial vehicle transportation system modeling uncertainties neural network antiswing control |
| 基金项目 国家自然科学基金项目(91748121, 90916004, 60804004)资助 |
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| 中文摘要 |
| 针对四旋翼无人机吊挂空运系统存在的模型不确定性及欠驱动性问题, 本文提出了一种基于能量耦合的
自适应控制设计. 首先, 基于能量整形控制方法构造了一种新型的能量存储函数以处理状态耦合. 然后利用神经网
络对系统未建模动态特性进行在线估计, 同时设计参数自适应律在线估计模型中的未知参数, 并采用基于符号函数
的鲁棒控制算法补偿神经网络的估计误差. 本文运用李雅普诺夫方法和拉塞尔不变性原理对闭环系统的稳定性进
行了证明, 并且证明了负载摆动和无人机位置误差的渐近收敛性. 最后, 在室内实验平台上进行了飞行实验. 实验
结果表明, 本文提出的非线性控制方法能够在有效抑制吊挂负载摆动的同时, 实现无人机位置的精确控制. |
| 英文摘要 |
| This paper presents an energy coupling-based adaptive control scheme for an unmanned quadrotor transportation
system which is subjected to modeling uncertainties and underactuated properties. A new storage function is
constructed based on energy shaping methodology to deal with dynamic states coupling of the unmanned quadrotor transportation
system. A neural network (NN) is used to estimate the time-varying modeling uncertainties with on-line weight
tunning. And an adaptive nonlinear control law is developed to compensate for unknown parameters in the dynamics model,
while the NN approximation errors are compensated by using the signum function. Lyapunov-based stability analysis and
the LaSalle invariance theorem are employed to the stability of the closed-loop system, and the asymptotic convergence
of the payload’s swing motion and the quadrotor’s position errors. Finally, real-time flight experiments are performed
on a self-build indoor unmanned aerial vehicle (UAV) testbed. The experimental results are included to demonstrate the
effectiveness of the proposed control law. |
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