摘要
针对折叠臂高空作业车的轨迹跟踪控制问题,提出了一种基于扩张状态观测器的神经网络滑模控制器。针对现实情况下臂杆柔性模态变量不可测以及外界扰动的问题,设计扩张状态观测器用于观测系统的模态变量,并将外界扰动作为系统状态变量进行观测。由于滑模控制器的高速切换控制会引起的高频振颤,因此设计了神经网络滑模控制器,使用神经网络的连续控制代替了不连续的切换控制。并采用李雅普诺夫定理证明了整个系统的稳定性。仿真实验结果表明,所设计的基于扩张状态观测器的神经网络滑模控制器在存在建模不确定性以及干扰的情况下能够实现折臂式高空作业车工作平台的轨迹跟踪控制,并且对高空作业车臂架系统存在的振动问题进行了有效抑制。
For the problem of the trajectory tracking control of the folding-boom aerial work platform,this paper proposes a neural network sliding mode controller based on the expanded state observer(ESO).For the problem that the flexible modal variables of the boom cannot be measured and the external disturbances in reality,an expanded state observer is designed to observe the modal variables of the system,which also observes the external disturbances as the system state variables.Because of the high-frequency vibration caused by the high-speed switching control of the sliding mode controller,a neural network sliding mode controller is designed,and the continuous control of the neural network is used instead of the discontinuous switching control.And the Lyapunov theorem is used to prove the stability of the entire system.The simulation experiment results show that the neural network sliding mode controller based on the expanded state observer designed in this paper can realize the trajectory tracking control of the folding-boom aerial work platform under the presence of modeling uncertainty and interference.Moreover,the controller is effective for the suppression of the vibration.
作者
胡海东
陈浩然
HU Hai-dong;CHEN Hao-ran(School of Information Engineering,Inner Mongolia University of Science and Technology,Inner Mongolia Baotou 014010,China)
出处
《机械设计与制造》
北大核心
2023年第11期188-193,共6页
Machinery Design & Manufacture
基金
内蒙古自然科学基金项目(2019LH06003)。
关键词
折叠臂
高空作业车
扩张状态观测器
神经网络
轨迹跟踪控制
振动抑制
Folding-Boom
Aerial Work Platform
Extended State Observer
Neural Network
Trajectory Tracking Control
Inhibit Vibration
