针对Stewart平台的六自由度(six degrees of freedom,6-DOF)轨迹跟踪问题,提出一种基于神经网络的非奇异终端滑模控制方法并应用于Stewart平台的位置姿态控制中。通过分析Stewart平台的位置反解和速度反解,建立运动学方程,利用牛顿-欧...针对Stewart平台的六自由度(six degrees of freedom,6-DOF)轨迹跟踪问题,提出一种基于神经网络的非奇异终端滑模控制方法并应用于Stewart平台的位置姿态控制中。通过分析Stewart平台的位置反解和速度反解,建立运动学方程,利用牛顿-欧拉方程建立动力学方程,并结合加速度反解得到了平台的状态空间表达式;基于非奇异滑模面函数,设计非奇异终端滑模控制律。考虑到径向基函数(radial Basis function,RBF)神经网络的逼近特性,采用RBF神经网络对模型未知部分进行自适应逼近,并利用Lyapunov第二法设计了自适应律;通过仿真证明控制器设计的有效性。仿真结果表明,相比于比例积分微分(proportional integral derivative,PID)控制器,提出的RBF神经网络非奇异终端滑模控制器具有更好的轨迹跟踪精度和动态特性。展开更多
The windy environment is the main cause affecting the efficiency of offshore wind turbine installation.In order to improve the stability and efficiency of single-blade installation of offshore wind turbines under high...The windy environment is the main cause affecting the efficiency of offshore wind turbine installation.In order to improve the stability and efficiency of single-blade installation of offshore wind turbines under high wind speed conditions,the Stewart platform is used as an auxiliary tool to help dock the wind turbine blade in this paper.In order to verify the effectiveness of the Stewart platform for blade docking,a blade docking simulation system consisting of the Stewart platform,wind turbine blade,and wind load calculation module was built based on Simulink/SimscapeMultibody.At the same time,the PID algorithm is used to control the Stewart platform so that the blade can effectively track the desired trajectory during the docking process to ensure the successful docking of the blade.Through the simulation of the docking process for blades with a length of 61.5 meters,this paper successfully demonstrates a docking system that might facilitate future docking processes.It also shows that the Stewart platform can effectively reduce the vibration and the movement range of the blade root and improve the stability and efficiency of blade docking.展开更多
文摘针对Stewart平台的六自由度(six degrees of freedom,6-DOF)轨迹跟踪问题,提出一种基于神经网络的非奇异终端滑模控制方法并应用于Stewart平台的位置姿态控制中。通过分析Stewart平台的位置反解和速度反解,建立运动学方程,利用牛顿-欧拉方程建立动力学方程,并结合加速度反解得到了平台的状态空间表达式;基于非奇异滑模面函数,设计非奇异终端滑模控制律。考虑到径向基函数(radial Basis function,RBF)神经网络的逼近特性,采用RBF神经网络对模型未知部分进行自适应逼近,并利用Lyapunov第二法设计了自适应律;通过仿真证明控制器设计的有效性。仿真结果表明,相比于比例积分微分(proportional integral derivative,PID)控制器,提出的RBF神经网络非奇异终端滑模控制器具有更好的轨迹跟踪精度和动态特性。
文摘The windy environment is the main cause affecting the efficiency of offshore wind turbine installation.In order to improve the stability and efficiency of single-blade installation of offshore wind turbines under high wind speed conditions,the Stewart platform is used as an auxiliary tool to help dock the wind turbine blade in this paper.In order to verify the effectiveness of the Stewart platform for blade docking,a blade docking simulation system consisting of the Stewart platform,wind turbine blade,and wind load calculation module was built based on Simulink/SimscapeMultibody.At the same time,the PID algorithm is used to control the Stewart platform so that the blade can effectively track the desired trajectory during the docking process to ensure the successful docking of the blade.Through the simulation of the docking process for blades with a length of 61.5 meters,this paper successfully demonstrates a docking system that might facilitate future docking processes.It also shows that the Stewart platform can effectively reduce the vibration and the movement range of the blade root and improve the stability and efficiency of blade docking.
