Dynamic modeling and RBF neural network compensation control for space flexible manipulator with an underactuated hand  

作　　者：Dongyang SHANG Xiaopeng LI Meng YIN Fanjie LI 

机构地区：[1]School of Mechanical Engineering and Automation,Northeastern University,Shenyang 110819,China [2]Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,China

出　　处：《Chinese Journal of Aeronautics》2024年第3期417-439,共23页中国航空学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.52275090);the Fundamental Research Funds for the Central Universities(No.N2103025);the National Key Research and Development Program of China(No.2020YFB2007802);the Applied Basic Research Program of Liaoning Province(No.2023JH2/101300159)。

摘　　要：In space operation,flexible manipulators and gripper mechanisms have been widely used because of light weight and flexibility.However,the vibration caused by slender structures in manipulators and the parameter perturbation caused by the uncertainty derived from grasping mass variation cannot be ignored.The existence of vibration and parameter perturbation makes the rotation control of flexible manipulators difficult,which seriously affects the operation accuracy of manipulators.What’s more,the complex dynamic coupling brings great challenges to the dynamics modeling and vibration analysis.To solve this problem,this paper takes the space flexible manipulator with an underactuated hand(SFMUH)as the research object.The dynamics model considering flexibility,multiple nonlinear elements and disturbance torque is established by the assumed modal method(AMM)and Hamilton’s principle.A dynamic modeling simplification method is proposed by analyzing the nonlinear terms.What’s more,a sliding mode control(SMC)method combined with the radial basis function(RBF)neural network compensation is proposed.Besides,the control law is designed using a saturation function in the control method to weaken the chatter phenomenon.With the help of neural networks to identify the uncertainty composition in the SFMUH,the tracking accuracy is improved.The results of ground control experiments verify the advantages of the control method for vibration suppression of the SFMUH.

关 键 词：Space flexible manipulator RBF neural network Underactuated hand Dynamic models Model simplification 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP241[自动化与计算机技术—控制科学与工程] V44[航空宇航科学与技术—飞行器设计]