Rotation Angle Control Strategy for Telescopic Flexible Manipulator Based on a Combination of Fuzzy Adjustment and RBF Neural Network  

作　　者：Dongyang Shang Xiaopeng Li Meng Yin Fanjie Li Bangchun Wen 

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

出　　处：《Chinese Journal of Mechanical Engineering》2022年第4期203-226,共24页中国机械工程学报（英文版）

基　　金：Supported by National Natural Science Foundation of China(Grant No.51875092);National Key Research and Development Project of China(Grant No.2020YFB2007802);Natural Science Foundation of Ningxia Province(Grant No.2020AAC03279);Fundamental Research Funds for the Central Universities(Grant No.N2103025).

摘　　要：The length of fexible manipulators with a telescopic arm alters during movement.The dynamic parameters of telescopic fexible manipulators exhibit signifcant time-varying characteristics owing to variations in length.With an increase in the manipulators’length,the nonlinear terms caused by fexibility in the manipulators’dynamic equations cannot be ignored.The time-varying characteristics and nonlinear terms of telescopic fexible manipulators cause fuctuations in rotation angles,which afect the operation accuracy of end-efectors.In this study,a control strategy based on a combination of fuzzy adjustment and an RBF neural network is utilized to improve the control accuracy of fexible telescopic manipulators.First,the dynamic equation of the manipulators is established using the assumed mode method and Lagrange’s principle,and the infuence of nonlinear terms is analyzed.Subsequently,a combined control strategy is proposed to suppress the fuctuation of the rotation angle in telescopic fexible manipulators.The variation ranges of the feedforward PD controller parameters are determined by the pole placement strategy and length of the manipulators.Fuzzy rules are utilized to adjust the controller parameters in real-time.The RBF neural network is utilized to identify and compensate the uncertain part of the dynamic model of the fexible manipulators.The uncertain part comprises time-varying parameters and nonlinear terms.Finally,numerical simulations and prototype experiments prove the efectiveness of the combined control strategy.The results prove that the proposed control strategy has a smaller standard deviation of errors.Therefore,the combined control strategy is more suitable for telescopic fexible manipulators,which can efectively improve the control accuracy of rotation angles.

关 键 词：Flexible manipulator RBF neural network Fuzzy control Dynamic uncertainty 

分 类 号：TH113.2[机械工程—机械设计及理论]