隧道掘进机清渣机械臂运动控制  

Motion Control of Muck Removal Manipulator of Tunnel Boring Machine

作　　者：张珈瑞 姜礼杰 贾连辉 龚国芳[1] 杨华勇[1] 韩冬[1] ZHANG Jiarui;JIANG Lijie;JIA Lianhui;GONG Guofang;YANG Huayong;HAN Dong(State Key Laboratory of Fluid Power Components and Mechatronic Systems,Zhejiang University,Hangzhou,Zhejiang 310027;China Railway Engineering Equipment Group Co.,Ltd.,Zhengzhou,Henan 450016)

机构地区：[1]浙江大学流体动力基础件与机电系统全国重点实验室,浙江杭州310027 [2]中铁工程装备集团有限公司,河南郑州450016

出　　处：《液压与气动》2024年第12期1-10,共10页Chinese Hydraulics & Pneumatics

基　　金：国家重点研发计划(2022YFC3802302);国家自然科学基金(52105072)。

摘　　要：清渣机械臂采用阀控液压缸系统,具有建模不确定性与强非线性特征。为提高清渣机械臂运动的准确性,提出一种轨迹追踪运动控制方法。基于清渣机械臂缩尺试验台模型,根据改进D-H法建立清渣机械臂运动学模型,基于拉格朗日法建立清渣机械臂非线性耦合动力学模型。针对动力学模型的建模不确定性,使用径向基函数神经网络逼近模型中的未知项,神经网络中的权值使用自适应方法进行在线调节。建立清渣机械臂仿真模型进行验证,结果表明,该方法可以确保清渣机械臂轨迹追踪过程具有较小的误差。The muck removal manipulator uses a valve-controller hydraulic cylinder system with modeling uncertainty and strong nonlinear characteristics.To improve the accuracy of the motion of the muck removal manipulator,this research proposes a trajectory tracking control method.Based on the scaled test bench model of muck removal manipulator,a kinematic model is established using the modified D-H method,a nonlinear coupled dynamics model of muck removal manipulator is established based on the Lagrangian.To address the modeling uncertainty of dynamic models,an radial basis function neural network is used to approximate the unknown terms in the model,and the weights in the neural network are adjusted online using adaptive methods.Finally,a simulation model based on the scale test bench data is used to validate the theory proposed.The results show that the method can ensure that the trajectory tracking process has small errors.

关 键 词：隧道掘进机 清渣机械臂 轨迹追踪 运动控制 阀控液压缸 

分 类 号：TH137[机械工程—机械制造及自动化]