空间机械臂基于速度观测器的神经网络控制  

Neural Network Control of Space Manipulator Based on Velocity Observer

作　　者：张文辉 沈金淼 游张平[3,5,7] 叶晓平 周书华[4] ZHANG Wenhui;SHEN Jinmiao;YOU Zhangping;YE Xiaoping;ZHOU Shuhua(School of Electronic Engineering,Nanjing Xiaozhuang University,Nanjing 211167,China;School of Machinery and Automatic Control,Zhejiang Sci-Tech University,Hangzhou 310000,China;College of Engineering,LishuiUniversity,Lishui 323000,China;School of Automotive Engineering,Zhejiang Technical Institute of Economics,Hangzhou 323000,China;Key Laboratory of Digital Design and Intelligent Manufacturing for Creative Cultural Products of Zhejiang Province,Lishui 323000,China;State Key Laboratory for Novel Software Technology(Nanjing University),Nanjing 210093,China;Zhejiang Province Key Laboratory of Aerospace Metal Tube Forming Technology and Equipment,Lishui 323000,China)

机构地区：[1]南京晓庄学院电子工程学院,南京211167 [2]浙江理工大学机械与自动控制学院,杭州310000 [3]丽水学院工学院,丽水323000 [4]浙江经济职业技术学院汽车工程学院,杭州323000 [5]浙江省文创产品数字化设计与智能制造重点实验室,丽水323000 [6]计算机软件新技术国家重点实验室(南京大学),南京210093 [7]浙江省航空航天金属导管塑性成形技术与装备重点实验室,丽水323000

出　　处：《空间控制技术与应用》2022年第6期12-21,共10页Aerospace Control and Application

基　　金：国家自然科学基金资助项目(61772247);浙江省自然科学基金重点项目(LZ21F020003);浙江省自然科学基金资助项目(LY20E050002,LY18F030001);南京晓庄学院高层次培育项目(2020NXY14)。

摘　　要：针对无速度反馈的柔性关节空间机器人控制问题,提出了一种基于速度观测器的自适应神经网络的控制方法.基于奇异摄动理论将柔性关节空间机械臂动力学模型分解为快慢变2个子系统;利用神经网络逼近控制器和观测器中的未知非线性,设计基于自适应神经网络的速度观测器和控制器,动态抵消模型不确定性对系统的影响;利用泰勒线性化方法,设计了权值、基函数中心和宽度参数在内的自适应学习律,提高了控制精度,且不需要离线学习;设计了基于速度差值的控制器来抑制快变子系统模型中的弹性振动;基于Lyapunov稳定性理论证明了闭环系统的一致最终有界.仿真实验证明了所提控制策略的有效性.An adaptive neural network control method based on speed observer is proposed for the control of flexible joint space robot without speed feedback.Based on singular perturbation theory,the dynamic model of space manipulator with flexible joints is decomposed into two subsystems,fast and slow subsystems;Using neural network to approximate the unknown nonlinearity in the controller and observer,a speed observer and a controller based on adaptive neural network are designed to dynamically counteract the influence of model uncertainty on the system.Using Taylor linearization method,an on line adaptive learning law of weight,basis function center and width is designed,which improves the control accuracy and does not need the off line learning stage.A controller based on velocity difference is designed to suppress the elastic vibration in the model of the rapidly varying subsystem.Based on Lyapunov stability theory,the uniform ultimate boundedness of the closed loop system is proved.Simulation results show the effectiveness of the proposed control strategy.

关 键 词：空间机械臂 柔性关节 速度观测器 神经网络 振动抑制 

分 类 号：TP241[自动化与计算机技术—检测技术与自动化装置]