摘要
针对存在负载变化、建模误差和摩擦干扰的柔性关节空间机器人控制问题,提出了基于奇异摄动的神经网络自适应鲁棒控制方法。首先,通过拉格朗日方程和动量矩守恒定理建立柔性关节漂浮基空间机器人动力学模型;其次,通过奇异摄动理论将动力学模型近似分解表征为刚性的慢变子系统和柔性的快变子系统,针对于慢变子系统,设计基于神经网络补偿的自适应鲁棒控制器;针对于快变子系统,设计柔性补偿器和力矩微分反馈抑制器;最后,基于李雅普诺夫理论证明了控制系统的稳定性。仿真表明:所提出的控制策略是有效的,且在柔性补偿器失效的情况下,采用独立的神经网络自适应鲁棒控制器能够抑制弹性振动,并精确跟踪期望轨迹。
A neural network adaptive robust control method based on singular perturbation is proposed to solve the problem of flexible joint space robot control with load variation,modeling error,and friction disturbance. First,the Lagrange equation and the law of moment conservation are used to establish the dynamics model of free-floating space robot with flexible joints. Second,the singular perturbation theory is used to approximately decompose the dynamics model into a rigid slow subsystem and a flexible fast subsystem. An adaptive robust controller based on neural network compensation is designed for the slow subsystem,and a flexible compensator and a torque differential feedback suppressor are designed for the fast subsystem. Finally,the stability of the control system is proved based on the Lyapunov theory. The simulation results show that the proposed control strategy is effective,and the independent neural network adaptive robust controller can suppress the elastic vibration and track the desired trajectory accurately even when the flexible compensator fails.
作者
沈金淼
游张平
张文辉
叶晓平
周书华
单以才
SHEN Jinmiao;YOU Zhangping;ZHANG Wenhui;YE Xiaoping;ZHOU Shuhua;SHAN Yicai(School of Machinery and Automatic Control,Zhejiang Science and Technology University,Hangzhou 310000,Zhejiang,China;College of Electronic Engineering,Nanjing Xiaozhuang University,Nanjing 211171,Jiangsu,China;College of Engineering,Lishui University,Lishui 323000,Zhejiang,China;Key Laboratory of Digital Design and Intelligent Manufacturing for Creative Cultural Products of Zhejiang Province,Lishui 323000,Zhejiang,China;College of Automotive Engineering,Zhejiang Technical Institute of Economics,Hangzhou 310018,Zhejiang,China;Key Laboratory of Aerospace Metal Tube Forming Technology and Equipment of Zhejiang Province,Lishui 323000,Zhejiang,China)
出处
《上海航天（中英文）》
CSCD
2022年第6期29-36,50,共9页
Aerospace Shanghai（Chinese&English）
基金
国家自然科学基金(61772247)
浙江省自然科学基金(LZ21F020003,LY20E050002)
南京晓庄学院高层次项目(2020NXY14)。
关键词
空间机器人
负载变化
柔性关节
神经网络
振动抑制
自适应控制
space robot
load variation
flexible joint
neural network
vibration suppression
adaptive control
