摘要
为提高数控机床伺服系统的控制精度,对X-Y数控工作台高精度控制中的摩擦补偿和外部扰动的补偿进行了研究。建立了基于动态Lu Gre摩擦的伺服系统模型,提出了设计一个非线性双观测器来估计Lu Gre模型内部的不可测的状态,并通过自适应鲁棒控制器来实现未知的摩擦和负载转矩的补偿,同时设计神经网络观测器补偿外部扰动;利用Lyapunov稳定性理论证明了闭环系统的稳定性。仿真结果表明,有效地解决非线性摩擦和扰动的影响,提高系统的跟踪精度和鲁棒性。
In this paper,a high precision control of CNC with friction and disturbance compensation was proposed. Based on X-Y table,the servo system model based on dynamic Lu Gre friction model was established. Firstly,a nonlinear dual observer was designed to estimate the non-measurable state of the Lu Gre model. Then,the adaptive robust controller was designed to handle the unknown friction and load torque,and the neural network observer was used to compensate the external disturbances. The Lyapunov function was used to prove the stability of the closed-loop system. The simulation results showthat the proposed algorithm can effectively solve the effects of nonlinear friction and disturbance,and improve the tracking accuracy and robustness of the system.
作者
王元生
杨书根
WANG Yuan-sheng;YANG Shu-gen(Department of Automotive Engineering,Yancheng Institute of Industry Technology,Yancheng Jiangsu 224005,China;School of Mechanical Engineering,Jiangsu University,Zhenjiang Jiangsu 212013,China)
出处
《组合机床与自动化加工技术》
北大核心
2018年第8期38-41,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
江苏省高等职业院校国内高级访问学者计划资助项目(2014FX084)
江苏省重点研发计划--产业前瞻与共性关键技术竞争项目(BE2015107)
盐城工业职业技术学院科研课题(YGYY1701)
关键词
摩擦补偿
外部扰动
神经网络
自适应鲁棒控制
friction compensation
external disturbance
neural network
adaptive robust controller
