航空学报 > 2014, Vol. 35 Issue (2): 555-566   doi: 10.7527/S1000-6893.2013.0293

高效强力复合铣A轴的动力学建模与自适应滑模控制

赵鹏兵, 史耀耀   

  1. 西北工业大学 现代设计与集成制造技术教育部重点实验室, 陕西 西安 710072
  • 收稿日期:2013-04-28 修回日期:2013-05-29 出版日期:2014-02-25 发布日期:2013-06-09
  • 通讯作者: 史耀耀,Tel.:029-88492851. E-mail:shiyy@nwpu.edu.cn E-mail:shiyy@nwpu.edu.cn
  • 作者简介:赵鹏兵 男,博士研究生。主要研究方向:智能制造装备与现代数控系统。E-mail:zhpb83@163.com;史耀耀 男,博士,教授,博士生导师。主要研究方向:机电控制自动化,加工表面光整技术。Tel:029-88492851 E-mail:shiyy@nwpu.edu.cn
  • 基金资助:

    国家科技重大专项(2013ZX04001081)

Dynamic Modeling and Adaptive Sliding Mode Control of A-axis for Efficient and Powerful Milling

ZHAO Pengbing, SHI Yaoyao   

  1. The MOE (Ministry of Education) Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2013-04-28 Revised:2013-05-29 Online:2014-02-25 Published:2013-06-09
  • Supported by:

    National Science and Technology Major Project (2013ZX04001081)

摘要:

A轴单元作为五轴数控机床的关键功能部件,其控制精度直接影响工件的加工精度和表面质量。针对系统参数摄动和不确定性切削负载对A轴伺服系统控制精度的影响,分析了A轴驱动系统的动静态性能,讨论了驱动扭矩、负载扭矩、运动方向和系统参数之间的相互关系,并建立了系统的非线性动力学模型。基于该动力学模型,设计了自适应模糊滑模控制器(AFSMC),采用模糊系统对滑模控制律中的非线性函数项进行自适应逼近,并基于Lyapunov理论设计了模糊系统中可调参数的自适应律,同时,在滑模控制(SMC)的切换控制部分采用了指数趋近律。实验结果表明,所设计的AFSMC对不确定性负载扭矩和系统参数摄动具有较强的鲁棒性。与传统滑模控制(TSMC)相比,其在有效减小控制输入抖振的同时,使得跟踪控制精度提高了14.54%。

关键词: A轴, 非线性动力学, 定位控制, 模糊逼近, 滑模控制

Abstract:

Positioning precision of the A-axis as an essential assembly in a 5-axis CNC machine tool directly affects the machining accuracy and surface quality of the machined parts. Considering the influence of parameter perturbation and uncertain cutting force on the control precision of the A-axis, this paper analyzes the static and dynamic performance of the A-axis, discusses the relationships among the drive torque, load torque, motion direction and system parameters, and finally establishes a nonlinear dynamic model of the system. On the basis of this model, an adaptive fuzzy sliding mode control (AFSMC) is proposed. The fuzzy system is used to approximate the nonlinear functions in the sliding mode control law, and adaptive laws of the tunable parameters are designed based on Lyapunov theory. Meanwhile, the exponential reaching law is utilized in switching mode control (SMC). Experimental results show that the proposed AFSMC is robust to parameter perturbation and uncertain load torque. Compared with the traditional sliding mode control (TSMC), the proposed method can effectively reduce control input chattering and improve the tracking precision by 14.54%.

Key words: A-axis, nonlinear dynamics, positioning control, fuzzy approximation, sliding mode control

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