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兵工学报 ›› 2019, Vol. 40 ›› Issue (4): 737-743.doi: 10.3969/j.issn.1000-1093.2019.04.008

• 论文 • 上一篇    下一篇

基于低频学习的电液位置伺服系统鲁棒自适应控制

刘雷, 姚建勇, 马大为, 王广文   

  1. (南京理工大学 机械工程学院, 江苏 南京 210094)
  • 收稿日期:2018-06-11 修回日期:2018-06-11 上线日期:2019-06-10
  • 作者简介:刘雷(1992—), 男, 硕士研究生。E-mail: llei@njust.edu.cn;
    姚建勇(1984—), 男, 教授, 博士生导师。E-mail: jerryyao.buaa@gmail.com;
    马大为(1953—), 男, 教授, 博士生导师。E-mail: ma-dawei@mail.njust;
    王广文(1989—), 男, 硕士研究生。 E-mail: 564256167@qq.com
  • 基金资助:
    国家自然科学基金项目(51675279)

Low-frequency Learning-based Robust Adaptive Control for Electro-hydraulic Position Servo System

LIU Lei, YAO Jianyong, MA Dawei, WANG Guangwen   

  1. (School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China)
  • Received:2018-06-11 Revised:2018-06-11 Online:2019-06-10

摘要: 电液位置伺服系统存在高频干扰和传感器测量噪声,导致传统自适应控制参数收敛性差、性能一致性低等问题。针对这些问题,提出一种基于低频学习的鲁棒控制策略。设计低通滤波器修正电液位置伺服系统的自适应参数,将修正前后出现的残差反馈到鲁棒自适应控制中构造新型控制律,滤除自适应律中存在的高频成分,从而有效地降低参数的波动程度,达到稳定收敛的目的。通过Lyapunov稳定性理论验证了闭环系统的全局稳定性。对比实验结果表明,所提方法能够有效解决电液位置伺服系统在高频干扰和传感器测量噪声作用下的参数稳定收敛问题,同时获得了系统动态误差的渐进稳定性,实验取得了预期效果。

关键词: 电液位置伺服系统, 低频学习, 鲁棒自适应控制, 稳定收敛

Abstract: A kind of low-frequency learning-based robust control strategy is proposed for electro-hydraulic position servo system, in which high-frequency interference and sensor measurement noise lead to the poor convergence and low consistency of traditional adaptive control. The adaptative parameter of electro-hydraulic servo system is modified by designing a low-pass filter, and a new control law, which can filter out the high-frequency components in the adaptive law, is constructed by the residuals before and after modification. As a result, the steady-state convergence is achieved while the high-frequency oscillation is alleviated. Lyapunov stability theory is utilized to verify the global stability of the closed-loop system. The comparative experimental results show that the proposed method can effectively solve the steady-state convergence of the parameter of electro-hydraulic position servo system under the action of high-frequency dynamics and sensor measurement noise, and retain the asymptotic stability of system dynamic error while achieving satisfactory tracking performance. Key

Key words: electro-hydraulicpositionservosystem, low-frequencylearning, robustadaptivecontrol, stableconvergence

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