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

被引：0
|
作者：
Liu L. [1 ]
Yao J. [1 ]
Ma D. [1 ]
Wang G. [1 ]
机构：
[1] School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu
来源：
Binggong Xuebao/Acta Armamentarii | 2019年 / 40卷 / 04期
关键词：
Electro-hydraulic position servo system; Low-frequency learning; Robust adaptive control; Stable convergence;
D O I：
10.3969/j.issn.1000-1093.2019.04.008
中图分类号：
学科分类号：
摘要：
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. © 2019, Editorial Board of Acta Armamentarii. All right reserved.
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页码：737 / 743
页数：6
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