Sliding Mode Force Control of an Electrohydraulic Servo System with RBF Neural Network Compensation

被引：4
|
作者：
Lu, Xinliang [1 ]
Du, Fengpo [2 ]
Jia, Qian [3 ]
Ren, Bin [1 ]
Wang, Xingsong [2 ]
机构：
[1] Shijiazhuang Tiedao Univ, Sch Mech Engn, Shijiazhuang 050043, Hebei, Peoples R China
[2] Southeast Univ, Sch Mech Engn, Nanjing 211189, Jiangsu, Peoples R China
[3] Nanjing Inst Technol, Ind Ctr, Nanjing 211167, Jiangsu, Peoples R China
来源：
MECHANIKA | 2019年 / 25卷 / 01期
关键词：
electrohydraulic; RBF; neural network; sliding mode; compensation control; trajectory tracking;
D O I：
10.5755/j01.mech.25.1.21279
中图分类号：
O3 [力学];
学科分类号：
08 ; 0801 ;
摘要：
In this paper, the dynamics of an electrohydraulic servo system is analyzed. It is difficult to achieve the precise force tracking control due to its high nonlinearities and parameter uncertainties For the accurate force tracking control, a sliding mode control algorithm with radial basis function (RBF) neural network compensation was proposed. The theory verifies that the algorithm is globally asymptotically stable. The experimental results show that the proposed algorithm is not only effective and better than the PID control in the force tracking control, but also robust to external uncertain disturbances.
引用
收藏
页码：32 / 37
页数：6
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