Neural network-based adaptive funnel sliding mode control for servo mechanisms with friction compensation

被引：23

作者：

Wang, Shubo ^{[1
]}

Chen, Qiang ^{[2
]}

Ren, Xuemei ^{[3
]}

Yu, Haisheng ^{[1
]}

机构：

[1] Qingdao Univ, Sch Automat, Qingdao 266071, Shandong, Peoples R China

[2] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Zhejiang, Peoples R China

[3] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

来源：

NEUROCOMPUTING | 2020年 / 377卷

基金：

中国国家自然科学基金;

关键词：

Neural network (NN); Adaptive control; Funnel function; Servo mechanism; Sliding mode control (SMC); NONLINEAR-SYSTEMS; MOTION CONTROL; TRACKING CONTROL; FEEDBACK SYSTEMS; INPUT;

D O I：

10.1016/j.neucom.2019.10.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a novel adaptive funnel sliding mode control scheme is proposed for servo mechanisms with friction compensation. A continuously differentiable friction model is employed to capture the unknown friction dynamics. The friction nonlinearities and unknown dynamics are estimated by using neural network (NN). Moreover, a modified funnel variable, which relaxes limitation in original funnel control (e.g., systems with relative degree 1 or 2), is developed using the tracking error to replace the scaling factor, which is used to design the sliding mode surface. Then, a novel adaptive funnel sliding mode control scheme is proposed for servo mechanisms to improve the transient performance. The effectiveness of the developed control method is validated via experimental results. (C) 2019 Elsevier B.V. All rights reserved.

引用

页码：16 / 26

页数：11

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