Adaptive sliding mode control based on friction compensation for opto-electronic tracking system using neural network approximations

被引：28
作者：
Yue, Fengfa [1 ]
Li, Xingfei [1 ]
机构：
[1] Tianjin Univ, State Key Lab Precis Measuring Technol & Instrume, Tianjin 300072, Peoples R China
来源：
NONLINEAR DYNAMICS | 2019年 / 96卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Sliding mode control; Neural network control; LuGre model; Nonlinear control; Opto-electronic tracking; PRECISION MOTION CONTROL; NONLINEAR-SYSTEMS; DEAD-ZONES;
D O I：
10.1007/s11071-019-04945-3
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In this paper, an adaptive sliding mode control algorithm based on friction compensation utilizing neural network (NN) is designed for an opto-electronic tracking system under the circumstance of friction and external disturbance. Since neural networks can approximate any nonlinear function, the developed NN controller can approximate the nonlinear friction which is integrated into the adaptive sliding mode control system in the Lyapunov framework. The adaptive sliding mode controller with friction compensation can effectively reduce the effects of nonlinear friction and external disturbance of the opto-electronic tracking system utilizing neural network approximations. The stability of the proposed method is guaranteed according to Lyapunov criterion. Simulation and experimental validation results for a nonlinear LuGre dynamic model of the opto-electronic tracking system are provided to validate the effectiveness of the proposed control method.
引用
收藏
页码：2601 / 2612
页数：12
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