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

Authors
  • Yue, Fengfa
  • Li, Xingfei
Type
Published Article
Journal
Nonlinear Dynamics
Publisher
Springer-Verlag
Publication Date
Apr 26, 2019
Volume
96
Issue
4
Pages
2601–2612
Identifiers
DOI: 10.1007/s11071-019-04945-3
Source
Springer Nature
Keywords
License
Yellow

Abstract

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.

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