JOURNAL ARTICLE

Robust Neural Sliding Mode Control of Robot Manipulators

Nguyễn Trần HiệpPhạm Thượng CátLotfi BéjiSamir OtmaneAzgal Abichou

Year: 2009 Journal:   AIP conference proceedings Pages: 210-215   Publisher: American Institute of Physics

Abstract

This paper proposes a robust neural sliding mode control method for robot tracking problem to overcome the noises and large uncertainties in robot dynamics. The Lyapunov direct method has been used to prove the stability of the overall system. Simulation results are given to illustrate the applicability of the proposed method

Keywords:
Control theory (sociology) Sliding mode control Computer science Robot manipulator Robust control Lyapunov function Robot Control engineering Artificial neural network Stability (learning theory) Mode (computer interface) Lyapunov stability Tracking (education) Robustness (evolution) Robot control Artificial intelligence Control (management) Control system Mobile robot Nonlinear system Engineering Machine learning Physics

Metrics

1
Cited By
0.75
FWCI (Field Weighted Citation Impact)
0
Refs
0.76
Citation Normalized Percentile
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Citation History

Topics

Iterative Learning Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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