Fault Diagnosis in robotic manipulators using Artificial Neural Networks and Fuzzy logic

被引：0

作者：

Khireddine, Mohamed Salah ^{[1
]}

Chafaa, Kheireddine ^{[1
]}

Slimane, Noureddine ^{[1
]}

Boutarfa, Abdelhalim ^{[1
]}

机构：

[1] Batna Univ, Dept Elect, LRP & LEA Labs, Batna, Algeria

来源：

2014 WORLD CONGRESS ON COMPUTER APPLICATIONS AND INFORMATION SYSTEMS (WCCAIS) | 2014年

关键词：

Artificial Neural network; Fault Diagnosis; Fuzzy logic; robotic manipulator; NONLINEAR-SYSTEMS; PARITY RELATIONS; TOLERANCE;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Computational intelligence techniques are being investigated as extension of the traditional fault diagnosis methods. This paper presents a scheme for fault detection and isolation (FDI) via artificial neural networks and fuzzy logic. It deals with sensors and actuator fault of a three links scara robot. The proposed FDI approach is implemented on Matlab/Simulink software and tested under several types of faults. The obtained results improving the importance of this method. Then, the actuator and sensor fault are detected and isolated successfully.

引用

页数：6

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