<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Fault diagnosis in robotic manipulators using artificial neural networks and fuzzy logic</style></title><secondary-title><style face="normal" font="default" size="100%">2014 World Congress on Computer Applications and Information Systems (WCCAIS)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/6916571</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Hammamet, Tunisia.</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract></record></records></xml>