Fault diagnosis in robotic manipulators using artificial neural networks and fuzzy logic

Abstract

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.