Title :
A neural network based actuator fault detection and diagnostic scheme for a SCARA manipulator
Author :
Jain, Anshul A. ; Demetriou, Michael A.
Author_Institution :
Dept. of Mech. Eng., Worcester Polytech. Inst., MA, USA
Abstract :
One of the most critical components of a robotic system is the actuator, which undergoes a lot of wear and tear and may lead to its failure. In order to monitor such a system, we propose a neural network-based fault detection and diagnosis scheme for actuator failures in robotic manipulators. A single detection and diagnostic observer is utilized for online failure assessment and the weights of the failure online approximators are adaptively updated using Lyapunov re-design methods. The fault detection scheme is implemented for a SCARA manipulator and simulation results are presented
Keywords :
Lyapunov methods; actuators; adaptive systems; fault diagnosis; manipulator dynamics; manipulator kinematics; observers; radial basis function networks; Lyapunov redesign method; SCARA manipulator; actuator failure; dynamics; fault detection; fault diagnosis; kinematics; observer; radial basis function neural network; Actuators; Computer networks; Condition monitoring; Control systems; Fault detection; Fault diagnosis; Manipulators; Neural networks; Orbital robotics; Robots;
Conference_Titel :
Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on
Conference_Location :
Rio Patras
Print_ISBN :
0-7803-6491-0
DOI :
10.1109/ISIC.2000.882940
