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

fYear

2000

fDate

2000

Firstpage

297

Lastpage

302

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on

Conference_Location

Rio Patras

ISSN

2158-9860

Print_ISBN

0-7803-6491-0

Type

conf

DOI

10.1109/ISIC.2000.882940

Filename

882940