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Fault detection and identification for robot manipulators

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4 Author(s)
McIntyre, M.L. ; Dept. of Electr. & Comput. Eng., Clemson Univ., SC, USA ; Dixon, W.E. ; Dawson, D.M. ; Walker, I.D.

Several factors must be considered for robotic task execution in the presence of a fault, including: detection, identification, and accommodation for the fault. In this paper, a prediction error based dead-zone residual function and nonlinear observers are used to detect and identify a class of actuator faults. Advantages of the proposed fault detection and identification methods are that they are based on the nonlinear dynamic model of a robot manipulator (and hence, can be extended to a number of general Euler Lagrange systems), they do not require acceleration measurements, and they are independent from the controller. A Lyapunov-based analysis is provided to prove that the developed fault observer converges to the actual fault.

Published in:

Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on  (Volume:5 )

Date of Conference:

26 April-1 May 2004

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