Volume 26 Issue 3 - Publication Date: 1 March 2007
Robust Fault Detection of a Robotic Manipulator
B. Halder and N. Sarkar Department of Mechanical Engineering Vanderbilt University, Nashville Tennessee, TN 37212, US
In this paper, a new robust fault detection technique for robotic manipulators is developed. The new approach, called robust nonlinear analytic redundancy (RNLAR) technique, detects both sensor and actuator faults in a robotic manipulator. The proposed RNLAR technique can compensate for the effects of model–plan -mismatch (MPM) and process disturbance. A nonlinear primary residual vectors (PRV) design method to detect faults is proposed where the PRVs are highly sensitive to faults and less sensitive to MPMand process disturbance. Experimental results on a PUMA 560 are presented to justify the effectiveness of the RNLAR scheme.
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