Robust Fault Detection of a Robotic Manipulator

Authors:
Bibhrajit Halder;Nilanjan Sarkar
Affiliations:
Department of Mechanical Engineering Vanderbilt University, Nashville Tennessee, TN 37212, US;Department of Mechanical Engineering Vanderbilt University, Nashville Tennessee, TN 37212, US/
Venue:
International Journal of Robotics Research
Year:
2007

Citing 4
Cited 1

Optimally robust redundancy relations for failure detection in uncertain systems

Automatica (Journal of IFAC)
Derivation and application of nonlinear analytical redundancy techniques with applications to robotics

Derivation and application of nonlinear analytical redundancy techniques with applications to robotics
Fault identification for robot manipulators

IEEE Transactions on Robotics
Brief Robust fault detection in uncertain dynamic systems

Automatica (Journal of IFAC)

A hierarchical multiple-model approach for detection and isolation of robotic actuator faults

Robotics and Autonomous Systems

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Abstract

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 MPM and process disturbance. Experimental results on a PUMA 560 are presented to justify the effectiveness of the RNLAR scheme.