Fault detection for robot manipulators with parametric uncertainty: A prediction-error-based approach

In this paper, we introduce a new approach to fault detection for robot man ipulators. The technique, which is based on the isolation of fault signatur es via filtered torque prediction error estimates, does not require measure ments or estimates of manipulator acceleration as is the case with some pre viously suggested methods. The method is formally demonstrated to be robust under uncertainty in the robot parameters. Furthermore, an adaptive versio n of the algorithm is introduced, and shown to both improve coverage and si gnificantly reduce detection times. The effectiveness of the approach is de monstrated by experiments with a two-joint manipulator system.