Abstract
This paper studies a model-based fault detection and isolation (FDI) scheme for robot manipulators with actuator and sensor faults. Without adding redundant joint sensor measurements, the multiple faults simultaneously occurring in the actuators and sensors of the manipulator are detected, estimated and isolated. Considering Lipschitz-like nonlinearities and modeling uncertainties, a nonlinear adaptive observer is presented to estimate the faulty parameters with a pre-specified estimation error bound. The performances of the proposed FD scheme, including the robustness of observers to the uncertainties, the accuracy of fault estimation and the rapidity of fault diagnosis, are rigorously analyzed. The proposed approach is verified by a simulation of Integrated Motion Inc. (IMI) two-link, revolute, direct-drive robot manipulator.
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