This paper deals with the problem of fault diagnosis (FD) for a class of nonlinear systems. The scheme is based on a discrete-time diagnostic observer that computes a prediction of the system’s state. Compensation of the fault effect on the state prediction is achieved via an adaptive discrete-time approach, based on a parametric model of the faults. A stability proof is developed to prove the global exponential stability of the state estimates. A solution for fault isolation and identification is also proposed, based on a postfault analysis. The proposed FD approach is applied and experimentally tested on a conventional industrial robot manipulator.

Issue Section:
Research Papers
Keywords:
asymptotic stability, discrete time systems, fault diagnosis, nonlinear control systems, observers, fault diagnosis, nonlinear systems, adaptive estimation
Topics:
Discrete time systems, Errors, Fault diagnosis, Manipulators, Modeling, Stability, Nonlinear systems, Actuators, Dynamics (Mechanics)
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 by American Society of Mechanical Engineers
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