This paper presents the application of an Adaptive Robust Observer (ARO) to the detection of some common faults that occur in hydraulic cylinder drive units such as the lack of sufficient supply pressure, reduced hydraulic compliance and excessive leakage of the hydraulic fluid. All of these faults could contribute to the reduced performance of the system and eventual complete failure. The inherent nonlinear system dynamics, severe parametric uncertainties and model uncertainties make fault detection in hydraulic systems difficult to implement in practice. To tackle these problems, the Adaptive Robust Observer presented in this paper is designed using the nonlinear system dynamics and robust filter structures which attenuate the effect of model uncertainties to give robust estimates of the states. By using on-line parameter adaptation the accuracy of the state-estimate is improved. Also, by estimating the parameters only when certain persistence of excitation conditions are satisfied, bounds on parameter estimation errors can be computed which would help in setting better threshold limits on the residual signals which improves the robustness of the fault detection scheme. Simulation and experimental results on the swing-arm of a three-degree of freedom hydraulic robot arm are presented to demonstrate the effectiveness of the proposed fault detection scheme.

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