Active fault diagnosis for hybrid systems based on sensitivity analysis and adaptive filter

Abstract

An active fault diagnostic (AFD) approach for diagnosis of actuator faults is proposed. The AFD approach excites the system by injecting a so-called excitation input. Here, the input is designed off-line based on sensitivity analysis such that the maximum sensitivity for each individual system parameter is obtained. Using maximum sensitivity, results in a better precision in the estimation of the corresponding parameter. The fault detection and isolation is done by comparing the nominal parameters with those estimated by an adaptive filter. Gaussian noise is used as the input disturbance as well as the measurement noise for simulation. The method is implemented and demonstrated on the large scale livestock hybrid ventilation model which was obtained during previous research.