Robust Fault Detection using Set-based Approaches

This paper presents the performance of zonotopic fault detection (FD) for additive and multiplicative fault using direct test and inverse test. Zonotopic set-based approaches use the zonotope to describe the uncertain state, parameter and noise which are assumed unknown but bounded to reduce their influences on FD. These FD test methods aim at checking the consistency between the measured and estimated behaviour obtained from estimator in the parameter or output space. When an inconsistency is detected between these two, a fault can be indicated. At last, a motor model will be used to compare the performance of direct test and inverse test for additive and multiplicative faults.