A Robust Fault Detection Method using a Zonotopic Kaucher Set-membership Approach

This paper presents a robust fault detection method using a zonotopic Kaucher set-membership method. The fault detection approach is based on checking the consistency between the model and the data. Consistency is given if there is an intersection between the feasible parameter set and the nominal parameter set. To allow efficient computation the feasible set is approximated by a zonotope. Due to the usage of Kaucher interval arithmetic the results are mathematically guaranteed. The proposed approach is assessed using an illustrative application based on a well-known four-tank case study. The study shows that it is possible to detect even small errors in a noisy setting. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.