Model-based fault detection of a nonlinear system using interval type-2 fuzzy systems with non-singleton type-2 fuzzification

Abstract

In this study interval type-2 fuzzy systems with non-singleton type-2 fuzzifire are used for identification and modeling nonlinear systems having noise with changing domain for fault detection purpose. The main idea in this fault detection method is to serve an upper bound and a lower bound as a confidence bound for system output that obtained from the interval type-2 fuzzy system. If we haven't precise information about mean and variance of noise, then non-singleton type-2 fuzzifire is usable. This fuzzifire improves performance of fault detection confidence bound. In the end of this paper a well-known benchmark two-tank system has been used for representing the advantages of proposed fault detection method.