Fault diagnosis of the 3 tank system using fuzzy multiple inference modelling

This paper proposes a new approach for detecting and isolating faults in a non-linear dynamic process using the multiple model approach. The necessary conditions for the assignability of eigenvalues to a region in the s-plane and the necessary conditions to guarantee the stability of fuzzy models for Takagi-Sugeno (T-S) fuzzy observers are derived. The paper is structured in two stages. The first is to generate residual signals based on a comparison between the actual and estimated states and in the second stage the Takagi-Sugeno fuzzy observer is reconfigured to identify not only the faults but also the degree or severity of each fault. The techniques developed are demonstrated using a laboratory three tank system.