On applying interval fuzzy model to fault detection and isolation for nonlinear input-output systems with uncertain parameters

This paper presents an application of the interval fuzzy model (INFUMO) in fault detection and isolation for a class of processes with uncertain interval-type parameters. Confidence data bands for the process input-output pairs are approximated using a fuzzy model with interval parameters. The approximation, based on linear programming, employs l_infin-norm as the modelling error measure. Arbitrary sets of identification input signals can be used due to the application of low-pass filtering when obtaining the confidence bands. Using a combination of INFUMOs makes it possible to devise a fault-isolation scheme based on the given incidence matrix. Simulation results of a fault detection and isolation for a two-tank system are provided, which illustrate the relevance of the proposed FDI method