Diagnosis of uncertain fuzzy systems

In this work, the problem of diagnosis of uncertain nonlinear systems is tackled. The method is to use the interval analysis approach to estimate state vectors that are uncertain at the base. This approach assumes that uncertainty is random and with unknown probability distribution, except the upper and lower bounds of uncertainties are known. systems are designed by fuzzy models. An estimated interval of each model is calculated to deduce thereafter an estimate of the overall system. If the system is safe, the estimated measures, will be in the form of an interval includes the real outputs. Otherwise, it indicates a faulty functioning system.