IJCAS

This paper presents an Unknown Input robust Observer (UIO) capable of simultaneously estimate both sensor fault and system states. The system is assumed to be discrete-time Takagi-Sugeno (T-S) Fuzzy with uncertainties. An augmented system is obtained from the dynamic fault model and original system. Afterward, a UIO is designed for the augmented system aiming at decoupling process disturbances. Its design is obtained by using an H∞ optimization technique and developed to maintain the observer stable, reducing the non-decoupled process disturbances effect. The proposed method is validated by two numerical examples as it is compared to a regular UIO technique and the extended Kalman filter. Results show the proposed technique presents better performance when the dynamic system is not purely nonlinear even if the same tuning parameters are chosen. Although other techniques are not able to ensure the error limitation, the proposed one is capable of it even in nonlinear systems.

Keywords: Discrete time Takagi Sugeno fuzzy system, fault estimation, H&infin, optimization technique, unknown input robust observer