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This article deals with the fault detection and isolation problems for a class of uncertain discrete-time Takagi-Sugeno (T-S) fuzzy system based on the combination of the H-infinity observer and the zonotope method (ZM). For fault detection (FD) purpose, first, a Luenberger-like H-infinity observer, which is robust to disturbance in a sense of H-infinity performance index is designed under the assumption of the feasibility of an linear matrix inequality. Second, the ZM is applied to the H-infinity observer error dynamic system such that the interval state estimation can be calculated iteratively if the system suffers from neither actuator nor sensor faults. Third, a residual is constructed and its interval estimation is also given, and furthermore, based on the residual interval estimation, an FD scheme is developed. After this, we discuss the fault isolation issue in the similar way to alarm the appearance of the exact type fault: actuator or sensor fault. It is the ZM is applied onto the Luenberger-like observer, the fault detection and isolation performances are improved greatly. Finally, a numerical simulation example is given and some comparisons are also made to the existing results to verify the effectiveness and to show the advantages of proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a novel interval fault estimation approach by using zonotope technique for discrete-time linear parameter-varying systems in the presence of bounded parametric uncertainties, measured perturbation, and system disturbance. First, an augmented descriptor system is generated by using augmentation technique. Thus, the problem of interval fault estimation is transformed into the interval augmented state estimation. Then, an outer approximation of the new augmented state estimation domain is computed by using zonotope method. A zonotope should be consistent with the given outputs, perturbation, disturbance, and parametric uncertainties. Besides, it is minimized at each sampled time via an analytic formulation. Finally, a vehicle lateral dynamic nonlinear model is utilized to show the feasibility and effectiveness of the proposed zonotopic fault estimation technique. [ABSTRACT FROM AUTHOR]

This paper proposes a novel interval observer design method for discrete-time Takagi–Sugeno fuzzy systems with parametric uncertainty, disturbances, and measurement noise. We present a new structure of interval observer with more design parameters, which can be used to broaden the application scope of interval observer design. For improving the accuracy of interval estimation, an $L_{\infty }$ norm-based approach is used in the design of interval observer to attenuate the effect of the unknown disturbances, noise, and parametric uncertainty. Furthermore, the design conditions are formulated into a set of linear matrix inequalities, which can be efficiently solved. Numerical simulations are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]