This paper is devoted to the data-driven fault detection of nonlinear systems. For our
purpose, the definition of Takagi-Sugeno fuzzy data-driven forms of kernel representations …

The paper tackles the problem of robust fault detection using Takagi–Sugeno neuro-fuzzy
(NF) models. A model-based strategy is employed to generate residuals in order to make a …

The main focus of this paper is on the analysis and integrated design of L_2 observer-based
fault detection (FD) systems for discrete-time nonlinear industrial processes. To gain a …

The paper tackles the problem of robust fault detection using Takagi-Sugeno fuzzy models.
A model-based strategy is employed to generate residuals in order to make a decision about …

In this article, optimal observer-based fault detection (FD) and estimation schemes for
Takagi–Sugeno fuzzy systems with process faults are investigated. In particular, an optimal …

In this paper, a neuro‐fuzzy and de‐coupling fault diagnosis scheme (NFDFDS) is proposed
for fault detection and isolation (FDI) of nonlinear dynamic systems. In this approach …

This paper deals with the data-driven design of observer-based fault detection and control
systems. We first introduce the definitions of the data-driven forms of kernel and image …

In this paper we propose a solution to the model-based fault diagnosis problem for the class
of non-linear dynamic systems subjected to be described by a Takagi-Sugeno fuzzy model …

A new fault detection scheme for continuous-time nonlinear dynamic system is studied. The
nonlinear system is modelled by Takagi-Sugeno fuzzy model. A fuzzy observer-based …

A fault detection approach is presented for Lipschitz non-linear dynamic systems with
bounded measurement noises. This approach does not require any nominal models of …