The multimodel approach has become a major research topic during the last few decades
and unlike many other advanced techniques, it has also been successfully applied in …

This paper deals with a new fuzzy adapting rate for a neural emulator of nonlinear systems
with unknown dynamics. This method is based on an online intelligent adaptation by using a …

This paper concerns the design of robust sliding mode multiobserver for nonlinear systems.
A discrete uncoupled multimodel structure is retained for the modeling of nonlinear systems …

Purpose–The purpose of this paper is to present a new concept based on a neural network
validity approach in the area of multimodel for complex systems. Design/methodology …

This paper presents a method of diagnosis targeting the failure models used to represent the
different behaviour able to affect complex systems. This method, based on the multimodel …

The difficulty of observer design for a general class of nonlinear system and the reduction of
chattering phenomenon are still challenging tasks in the theory of sliding mode observers …

This paper describes an optimization technique of neural networks radial basis function
multi-model identification of nonlinear system. Indeed, this paper treats the multi-model …

This paper describes a multi-model identification of nonlinear system. Indeed, the multi-
model approach is based on neural networks, and is obtained by parametric identification …

La surveillance des systèmes industriels et/ou embarqués constitue une préoccupation
majeure en raison de l'accroissement de leur complexité et des exigences sur le respect des …

In order to improve the robustness of the discrete high gain observer with respect to noise
measurements and enhance the convergence dynamics, we propose, in this paper, a fuzzy …