This article studies the identification problem of the nonlinear sandwich systems. For the
sandwich system, because there are inner variables which cannot be measured in the …

Block-oriented nonlinear models are popular in nonlinear system identification because of
their advantages of being simple to understand and easy to use. Many different identification …

Abstract Using Artificial Neural Networks (ANN) for nonlinear system identification has
proven to be a promising approach, but despite of all recent research efforts, many practical …

Nonlinear state-space identification for dynamical systems is most often performed by
minimizing the simulation error to reduce the effect of model errors. This optimization …

This paper presents a record of the participation of the authors in a workshop on nonlinear
system identification held in 2016. It provides a summary of a keynote lecture by one of the …

This article introduces a network architecture, called dynoNet, utilizing linear dynamical
operators as elementary building blocks. Owing to the dynamical nature of these blocks …

In this paper, fractional Hammerstein system identification is considered, where the linear
block is of fractional order. The original discrete Hammerstein system is first converted to a …

The identification of black-box nonlinear statespace models requires a flexible
representation of the state and output equation. Artificial neural networks have proven to …

Block oriented models are recurrently employed to describe the dynamic characteristics of
nonlinear systems. This paper adopts an efficacious block-oriented model called cascaded …

The piecewise-linear characteristics often appear in the nonlinear systems that operate in
different ways in different input regions. This paper studies the identification issue of a class …