A fairly general class of nonlinear plants can be modeled as fuzzy systems, ie, as a time-
varying convex combination of “vertex” linear systems. As many linear LMI control results …

The wind power system is characterized by complex structures, numerous effect elements,
and complicated physical relationships, which bring great difficulties to establish the wind …

In this paper, a new method for nonlinear system identification via extreme learning machine
neural network based Hammerstein model (ELM-Hammerstein) is proposed. The ELM …

In this study, neuro‐fuzzy‐based identification procedure for Hammerstein model with
coloured noise is presented. Separable signal is used to realise the decoupling of the …

In this paper, a neuro-fuzzy based identification procedure for Hammerstein output error
model with colored noise is presented. Separable signal is used to realize the decoupling of …

In this paper, a novel algorithm is developed for identifying Hammerstein model. The static
nonlinear function is characterized by function link artificial neural network (FLANN) and the …

In this paper, an identification procedure of Hammerstein–Wiener nonlinear system with
process noise using special test signals is presented. Special test signals that contain …

In this paper, modeling and identification of nonlinear dynamic systems using neuro-
fractional Hammerstein model are considered. The proposed model consists of the neural …

In industrial process, some important variables such as quality index, efficiency index and
concentration of product components are difficult or even impossible to be measured directly …

This article introduces the multilinear model control approach to SISO Hammerstein-like
systems. An included angle dividing method is proposed to decompose the operating …