As Industry 4.0 makes its course into the Chemical Processing Industry (CPI), new
challenges emerge that require an adaptation of the Process Analytics toolkit. In particular …

The aim of this book is to show that the nonparametric regression can be successfully
applied to system identification and how much can be achieved in this way. It gathers what …

This monograph systematically presents the existing identification methods of nonlinear
systems using the block-oriented approach It surveys various known approaches to the …

Modeling and identification of mechanical systems constitute an essential stage in practical
control design and applications. Controllers commanding systems that operate at varying …

This paper studies a method for the identification of Hammerstein models based on least
squares support vector machines (LS-SVMs). The technique allows for the determination of …

In 2006, Paul W. Holland retired from Educational Testing Service (ETS) after a career
spanning five decades. In 2008, ETS sponsored a conference, Looking Back, honoring …

Derived from the idea of stochastic approximation, recursive algorithms to identify a
Hammerstein system are presented. Two of them recover the characteristic of the nonlinear …

This brief deals with the recursive parameter identification of Hammerstein type nonlinear
dynamic systems with time-varying piecewise-linear characteristics. A special form of the …

The paper considers the problem of nonparametric estimation of nonlinear characteristic in
the FIR Wiener system. Methods proposed so far have suffered from the so-called 'curse of …

In the process industry, there exist many systems which can be approximated by a
Hammerstein model. Moreover, these systems are usually subjected to input magnitude …