Abstract Model-based control strategies are widely used for optimal operation of chemical
processes to respond to the increasing performance demands in the chemical industry. Yet …

Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has
become a promising system theoretical approach to handle the control of mildly nonlinear …

Acquire the tools for understanding new architectures and algorithms of dynamical recurrent
networks (DRNs) from this valuable field guide, which documents recent forays into artificial …

This paper considers black-and grey-box continuous-time transfer function estimation from
frequency response measurements. The first contribution is a bilinear mapping of the …

In recent years several new classes of matrices have been discovered and their structure
exploited to design fast and accurate algorithms. In this new reference work, Raf Vandebril …

A least-squares identification method is studied that estimates a finite number of expansion
coefficients in the series expansion of a transfer function, where the expansion is in terms of …

This book is concerned with applications of functional analysis and complex analysis to
problems of interpolation in spaces of analytic functions. The problems we look at are those …

In this paper, new noniterative algorithms for the identification of (multivariable) block-
oriented nonlinear models consisting of the interconnection of linear time invariant systems …

This paper introduces the reader to several recent developments in worst-case identification
motivated by various issues of modelling of systems from data for the purpose of robust …

Abstract Models of inverse systems are commonly encountered in control, eg, feedforward.
The aim of this paper is to address several aspects in identification of inverse models …