The links between identification and control are examined. The main trends in this research
area are summarized, with particular focus on the design of low complexity controllers from a …

During the last two decades, considerable progress has been made in statistical time series
analysis. The aim of this book is to present a survey of one of the most active areas in this …

Estimation of a single-input single-output block-oriented model is studied. The model
consists of a linear block embedded between two static nonlinear gains. Hence, it is called N …

In this work we will introduce the asymptotic method (ASYM) of identification and provide two
case studies. The ASYM was developed for multivariable process identification for model …

Identification of distillation columns for model based control is studied using Wiener type
models. A recently developed parametric identification of Wiener model is extended and …

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX)
modeling which automatically seeks the best model order to represent investigated linear …

Abstract System identification deals with the problem of constructing models of systems from
observations of the inputs and outputs to the systems. In this thesis, a particular class of …

In this work, an identification based fault detection method is proposed. The idea is to
identify a dynamic process model from test data and to generate residuals using the …

In this paper, a model predictive control (MPC) case study is presented on the selective
catalytic reduction (SCR) in a coal-fired power plant. The MPC is used for optimizing the …

Identification of single-input single-output Hammerstein models is studied in this work. The
basic idea here is to extend the recently developed asymptotic method (ASYM) of linear …