Industrial data sets are often contaminated with outliers due to sensor malfunctions, signal
interference, and other disturbances as well as interplay of various other factors. The effect …

This book presents an overview of the different errors-in-variables (EIV) methods that can be
used for system identification. Readers will explore the properties of an EIV problem. Such …

System Identification (SI) is a discipline in control engineering concerned with inferring
mathematical models from dynamic systems based on its input/output observations. Rich …

Finite-sample system identification (FSID) methods provide guaranteed confidence regions
for the unknown model parameter of dynamical systems under mild statistical assumptions …

Errors-in-variables (EIV) systems are known to be identifiable not generally, but under some
specific conditions. These conditions are normally formulated for open-loop systems. This …

The paper gives a survey of errors-in-variables methods in system identification.
Background and motivation are given, and examples illustrate why the identification problem …

Identification of the EIV system has attracted much interest due to the potential usage of the
EIV system in the engineering sciences and elsewhere. It is a more difficult problem in …

A robust control oriented identification approach is proposed to deal with the identification of
errors-in-variables models (EIVMs), which are corrupted with input and output noises. Based …

This paper proposes a convex optimization algorithm to minimize the v‐gap metric for
parameter estimation of a SISO system using frequency‐domain measurements. According …

This paper proposes a shaping weighting function (SWF) design method for the H∞ loop-
shaping design procedure of McFarlane and Glover. In the original H∞ loop-shaping design …