This article reviews the development of experiment design in the field of identification of
dynamical systems, from the early work of the seventies on input design for open loop …

The purpose of this volume is to provide a brief review of the previous work on model
reduction and identifi cation of distributed parameter systems (DPS), and develop new …

Model-based engineering becomes more and more important in industrial practice. System
identification is a vital technology for producing the necessary models, and has been an …

This paper focuses on the problem of robust experiment design, ie, how to design an input
signal which gives relatively good estimation performance over a large number of systems …

This paper discusses the application of the virtual reference tuning (VRT) techniques to tune
neural controllers from batch input–output data, by particularising nonlinear VRT and …

It is well known that robust optimal experiment design is an extremely computationally
expensive problem. The design is generally solved by discretisation of the design space …

In this paper the following problem is studied: design an input signal with the property that
the estimated model based on this signal satisfies a given performance level with a …

In this paper, sufficient conditions for robust output feedback controller design for systems
with ellipsoidal parametric uncertainty are given in terms of solutions to a set of linear matrix …

We consider the problem of minimum-variance excitation design for frequency response
estimation based on finite impulse response (FIR) and output error (OE) models. The …

In this paper we investigate the cost of complexity, which is defined as the minimum amount
of input power required to estimate the frequency response of a given linear time invariant …