Abstract Frequency Response Functions (FRFs) are essential in mechatronic systems and
its application ranges from system design and validation to controller design and …

Data informativity is a crucial property to ensure the consistency of the prediction error
estimate. This property has thus been extensively studied in the open-loop and in the closed …

Abstract In Prediction Error identification, to obtain a consistent estimate of the true system, it
is crucial that the input excitation yields informative data with respect to the chosen model …

We present a framework for the gradual improvement of model-based controllers. The total
time of the learning procedure is divided into a number of learning intervals. After a learning …

This paper considers a recently proposed framework for experiment design in system
identification for control. We study model based control design methods, such as Model …

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 work presents a novel methodology for Sub-Optimal Excitation Signal Generation and
Optimal Parameter Estimation of constrained nonlinear systems. It is proposed that the …

Optimal input design is an important step of the identification process in order to reduce the
model variance. In this work a D-optimal input design method for finite-impulse-response …

Prediction error identification requires that data be informative with respect to the chosen
model structure. Whereas sufficient conditions for informative experiments have been …

We present a closed form expression for the Fischer's information matrix associated with the
identification of Wiener models. In the derivation we assume that the input signal is …