The identification of ARX models with constrained output variance in the presence of non-
Gaussian distribution of measurements is proposed in this paper. In the presence of non …

Optimal input design for system identification is an area of intensive modern research. This
paper considers the identification of output error (OE) model, for the case of constrained …

Refined instrumental variable methods have been broadly used for identification of
continuous-time systems in both open and closed-loop settings. However, the theoretical …

This paper deals with system identification and control of a nonlinear electromagnetic
actuator, which can be used in many practical applications: electromagnetic valve actuators …

Indirect methods for the identification of linear plant models on the basis of closed loop data
are based on the use of (reconstructed) input signals that are uncorrelated with the noise …

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 …

A key challenge in science and engineering is to provide a quantitative description of the
systems under investigation, leveraging the noisy data collected. Such a description may be …

This paper presents the identification process aimed at estimating the model parameters of a
COMAU Smart S2 industrial robot for controller design purposes. The principal challenges …

In data-driven controller re-tuning, when requirements exist for the closed-loop frequency
response, it is essential that the estimated closed-loop frequency response for a new …

In this paper, we study the problem of the model structure validation for closed-loop system
identification. Two probabilistic model uncertainties and optimum input filter are derived from …