In this paper we propose a novel data-based predictive control scheme in which the
prediction model is obtained from a linear combination of past system trajectories. The …

Stock price forecasting is a relevant and challenging problem that has attracted a lot of
interest from engineers and scientists. In this paper we apply two techniques for stock price …

This work presents a data driven control strategy able to track a set point without steady‐
state error. The control sequence is computed as an affine combination of past control …

Here the problem of designing two degrees of freedom controllers for an unknown plant
based on input–output measurements is discussed. Virtual reference feedback tuning aims …

This letter presents a new method for modeling dynamical systems. The method uses
historical data of the outputs to predict the evolution of the system. The proposed method is …

In this paper, a heuristic historian data‐based predictive control strategy is presented and
used to control a water distribution system simulated using the EPANET software, in …

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 …

The problem of designing two feedback controllers for an unknown plant based on input–
output measurements is discussed within a linear setting. Virtual reference feedback tuning …

This work presents a new methodology to obtain probabilistic interval predictions of a
dynamical system. The proposed strategy uses stored past system measurements to …

Purpose The purpose of this paper is to deal with the anomaly detection problem in multi-
unmanned aerial vehicles (UAVs) formation that can be transformed to identify some …