This paper provides an overview of the recent developments in data-based techniques
focused on modern industrial applications. As one of the hottest research topics for …

It is well-documented how artificial intelligence can have (and already is having) a big
impact on chemical engineering. But classical machine learning approaches may be weak …

For the past decades, networked control systems (NCSs), as an interdisciplinary subject,
have been one of the main research highlights and many fruitful results from different …

This work aims at comparing several features of Principal Component Analysis (PCA) and
Partial Least Squares Regression (PLSR), as techniques typically utilized for modeling …

A data-driven predictive control methodology based on reduced Hankel matrix is proposed
in this paper. Undersome assumptions, the properties of a system can be simply and visually …

Given their increasing participation in fast-changing markets, the integration of scheduling
and control is an important consideration in chemical process operations. This generally …

Recently increasing amount of data centers (DCs) have been constructed for the
development of information and communications technology (ICT). Meanwhile, more energy …

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 …

In this paper, the design of the fractional-order predictive functional controller (α PFC) for the
linear fractional systems of arbitrary order has been presented. For this purpose, at first, the …

Nonlinearities, uncertainties and large time delay widely exist in the industrial processes,
which pose great difficulty to traditional proportional-integral-derivative (PID) control …