As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …

In this review paper, the integration of Machine Learning (ML) and Model Predictive Control
(MPC) in Automotive Control System (ACS) applications are discussed. ACS can be divided …

From an engineering point of view, non‐linear systems are essential to the operation of
control systems, because all systems actually have a non‐linear state in nature. In reality …

Deep learning is a topic of considerable current interest. The availability of massive data
collections and powerful software resources has led to an impressive amount of results in …

Abstract Using Artificial Neural Networks (ANN) for nonlinear system identification has
proven to be a promising approach, but despite of all recent research efforts, many practical …

Building energy management has been recognized as of significant importance on
improving the overall system efficiency and reducing the greenhouse gas emission …

Recently, research on the fault diagnosis of rotating machinery, especially for the compound
or unknown cases, has drawn increasing attention. Some advanced learning-based …

Koopman operator, acting on an infinite-dimensional Hilbert space of the observables,
provides a global systematic linear representation of nonlinear systems, which is a leading …

Despite the negative externalities on the environment and human health, today's economies
still produce excessive carbon dioxide emissions. As a result, governments are trying to shift …

Surrogate models play a vital role in overcoming the computational challenge in designing
and analyzing nonlinear dynamic systems, especially in the presence of uncertainty. This …