The utilization of surrogate models to approximate complex systems has recently gained
increased popularity. Because of their capability to deal with black-box problems and lower …

The bio-inspired algorithms are novel, modern, and efficient tools for the design of electrical
machines. However, from the mathematical point of view, these problems belong to the most …

Abstract The Surrogate Modeling Toolbox (SMT) is an open-source Python package that
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …

Recent studies show that synchronous reluctance motors (SynRMs) present promising
technologies. As a result, research on trending SynRMs drive systems has expanded. This …

This paper puts forward a PD-type iterative learning control algorithm for a class of discrete
spatially interconnected systems with unstructured uncertainty. By lifting and changing the …

Reference implementation of Digital Twins for electrical energy conversion systems is an
important and open question in the industrial domain. Digital Twins can predict the future …

Recently, there has been a growing interest in mixed-categorical metamodels based on
Gaussian Process (GP) for Bayesian optimization. In this context, different approaches can …

There is a great potential in small satellite technology for testing new sensors, processes,
and technologies for space applications. Antennas need careful design when develo** a …

Electro-mechanic devices for the automatic changing of gear were tested by company using
the same accelerated life testing procedures in different stages of the product development …

In recent decades, the genetic algorithm (GA) has been extensively used in the design
optimization of electromagnetic devices. Despite the great merits possessed by the GA, its …