Abstract: In this paper, we study the cooperative output regulation problem for heterogeneous linear multi-agent systems by a distributed feedforward approach. In comparison with existing results for ...

Abstract: This review paper provides an overview of the latest developments in artificial intelligence (AI)-based antenna design and optimization for wireless communications. Machine learning (ML) and ...

Abstract: For the purpose of shortening response time and improved anti-disturbance performance of the permanent magnet synchronous motor (PMSM) drives, a compound control method using improved ...

Abstract: The interdependence of different energy forms in multiple energy systems (MESs) could leverage their synergies to reduce carbon emissions. However, such synergies cannot be exploited without ...

Abstract: This standard specifies interchange and arithmetic formats and methods for binary and decimal floating-point arithmetic in computer programming environments. This standard specifies ...

Abstract: With the increasing proportion of renewable power generations, the frequency control of microgrid becomes more challenging due to stochastic power generations and dynamic uncertainties. The ...

Abstract: It is an exciting time for power systems as there are many ground-breaking changes happening simultaneously. There is a global consensus in increasing the share of renewable energy-based ...

Abstract: This work proposes an improved analytical model and a novel location method for irreversible demagnetization (ID). The analytical model accounts for the nonlinearities from the ...

Abstract: The goal of seismic inversion is to obtain subsurface properties from surface measurements. Seismic images have proven valuable, even crucial, for a variety of applications, including ...

Abstract: This article proposes a new framework using physics-informed neural networks (PINNs) to simulate complex structural systems that consist of single and double beams based on Euler–Bernoulli ...

Abstract: Electroencephalography (EEG) has been a staple method for identifying certain health conditions in patients since its discovery. Due to the many different types of classifiers available to ...

Abstract: With the widespread application of temporal knowledge graph reasoning (TKGR) models, there is an increasing demand to reduce the memory consumption and enhance the reasoning efficiency.