Data-Driven Distributed Combined Primary and Secondary Control in Microgrids

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The hollow fiber ultrafiltration (HFUF)-based microbial concentration method is widely applied for monitoring pathogenic viruses and microbial indicators in environmental water samples. However, the HFUF-based method can co-concentrate substances that inte ...

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

Increasing adoption of smart meters and phasor measurement units (PMUs) in power distribution networks are enabling the adoption of data-driven/model-less control schemes to mitigate grid issues such as over/under voltages and power-flow congestions. Howev ...

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

During the last two decades, ultrafast in-volume laser-based processing of transparent materials has emerged as a key 3D-printing method for manufacturing a variety of complex integrated photonic devices and micro-parts. Yet, identifying suitable laser pro ...

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

A critical operational challenge in Mobility-on-demand systems is the problem of imbalance between vehicle supply and passenger demand. However, conventional model-based methods require accurate parametric system models with complex nonlinear dynamics that ...

A quantitative analysis of stress in indium tin oxide (ITO) films with varying thicknesses was conducted using high-precision stylus profilometry. The experimental results revealed a transition of the stress type from tensile to compressive as the ITO film ...

Cross regulation is the main technical challenge of a Single-Inductor Multiple-Output (SIMO) dc-dc converter. This paper proposes a multivariable digital controller to suppress the cross regulation of a Single-Inductor Dual-Output (SIDO) buck converter in ...

Data-Driven Distributed Combined Primary and Secondary Control in Microgrids

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Surfactant Treatment for Efficient Gene Detection of Enteric Viruses and Indicators in Surface Water Concentrated by Ultrafiltration

Data-driven modeling of beam loss in the LHC

Experimental Validation of Model-less Robust Voltage Control using Measurement-based Estimated Voltage Sensitivity Coefficients

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Third-harmonic generation monitoring of femtosecond-laser-induced in-volume functional modifications

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Center-aware Adversarial Augmentation for Single Domain Generalization

Validating functional redundancy with mixed generative adversarial networks

Data-enabled Predictive Control for Empty Vehicle Rebalancing

Quantitative study of the thickness-dependent stress in indium tin oxide thin films

Multivariable Control of Single-Inductor Dual-Output Buck Converters