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Found 8 papers, 1 papers with code
Control Designs for Critical-Continegency Responsible Grid-Following Inverters and Seamless Transitions To and From Grid-Forming Modes
This article introduces two control frameworks: one for Grid-Following (GFL) inverters aiding Grid-Forming (GFM) inverters in voltage regulation during large contingency events and optimizing power transactions under normal conditions; and another for seamless transitions between grid-tied and grid-isolated setups, managing voltage transient characteristics.
Sparse Linear Regression with Constraints: A Flexible Entropy-based Framework
We demonstrate the efficacy and flexibility of our proposed approach in incorporating a variety of practical constraints, that are otherwise difficult to model using the existing benchmark methods.
Enhanced Grid Following Inverter (E-GFL): A Unified Control Framework for Stiff and Weak Grids
We present the stability, robust stability, and performance of the original GFL MIMO closed-loop system through our proposed 2-SISO closed-loop framework.
Sequence Generation via Subsequence Similarity: Theory and Application to UAV Identification
The ability to generate synthetic sequences is crucial for a wide range of applications, and recent advances in deep learning architectures and generative frameworks have greatly facilitated this process.
A Novel Maximum-Entropy-Driven Technique for Low-Rank Orthogonal Nonnegative Matrix Factorization with $\ell_0$-Norm sparsity Constraint
In data-driven control and machine learning, a common requirement involves breaking down large matrices into smaller, low-rank factors that possess specific levels of sparsity.
Towards Efficient Modularity in Industrial Drying: A Combinatorial Optimization Viewpoint
The industrial drying process consumes approximately 12% of the total energy used in manufacturing, with the potential for a 40% reduction in energy usage through improved process controls and the development of new drying technologies.
A Clustering Approach to Edge Controller Placement in Software Defined Networks with Cost Balancing
In this work we introduce two novel deterministic annealing based clustering algorithms to address the problem of Edge Controller Placement (ECP) in wireless edge networks.
On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset
Typically clustering algorithms provide clustering solutions with prespecified number of clusters.
