Attack-resilient event-triggered formation control of multi-agent systems under periodic DoS attacks using complex Laplacian

J Wang, J Gao, P Wu - ISA transactions, 2022 - Elsevier
This paper concentrates on attack-resilient event-triggered formation control of multi-agent
systems (MASs) under periodic Denial-of-Service (DoS) attacks, which involves a new …

Convolutional neural network based automatic detection of visible faults in a photovoltaic module

NV Sridharan, V Sugumaran - Energy Sources, Part A: Recovery …, 2021 - Taylor & Francis
ABSTRACT Background/Objective: The primary objective of the present study is to
distinguish several visual faults which hinder the performance, reliability and lifetime of …

Smart grid communication: Recent trends and challenges

I Srivastava, S Bhat, AR Singh - Next Generation Smart Grids: Modeling …, 2022 - Springer
Thecomplexity of power distribution network is increasing day by day with rapid increase in
power demand. For monitoring and control of this complex power network, application of …

The MAS4AI framework for human-centered agile and smart manufacturing

A Sidorenko, W Motsch, M van Bekkum… - Frontiers in Artificial …, 2023 - frontiersin.org
Volatility and uncertainty of today's value chains along with the market's demands for low-
batch customized products mandate production systems to become smarter and more …

Converging IoT protocols for the data integration of automation systems in the electrical industry

S Gil, GD Zapata-Madrigal, R García-Sierra… - Journal of Electrical …, 2022 - Springer
Abstract The Internet of Things (IoT) plays an important role in the development of
applications for the Electrical Industry. The data has become essential for the technological …

A hybrid machine learning and meta‐heuristic algorithm based service restoration scheme for radial power distribution system

I Srivastava, S Bhat, VSG Thadikemalla… - … on Electrical Energy …, 2021 - Wiley Online Library
Summary In‐service Restoration (SR), the healthy section of the feeder can be re‐energized
by finding the optimal path for power flow. Through conventional methods which are mainly …

Deep learning-based ensemble model for classification of photovoltaic module visual faults

NV Sridharan, V Sugumaran - Energy Sources, Part A: Recovery …, 2022 - Taylor & Francis
Fault occurrences in photovoltaic (PV) modules can hinder the performance of the system,
resulting in reduced lifetime and performance of the modules. PV module (PVM) faults if …

Model-based diagnosis of multi-agent systems: A survey

M Kalech, A Natan - Proceedings of the AAAI Conference on Artificial …, 2022 - ojs.aaai.org
As systems involving multiple agents are increasingly deployed, there is a growing need to
diagnose failures in such systems. Model-Based Diagnosis (MBD) is a well-known AI …

Consensus problem and formation control for heterogeneous multi-agent systems with switching topologies

C Wang, J Wang, P Wu, J Gao - Electronics, 2022 - mdpi.com
The cooperative control problem of discrete-time multi-agent systems (MASs) is discussed,
and bounded uncertain time-delays and directed switching topologies are considered. By …

Edge Device Fault Probability Based Intelligent Calculations for Fault Probability of Smart Systems

S Li, T Cui, W Viriyasitavat - Tsinghua Science and Technology, 2024 - ieeexplore.ieee.org
In a smart system, the faults of edge devices directly impact the system's overall fault.
Further, complexity arises when different edge devices provide varying fault data. To study …