scholarly journals The Application of the Multi-Agent Coverage and Self-Healing Control Based on a Swarm Intelligence SONM and Potential Function Approach

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 72671-72682
Author(s):  
Zhenhua Pan ◽  
Ling Shu ◽  
Hongbin Deng ◽  
Dongfang Li
Keyword(s):  
Swarm Intelligence ◽  
Potential Function ◽  
Function Approach ◽  
Self Healing ◽  
Multi Agent

A multi-agent based self-healing smart grid

2013 ◽  
Author(s):  
Ruchi Gupta ◽  
Deependra Kumar Jha ◽  
Vinod Kumar Yadav ◽  
Sanjeev Kumar
Keyword(s):  
Smart Grid ◽  
Self Healing ◽  
Agent Based ◽  
Multi Agent

An Effectiveness Modelling Approach for IoT-Based Smart Grids

2021 ◽  
pp. 92-111
Author(s):  
Dongming Fan ◽  
Yi Ren ◽  
Qiang Feng
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Information Technologies ◽  
Self Healing ◽  
New Paradigm ◽  
Agent Based ◽  
Efficient Energy ◽  
Real Time Analysis ◽  
Multi Agent

The smart grid is a new paradigm that enables highly efficient energy production, transport, and consumption along the whole chain from the source to the user. The smart grid is the combination of classical power grid with emerging communication and information technologies. IoT-based smart grid will be one of the largest instantiations of the IoT in the future. The effectiveness of IoT-based smart grid is mainly reflected in observability, real-time analysis, decision-making, and self-healing. A proper effectiveness modeling approach should maintain the reliability and maintainability of IoT-based smart grids. In this chapter, a multi-agent-based approach is proposed to model the architecture of IoT-based smart grids. Based on the agent framework, certain common types of agents are provided to describe the operation and restoration process of smart grids. A case study is demonstrated to model an IoT-based smart grid with restoration, and the interactive process with agents is proposed simultaneously.

Distributed Multi-Agent Systems for a Collective Construction Task based on Virtual Swarm Intelligence

2010 ◽  
Vol 1 (2) ◽  
pp. 58-79 ◽  
Author(s):  
Yan Meng ◽  
Yaochu Jin
Keyword(s):  
Swarm Intelligence ◽  
Random Search ◽  
Building Blocks ◽  
Local Area ◽  
Multi Agent Systems ◽  
Virtual Particle ◽  
Multi Agent ◽  
Bounded Area ◽  
Collective Construction ◽  
Construction Task

In this paper, a virtual swarm intelligence (VSI)-based algorithm is proposed to coordinate a distributed multi-robot system for a collective construction task. Three phases are involved in a construction task: search, detect, and carry. Initially, robots are randomly located within a bounded area and start random search for building blocks. Once the building blocks are detected, agents need to share the information with their local neighbors. A distributed virtual pheromone-trail (DVP) based model is proposed for local communication among agents. If multiple building blocks are detected in a local area, agents need to make decisions on which agent(s) should carry which block(s). To this end, a virtual particle swarm optimization (V-PSO)-based model is developed for multi-agent behavior coordination. Furthermore, a quorum sensing (QS)-based model is employed to balance the tradeoff between exploitation and exploration, so that an optimal overall performance can be achieved. Extensive simulation results on a collective construction task have demonstrated the efficiency and robustness of the proposed VSI-based framework.

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