Optimal energy management and control aspects of distributed microgrid using multi-agent systems

This paper investigates the consensus tracking problem for second-order multi-agent systems without/with input delays. Randomized quantization scheme is considered in the communication channels, and impulsive consensus tracking algorithms using position-only information are proposed for the consensus tracking of multi-agent systems. Based on the algebraic graph theory and stability theory of impulsive systems, sufficient and necessary conditions for consensus tracking are studied. It is found that consensus tracking for second-order multi-agent systems without/with input delays can be achieved by appropriately choosing the sampling period and control gains which are determined by second/third degree polynomials. Simulations are performed to validate the theoretical results.

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Spatial Decision Support and Multi-Agent Systems: Application to Forest Fire Prevention and Control

Spatial Management of Risks ◽

10.1002/9780470611357.ch7 ◽

2010 ◽

pp. 151-168

Author(s):

Franck Guarnieri ◽

Alain Jaber ◽

Jean-Luc Wybo

Keyword(s):

Decision Support ◽

Forest Fire ◽

Prevention And Control ◽

Fire Prevention ◽

Multi Agent Systems ◽

Spatial Decision Support ◽

Agent Systems ◽

Forest Fire Prevention ◽

Multi Agent ◽

And Control

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Reports on the 2018 AAAI Spring Symposium Series

AI Magazine ◽

10.1609/aimag.v39i4.2824 ◽

2018 ◽

Vol 39 (4) ◽

pp. 29-35

Author(s):

Christopher Amato ◽

Haitham Bou Ammar ◽

Elizabeth Churchill ◽

Erez Karpas ◽

Takashi Kido ◽

...

Keyword(s):

Artificial Intelligence ◽

Intelligent Agents ◽

Well Being ◽

Machine Intelligence ◽

Multi Agent Systems ◽

Agent Systems ◽

Internet Of Everything ◽

Symposium Series ◽

Multi Agent ◽

And Control

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, presented the 2018 Spring Symposium Series, held Monday through Wednesday, March 26–28, 2018, on the campus of Stanford University. The seven symposia held were AI and Society: Ethics, Safety and Trustworthiness in Intelligent Agents; Artificial Intelligence for the Internet of Everything; Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being AI; Data Efficient Reinforcement Learning; The Design of the User Experience for Artificial Intelligence (the UX of AI); Integrated Representation, Reasoning, and Learning in Robotics; Learning, Inference, and Control of Multi-Agent Systems. This report, compiled from organizers of the symposia, summarizes the research of five of the symposia that took place.

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Multi-Agent Control System for the Movement of Uniaxial Objects

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.237.183 ◽

2015 ◽

Vol 237 ◽

pp. 183-188

Author(s):

Mirosław Mrozek

Keyword(s):

Control System ◽

Point Of View ◽

Multi Agent Systems ◽

Control Groups ◽

Agent Systems ◽

Multi Agent ◽

Agent Control ◽

Classical Control ◽

And Control ◽

Multi Agents

Multi-agent systems are used mainly in IT solutions and control groups of robots. From the point of view of classical control architectures, they are a kind of distributed systems in which nodes perform advanced algorithms, usually associated with the technology of artificial intelligence, and they can be considered as agents. The article describes the multi-agents control system of objects of uniaxial movements. An example of such a system to control a repository with movable racks with electric motors is presented. Each rack acts as an agent through the implemented control of the resources of embedded microcontrollers. Such a system provides high quality control, guaranteeing long-lasting, trouble-free operation while maintaining the safety of both service and stored items.

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