Relating the Automation of Functions in Multiagent Control Systems to a System Engineering Representation

Multiagent systems controlling robots can have different structures, depending on a way of generating decision in these systems. Decisions can be work out in centralized, decentralized or even hybrid way (hybrid system is a connection of both centralized and decentralized systems). In the case of controlling a team of underwater vehicles, it is significant to examine different structures of multiagent systems for choosing the best one for defined underwater task. In the paper, results of operation of three different structures (centralized, dispersed - decentralized and hybrid) of multiagent control systems of underwater vehicles team were presented. The systems were tested in predator-prey problem. In this problem, a team of three underwater vehicles had to catch another underwater robot escaping with larger velocity.

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Best of Both Worlds: Using Explainable AI and Model-based System Engineering to Design Flight Guidance and Control Systems

AIAA AVIATION 2021 FORUM ◽

10.2514/6.2021-2779 ◽

2021 ◽

Author(s):

Lance Sherry ◽

James Baldo ◽

Brett Berlin ◽

Oleksandra Snisarevska

Keyword(s):

Control Systems ◽

System Engineering ◽

Guidance And Control ◽

Model Based ◽

Explainable Ai ◽

Flight Guidance ◽

And Control

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Motion Feasibility Conditions for Multiagent Control Systems on Lie Groups

IEEE Transactions on Control of Network Systems ◽

10.1109/tcns.2019.2925264 ◽

2020 ◽

Vol 7 (1) ◽

pp. 493-502 ◽

Cited By ~ 4

Author(s):

Leonardo J. Colombo ◽

Dimos V. Dimarogonas

Keyword(s):

Control Systems ◽

Lie Groups ◽

Multiagent Control ◽

Systems On Lie Groups

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Test Bed for Multiagent Control Systems in Road Traffic Management

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198105191000113 ◽

2005 ◽

Vol 1910 (1) ◽

pp. 108-115

Author(s):

R. T. van Katwijk ◽

P. van Koningsbruggen ◽

B. De Schutter ◽

J. Hellendoorn

Keyword(s):

Control Systems ◽

Traffic Control ◽

Traffic Management ◽

Multiagent System ◽

Road Traffic ◽

Heterogeneous Traffic ◽

Distributed Artificial Intelligence ◽

Test Bed ◽

Coordination Problem ◽

Multiagent Control

A test bed for multiagent control systems in road traffic management is presented. As the complexity of traffic control on a network grows, it becomes more difficult to coordinate the actions of the large number of heterogeneous traffic management instruments that are available in the network. One way of handling this complexity is to divide the coordination problem into smaller coherent subproblems that can be solved with a minimum of interaction. Multiagent systems can aid in the distribution of the problem (over the various agents that compose the multiagent system) and facilitate the coordination of the activities of these agents when required. In the literature, no consensus exists about the best configuration of the traffic-managing multiagent system and how the activities of the agents that compose the multiagent system should be coordinated. The decomposition of a problem into various subproblems is an active field of research in the world of distributed artificial intelligence. A survey of approaches reported in the literature is presented. Subsequently, both the test bed and the modules that compose it are introduced. Finally, an application is presented that illustrates some of the research the test bed has made possible.

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