A framework for coordinated control of multiagent systems and its applications

被引:27
作者
Li, Howard [1 ]
Karray, Fakhreddine [1 ]
Basir, Otman [1 ]
Song, Insop [2 ]
机构
[1] Univ Waterloo, Dept Elect & Comp Engn, Pattern Anal & Machine Intelligence Lab, Waterloo, ON N2L 3G1, Canada
[2] Ericsson Inc, Warrendale, PA 15086 USA
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS | 2008年 / 38卷 / 03期
基金
加拿大自然科学与工程研究理事会;
关键词
control of multiagent systems; framework; hybrid control systems; multiagent systems (MASs);
D O I
10.1109/TSMCA.2008.918591
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a framework is proposed for the distributed control and coordination of multiagent systems (MASs). In the proposed framework, the control of MASs is regarded as achieving decentralized control and coordination of agents. Each agent is modeled as a coordinated hybrid agent, which is composed of an intelligent coordination layer and a hybrid control layer. The intelligent coordination layer takes the coordination input, plant input, and workspace input. In the proposed framework, we describe the coordination mechanism in a domain-independent way, i.e., as simple abstract primitives in a coordination rule base for certain dependence relationships between the activities of different agents. The intelligent coordination layer deals with the planning, coordination, decision making, and computation of the agent. The hybrid control layer of the proposed framework takes the output of the intelligent coordination layer and generates discrete and continuous control signals to control the overall process. To verify the feasibility of the proposed framework, experiments for both heterogeneous and homogeneous NIASs are implemented. The proposed framework is applied to a multicrane system, a multiple robot system, and a MAS consisting of an overhead crane, a mobile robot, and a robot manipulator. It is demonstrated that the proposed framework can model the three NIASs. The agents in these systems are able to cooperate and coordinate to achieve a global goal. In addition, the stability of systems modeled using the proposed framework is also analyzed.
引用
收藏
页码:534 / 548
页数:15
相关论文
共 40 条
[1]  
Akella S, 2002, 2002 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS, P624, DOI 10.1109/ROBOT.2002.1013428
[2]  
[Anonymous], READINGS DISTRIBUTED
[3]   A distributed control system based on agent architecture for wastewater treatment [J].
Baeza, J ;
Gabriel, D ;
Béjar, J ;
Lafuente, J .
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2002, 17 (02) :93-103
[4]   Decentralized supervisory control with communicating controllers [J].
Barrett, C ;
Lafortune, S .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (09) :1620-1638
[5]   An agent-based approach to reconfiguration of real-time distributed control systems [J].
Brennan, RW ;
Fletcher, M ;
Norrie, DH .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 2002, 18 (04) :444-451
[6]  
Chli M, 2003, IEEE SYS MAN CYBERN, P551
[7]   Forward decomposition algorithms for optimal control of a class of hybrid systems [J].
Cho, YC ;
Cassandras, CG ;
Pepyne, DL .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2001, 11 (05) :497-513
[8]   Decentralized control for coordinated flow of multi-agent systems [J].
Crespi, V ;
Cybenko, G ;
Rus, D ;
Santini, M .
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3, 2002, :2604-2609
[9]  
Earl MG, 2002, IEEE DECIS CONTR P, P107, DOI 10.1109/CDC.2002.1184476
[10]  
Ferber J, 1999, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, V1st