Abstract
In this chapter, the Coordinated Hybrid Agent (CHA) framework is introduced for the distributed control and coordination of multi-agent systems. In this framework, the control of multi-agent systems is regarded as achieving decentralized control and coordination of agents. Each agent is modeled as a CHA 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. The intelligent coordination layer deals with the planning, coordination, decision-making and computation of the agent. The hybrid control layer of the framework takes the output of the intelligent coordination layer and generates discrete and continuous control signals to control the overall process. In order to verify the feasibility of the framework, experiments for multi-agent systems are implemented. The framework is applied to a multi-agent system consisting of an overhead crane, a mobile robot and a robot manipulator. The agents are able to cooperate and coordinate to achieve the global goal. In addition, the stability of systems modeled using the framework is also analyzed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Russell, S., Norvig, P.: Artificial Intelligence - A Modern Approach. Prentice-Hall, Englewood Cliffs (2003)
Genco, A.: Mobile Agents - Principles of Operation and Applications. WIT Press, Southampton, UK (2008)
Brennan, W., Fletcher, M., Norrie, D.H.: An agent-based approach to reconfiguration of real-time distributed control systems. IEEE Transactions on Robotics and Automation 18(4), 444–449 (2002)
Baeza, J., Gabriel, D., Bejar, J., Lafuente, J.: A distributed control system based on agent architecture for wastewater treatment. Computer-Aided Civil and Infrastructure Engineering 17(2), 93–103 (2002)
Earl, M.G., D’Andrea, R.: Modeling and control of a multi-agent system using mixed integer linear programming. In: Proceedings of 41st IEEE Conference on Decision and Control, vol. 1, pp. 107–111 (2002)
Crespi, V., Cybenko, G., Rus, D., Santini, M.: Decentralized control for coordinated flow of multi-agent systems. In: Proceedings of the 2002 International Joint Conference on Neural Networks (IJCNN), pp. 2604–2609 (2002)
Garza, L.E., Cantu, F.J., Acevedo, S.: Faults diagnosis in industrial processes with a hybrid diagnostic system. In: Coello Coello, C.A., de Albornoz, Á., Sucar, L.E., Battistutti, O.C. (eds.) MICAI 2002. LNCS (LNAI), vol. 2313, pp. 536–545. Springer, Heidelberg (2002)
Indrayadi, Y., Valckenaers, H.P., Van Brussel, H.: Dynamic multi-agent dispatching control for flexible manufacturing systems. In: Proceedings 13th International Workshop on Database and Expert Systems Applications, pp. 489–493 (2002)
Pereira, G.A.S., Pimentel, B.S., Chaimowicz, L., Campos, M.F.M.: Coordination of multiple mobile robots in an object carrying task using implicit communication. In: Proceedings of the 2002 IEEE International Conference on Robotics & Automation, Washington DC, USA, pp. 281–286 (2002)
Dasgupta, P.: A multiagent swarming system for distributed automatic target recognition using unmanned aerial vehicles. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 38(3), 549–563 (2008)
Baker, C.R., Dolan, J.M.: Street Smarts for Boss. IEEE Robotics & Automation Magazine, 78–87 (March 2009)
Broten, G.S., Mackay, D., Monckton, S.P., Collier, J.: The Robotics Experience - Beyond Components, and Middleware. IEEE Robotics & Automation Magazine, 46–54 (March 2009)
Kress-Gazit, H., Conner, D.C., Choset, H., Rizzi, A.A., Pappas, G.J.: Courteous Cars - Decentralized Multiagent Traffic Coordination. IEEE Robotics & Automation Magazin, 30–38 (March 2008)
Fregene, K., Kennedy, D., Wang, D.: HICA: A Framework for Distributed Multiagent Control. In: Proceedings of IASTED International Conference on Intelligent Systems and Control, pp. 187–192 (2001)
Li, H., Karray, F., Basir, O., Song, I.: A framework for coordinated control of multi-agent systems and its applications. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 38(3) (2008)
Li, H., Karray, F., Basir, O., Song, I.: A coordinated hybrid agent framework as applied to heterogeneous multi-agent Control. In: Proceedings of the 2nd International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, Philippines (2005)
Ferber, J.: Multi-Agent Systems - An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1999)
Hewitt, C.: Viewing Control Structures as Patterns of Passing Messages. Artificial Intelligence 8(3), 323–364 (1977)
Erman, L., Hayes-Roth, F., Lesser, V., Reddy: The hearsay-ii speech understanding system: Integrating knowledge resolve uncertainty. ACM Computing Surveys 12 (1980)
Passino, K.M., Burgess, K.L.: Stability Analysis of Discrete Event Systems. John Wiley & Sons, Inc., Chichester (1998)
Passino, K.M., Michel, A.N., Antsaklis, P.J.: Lyapunov Stability of a Class of Discrete Event Systems. IEEE Transactions on Automatic Control 39(2), 269–279 (1994)
Lygeros, J.: Hierarchical, Hybrid Control of Large Systems. PhD Thesis, University of California, Berkeley, CA (1996)
Shoham, Y., Tennenholtz, M.: On social laws for artificial agent societies: off-line design. Artificial Intelligence 73(1–2), 231–252 (1995)
Cho, Y.C., Cassandras, C.G., Pepyne, D.L.: Forward decomposition algorithms for optimal control of a class of hybrid systems. International Journal of Robust and Nonlinear Control 11 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Li, H., Karray, F., Basir, O. (2010). A Framework for Coordinated Control of Multi-Agent Systems. In: Srinivasan, D., Jain, L.C. (eds) Innovations in Multi-Agent Systems and Applications - 1. Studies in Computational Intelligence, vol 310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14435-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-14435-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14434-9
Online ISBN: 978-3-642-14435-6
eBook Packages: EngineeringEngineering (R0)