Consensus of a Kind of Dynamical Agents in Network with Time Delays

International Journal of Communications, Network and System Sciences (Impact Factor: 0.9). 01/2010; 3(11):893-898. DOI: 10.4236/ijcns.2011.311121
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Available from: Baoshan Zhang, Sep 22, 2014
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    ABSTRACT: In this paper, the consensus problems for networks of dynamic agents are investigated. The agent dynamics is adopted as a typical point mass model based on the Newton's law. The average-consensus problem is proposed for such class of networks, which includes two aspects, the agreement of the states of the agents and the convergence to zero of the speeds of the agents. A linear consensus protocol for such networks is established for solving such a consensus problem that includes two parts, a local speed feedback controller and the interactions from the finite neighbours. Two kinds of topology are discussed: one is fixed topology, the other is switching one. The convergence analysis is proved and the protocol performance is discussed as well. The simulation results are presented that are consistent with our theoretical results. Copyright © 2006 John Wiley & Sons, Ltd.
    International Journal of Robust and Nonlinear Control 07/2007; 17(10‐11):941 - 959. DOI:10.1002/rnc.1144 · 3.18 Impact Factor
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    ABSTRACT: Bacteria, bees, and birds often work together in groups to find food. A group of robots can be designed to coordinate their activities to search for and collect objects. Networked cooperative uninhabited autonomous vehicles are being developed for commercial and military applications. Suppose that we refer to all such groups of entities as "social foraging swarms". In order for such multiagent systems to succeed it is often critical that they can both maintain cohesive behaviors and appropriately respond to environmental stimuli (e.g., by optimizing the acquisition of nutrients in foraging for food). In this paper, we characterize swarm cohesiveness as a stability property and use a Lyapunov approach to develop conditions under which local agent actions will lead to cohesive foraging even in the presence of "noise" characterized by uncertainty on sensing other agent's position and velocity, and in sensing nutrients that each agent is foraging for. The results quantify earlier claims that social foraging is in a certain sense superior to individual foraging when noise is present, and provide clear connections between local agent-agent interactions and emergent group behavior. Moreover, the simulations show that very complicated but orderly group behaviors, reminiscent of those seen in biology, emerge in the presence of noise.
    IEEE Transactions on Automatic Control 02/2004; 49(1-49):30 - 44. DOI:10.1109/TAC.2003.821416 · 2.78 Impact Factor
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    ABSTRACT: Vicsek et al. proposed (1995) a simple but compelling discrete-time model of n autonomous agents {i.e., points or particles} all moving in the plane with the same speed but with different headings. Each agent's heading is updated using a local rule based on the average of its own heading plus the headings of its "neighbors". In their paper, Vicsek et al. provide simulation results which demonstrate that the nearest neighbor rule they are studying can cause all agents to eventually move in the same direction despite the absence of centralized coordination and despite the fact that each agent's set of nearest neighbors change with time as the system evolves. This paper provides a theoretical explanation for this observed behavior. In addition, convergence results are derived for several other similarly inspired models. The Vicsek model proves to be a graphic example of a switched linear system which is stable, but for which there does not exist a common quadratic Lyapunov function.
    Decision and Control, 2002, Proceedings of the 41st IEEE Conference on; 01/2003