Convergence of Type-Symmetric and Cut-Balanced Consensus Seeking Systems

We consider continuous-time consensus seeking systems whose time-dependent interactions are cut-balanced, in the following sense: if a group of agents influences the remaining ones, the former group is also influenced by the remaining ones by at least a proportional amount. Models involving symmetri...

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Bibliographic Details
Main Authors: Hendrickx, Julien (Author), Tsitsiklis, John N. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-10-20T16:53:27Z.
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Online Access:Get fulltext
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100 1 0 |a Hendrickx, Julien  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Laboratory for Information and Decision Systems  |e contributor 
100 1 0 |a Tsitsiklis, John N.  |e contributor 
700 1 0 |a Tsitsiklis, John N.  |e author 
245 0 0 |a Convergence of Type-Symmetric and Cut-Balanced Consensus Seeking Systems 
260 |b Institute of Electrical and Electronics Engineers (IEEE),   |c 2014-10-20T16:53:27Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/90991 
520 |a We consider continuous-time consensus seeking systems whose time-dependent interactions are cut-balanced, in the following sense: if a group of agents influences the remaining ones, the former group is also influenced by the remaining ones by at least a proportional amount. Models involving symmetric interconnections and models in which a weighted average of the agent values is conserved are special cases. We prove that such systems always converge. We give a sufficient condition on the evolving interaction topology for the limit values of two agents to be the same. Conversely, we show that if our condition is not satisfied, then these limits are generically different. These results allow treating systems where the agent interactions are a priori unknown, being for example random or determined endogenously by the agent values. 
520 |a National Science Foundation (U.S.) (Grant ECCS-0701623) 
546 |a en_US 
655 7 |a Article 
773 |t IEEE Transactions on Automatic Control