Bipartite Linearχ-Consensus of Double-Integrator Multi-Agent Systems With Measurement Noise

2017 ◽  
Vol 20 (1) ◽  
pp. 577-584 ◽  
Author(s):  
Cuiqin Ma ◽  
Weiwei Zhao ◽  
Yun-Bo Zhao
Keyword(s):  
Measurement Noise ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Double Integrator

scholarly journals Event-Triggered Bipartite Consensus of Single-Integrator Multi-Agent Systems with Measurement Noise

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Cui-Qin Ma ◽  
Yun-Bo Zhao ◽  
Wei-Guo Sun
Keyword(s):  
Sufficient Conditions ◽  
Measurement Noise ◽  
Mean Square ◽  
Multi Agent Systems ◽  
Negative Effects ◽  
Consensus Protocol ◽  
Agent Systems ◽  
Multi Agent ◽  
Bipartite Consensus ◽  
Event Triggered

Event-triggered bipartite consensus of single-integrator multi-agent systems is investigated in the presence of measurement noise. A time-varying gain function is proposed in the event-triggered bipartite consensus protocol to reduce the negative effects of the noise corrupted information processed by the agents. Using the state transition matrix, Ito^ formula, and the algebraic graph theory, necessary and sufficient conditions are given for the proposed protocol to yield mean square bipartite consensus. We find that the weakest communication requirement to ensure the mean square bipartite consensus under event-triggered protocol is that the signed digraph is structurally balanced and contains a spanning tree. Numerical examples validated the theoretical findings where the system shows no Zeno behavior.

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