Journal of Systems Science and Complexity

, Volume 31, Issue 6, pp 1525–1540 | Cite as

Bipartite Consensus of Discrete-Time Double-Integrator Multi-Agent Systems with Measurement Noise

  • Cuiqin MaEmail author
  • Weiwei Zhao
  • Yunbo Zhao


The effects of measurement noise are investigated in the context of bipartite consensus of multi-agent systems. In the system setting, discrete-time double-integrator dynamics are assumed for the agent, and measurement noise is present for the agent receiving the state information from its neighbors. Time-varying stochastic bipartite consensus protocols are designed in order to lessen the harmful effects of the noise. Consequently, the state transition matrix of the closed-loop system is analyzed, and sufficient and necessary conditions for the proposed protocol to be a mean square bipartite consensus protocol are given with the help of linear transformation and algebraic graph theory. It is proven that the signed digraph to be structurally balanced and having a spanning tree are the weakest communication assumptions for ensuring bipartite consensus. In particular, the proposed protocol is a mean square bipartite average consensus one if the signed digraph is also weight balanced.


Bipartite consensus discrete-time double-integrator measurement noise multi-agent systems 


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Copyright information

© Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mathematical SciencesQufu Normal UniversityQufuChina
  2. 2.No. 1 Senior Middle School of QufuQufuChina
  3. 3.College of Information EngineeringZhejiang University of TechnologyHangzhouChina

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