Automatica (Journal of IFAC)
Reaching a Consensus in a Dynamically Changing Environment: A Graphical Approach
SIAM Journal on Control and Optimization
IEEE Transactions on Signal Processing
SIAM Journal on Control and Optimization
Gossip consensus algorithms via quantized communication
Automatica (Journal of IFAC)
Consensus in networked multi-agent systems via sampled control: fixed topology case
ACC'09 Proceedings of the 2009 conference on American Control Conference
Distributed consensus for multi-agent systems with delays and noises in transmission channels
Automatica (Journal of IFAC)
Brief paper: Second-order consensus in multi-agent dynamical systems with sampled position data
Automatica (Journal of IFAC)
Finite-time convergent gradient flows with applications to network consensus
Automatica (Journal of IFAC)
Synchronization of multi-agent systems with delayed control input information from neighbors
Automatica (Journal of IFAC)
Coding With Side Information for Rate-Constrained Consensus
IEEE Transactions on Signal Processing - Part I
Distributed consensus over digital networks with limited bandwidth and time-varying topologies
Automatica (Journal of IFAC)
Discontinuities and hysteresis in quantized average consensus
Automatica (Journal of IFAC)
Distributed Consensus for Multiagent Systems with Communication Delays and Limited Data Rate
SIAM Journal on Control and Optimization
Hi-index | 22.14 |
This paper considers the average consensus problem for multi-agent systems with continuous-time first-order dynamics. Logarithmic quantization is considered in the communication channels, and continuous-time and sampled-data-based protocols are proposed. For the continuous-time protocol, we give an explicit upper bound of the consensus error in terms of the initial states, the quantization density and the parameters of the network graph. It is shown that in contrast with the case with uniform quantization, the consensus error in the logarithmic quantization case is always uniformly bounded, independent of the quantization density, and the @b-asymptotic average consensus is ensured under the proposed protocol, i.e. the asymptotic consensus error converges to zero as the sector bound @b of the logarithmic quantizer approaches zero. For the sampled-data-based protocol, we give sufficient conditions on the sampling interval to ensure the @b-asymptotic average consensus. Numerical examples are given to demonstrate the effectiveness of the protocols.