Average Consensus Tracking of Time-varying Reference Inputs for Multi-agent Systems with Communication Delay

We investigate the dynamic average-consensus tracking problem of multi-agent systems with time-varying reference inputs and communication delay, and propose a proportional-integral consensus tracking algorithm. Using a fixed, balanced, and strongly connected topology, and based on a matrix analysis, sufficient conditions are obtained for converging the multi-agent system to the average value of the time-varying reference inputs with and without quantized communication data, respectively. Numerical simulation results verify the accuracy of the theoretical results.