Distributed Dynamic Averaging Tracking Without Rate Measurements

This article introduces a dynamic average tracking algorithm for multiagent systems over weight-balanced direct graphs. Toward the end, we propose a proportional-integral distributive observer for each system with exponential convergence. In particular, the proposed algorithm only requires mild initialization conditions, does not rely on the time derivatives of reference signals and can ensure average consensus tracking with bounded steady-state error. The simulation results verified the performance of the proposed scheme.