Hierarchical Average-Tracking Algorithm for Multiagent Systems With Unmatched Constant References Signals

摘要

This brief addresses the average-tracking problem of heterogeneous linear multi-agent systems, which comprise leading agents and following agents. Leading agents access the constant reference signals, but the following agents do not have reference signals. A hierarchical average-tracking algorithm, which is composed of a distributed average-consensus seeking algorithm and a decentralized tracking control algorithm, is designed for the agents reaching the average value of leading agents’ reference signals. With the help of graph theory and matrix theory, consensus convergence conditions are obtained for the agents with the directed and balanced topology. Effectiveness of proposed algorithm is illustrated by numerical simulations.