Flocking for Multiagent Systems with Partial Information Exchange Based on Inclusion Principle

This paper investigates the flocking problem of multi-agents with partial information exchange, which means that only part, but not all, of the agents are informed of the group objective. A distributed flocking model based on the inclusion principle is provided to simplify the design and analysis of multi-agent systems. Furthermore, to reduce the communication energy consumption, an improved flocking algorithm based on the model is proposed to achieve stable flocking for all the agents. The stability of the multi-agent system is then established, with the help of the Lyapunov stability theorem and LaSalle’s invariance principle. Especially, considering the individual heterogeneity in both nature and engineering applications, we also investigate the flocking problem of multi-agents with different sensing radiuses and equilibrium distances. Finally, two kinds of simulation results are presented to demonstrate the validity of the proposed results. This work provides an insight not only into the properties of the different species of individual flocking, but also into the theoretical framework for the engineering design of multi-agent systems considering individual heterogeneity.