A Follower-Based Control Allocation in Multi-Agent Networks

This paper investigates the consensus problem in a multi-agent system with a leader, using the concept of swarm intelligence. Matrix equations are given to obtain equilibrium state of the network, and the average-based control input is defined accordingly. Two network control rules are subsequently developed, where in one of them the control input is only applied to the leader, and in the other one it is only applied to the neighbors of the leader (follower-based control allocation strategy or swarm intelligence approach). It is shown that the latter control strategy has a faster convergence rate. Simulations confirm the efficacy of the proposed follower-based control allocation strategy.