The convergence analysis of bat-inspired consensus protocols with nonlinear dynamics

This paper proposes a new class of cooperative bat-inspired consensus protocols including a collection of nonlinear dynamics for multi-agent coordination. The proposed consensus protocols embed a suggested convergence direction which can improve the performance of convergence time. This suggested convergence direction can be used to design a distributed algorithm for controlling multi-agent systems while simultaneously solving a large-scale optimization problem. By virtue of a Lyapunov-based method, we show that the proposed bat-inspired consensus protocols can reach the global consensus asymptotically. Meanwhile, the bat-inspired consensus protocols subjected to external disturbance are also considered. We give the theoretical proof of a sufficient condition for guaranteeing the convergence of the extended consensus protocols with disturbances.