Leader-following consensus of multi-agent system based on cellular neural networks framework

Abstract

Cellular neural networks have been applied in many fields and have shown good results. Therefore, this article studies the leader-following consensus problem (MSALFC) of multi-agent systems with fixed directed topology under cellular neural networks framework (CNNF). Compared with the common consensus problem, agents' communication topology is reconstructed through CNNF. Then, the breadth-first algorithm is used to cut unnecessary connections in the system. So that the undirected communication topology based on CNNF is transformed into a directed topology with only one spanning tree and communication protocol are constructed. Finally, an effective control protocol is designed to help the system achieve leader-follower consensus and Lyapunov stability theory is used to establish the sufficient condition to guarantee the realization of MSALFC. The communication protocol based on CNNF can not only effectively achieve the consistency of the system, but also reduce the communication traffic in the System. Numerical simulation is given to illustrate the theoretical results.