Model-free adaptive cluster consensus control for nonlinear multi-agent systems under DoS attack

Aiming at the cluster consensus problem for a class of unknown discrete time nonlinear multi-agent systems with denial of service(DoS) attacks, a model-free adaptive control algorithm is proposed. It is assumed that the system has a fixed topology and only part of the agents in each cluster can receive the leader information. Firstly, a dynamic linearization method is used to construct a data relationship model for multi agent systems, and the periodic DoS attack model conforms to Bernoulli distribution is constructed by limiting the corresponding attack time and frequency. A data-driven cluster tracking control protocol is designed by combining the cluster consensus error under the coupling effect among agents. Then, the sufficient conditions to ensure the convergence of tracking error under the sense of mathematical expectation are given by the method of compression mapping, and theoretically analyzes the convergence of the algorithm. Finally, simulation results verify the effectiveness of the proposed algorithm.