Cloud-Based Quasi-Average-Consensus for Time-Varying Networked Multi-Agent Systems Under Deception Attacks

In this paper, the quasi-average-consensus control problem of time-varying networked multi-agent systems (NMASs) is studied based on cloud, in which each agent is subject to a stochastic nonlinear disturbance and a deception attack signal. The information from the agent and its neighbors is required to design a protocol with cloud-based time-varying output feedback form when deception attacks occur between its sensor and the cloud-based controller. Recursive linear matrix inequality and stochastic analysis are used to establish sufficient condition of the quasi-average-consensus. In addition, an optimization algorithm is proposed to ensure the local optimal quasi-average-consensus. Effectiveness of the proposed scheme and method is demonstrated by a simulation result.