Adaptive Attack-free Output-feedback Consensus Protocol for Nonlinear MASs

This paper works on the consensus problem of nonlinear multi-agent systems (MASs) under undirected connected graphs. Based on relative output information of neighboring agents, fully distributed adaptive attack-free protocol is presented, where speaking of attack-free protocol we mean no observer information can be transmitted via communication topology. Firstly, the fixed-time observer is designed to estimate the consensus error based on relative output measurement among neighboring agents. And the consensus error estimation is used to generate the adaptive protocol. The adaptive gain is to estimate the communication connectivity and the upper bound of residual error; while the adaptive gain matrix is to tackle the unknown constant matrix in nonlinearity. The proposed protocol is in essence attack-free, since no information exchange is undertaken during the whole process. Moreover, such design structure takes the advantage of releasing communication burden.