Fuzzy-model-based bipartite synchronization for nonlinear cooperation-competition networks with semi-Markov switching topologies under FDI attacks

Abstract

This paper addresses the bipartite synchronization issue for a class of continuous-time nonlinear cooperation-competition networks, in which the relationships between network systems coexist with coordination and antagonism with the network topology switching obeys a semi-Markov jump process. First, the Takagi-Sugeno fuzzy method is employed to modify the nonlinear function in the networks to deal with this complexity. Then, a fuzzy security control law is devised for the networks to ensure that systems enable bipartite synchronization when communication channels are vulnerable to false data injection attacks. In addition, sufficient conditions are provided to guarantee that the resulting closed-loop system is stochastically stable with a prescribed passive performance index by constructing suitable Lyapunov functions. Lastly, the correctness of the proposed controller is validated by a numerical example and a single-link robot arm model example.