Adaptive predefined-time secure consensus tracking control for nonlinear multiagent systems against unknown false data injection attacks

This paper primarily investigates the adaptive predefined-time secure consensus tracking control problem for a class of nonlinear multiagent systems (MASs) against unknown false data injection (FDI) attacks and Bouc–Wen hysteresis. Firstly, by using the Nussbaum functions in the controller design, the conservative limitation that the attack weight’s sign must be consistently positive can not only be relaxed, but also the unknown compound gains problem caused by FDI attacks and input hysteresis can be resolved. Furthermore, the adaptive laws are designed in the form of a new nonlinear differential equation such that the predefined-time stability can be realized. In addition, a feasible adaptive predefined-time secure consensus tracking control strategy is developed based on the backstepping framework and the fuzzy approximation technique. It is demonstrated that all the closed-loop signals are semiglobally uniformly predefined-time-bounded (SGUPTB) and the outputs of all followers eventually synchronously track the output of the leader within a predefined time. Conclusively, a simulation example for the MASs composed of multiple single-link manipulators is provided to testify the effectiveness of the proposed control strategy.