Adaptive Secure Bipartite Consensus Tracking Control for Nonlinear Multiagent Systems Under FDI Attacks With Predefined Accuracy

This article mainly considers the adaptive secure bipartite consensus tracking control (BCTC) problem for nonlinear multiagent systems (MASs) under false data injection (FDI) attacks with predefined accuracy. Since FDI attacks produce unknown attack gains, which increases the difficulty of the controller design, an adaptive secure control strategy is given based on the essential property of Nussbaum functions. By improving the traditional coordinate transformation in the current literatures that can only achieve unilateral consensus control, a backstepping-based control algorithm is put forward attaining bilateral consensus control. In addition, the appropriate Lyapunov functions are generated by a class of non-negative functions to construct the adaptive secure bipartite consensus controllers, which not only makes certain that the bilateral errors ultimately converge to a predefined interval, but also guarantees that all the closed-loop signals within the investigated system are bounded. Conclusively, a practical example is provided to validate the effectiveness of the proposed control strategy.