Observer-based dynamic event-triggered secure control for nonlinear networked control systems with false data injection attacks

This paper considers the problem of observer-based dynamic event-triggered secure control for nonlinear networked control systems (NCSs) under false data injection attacks (FDIA). A novel output feedback controller is developed by utilizing a sampled-data observer to relieve the impacts of unmeasured states and FDIA. To make full use of the limited network resources, a dynamic periodic event-triggered mechanism (PETM) with an auxiliary variable is designed, which can reduce the transmission of information. Then, an approximation of injected false data is implemented based on an adaptive neural network (NN) in the presence of FDIA. Based on the proposed control strategy, the boundness of the nonlinear NCSs can be ensured by selecting some proper parameters. Finally, the effectiveness and validity of the proposed control strategy are illustrated via simulation of a single link robot arm system.