Sampled-data-driven event-triggered secure control of uncertain nonlinear cyber-physical systems against multiple attacks

In this paper, the sampled-data-driven event-triggered secure control is discussed for a class of uncertain nonlinear cyber-physical systems under multiple attacks containing deception attacks and replay attacks. Compared with exisiting research, the studied systems take into account the uncertainty and coupling that may occur in practical situations. Notably, deception attacks impede the application of a gain design approach in control design. To address this issue, an artful state transformation is presented to convert the considered system into an auxiliary system. Based on this, a novel sampled-data-driven attack compensation scheme is devised via the gain design approach, and an event-triggered mechanism is further introduced into the scheme to cancel needless control updates, which successfully ensures state convergence meanwhile resisting the impact of multiple attacks. Particularly, the designed control scheme not only utilizes data efficiently but also avoids Zeno behaviour automatically by judging triggering conditions in sampled points. Finally, the validity of the results is verified through two simulation examples.