Adaptive resilient control for cyber-physical systems against unknown injection attacks in sensor networks

An adaptive resilient control is concerned for a class of cyber-physical systems (CPSs) in the presence of stealthy false data injection attacks in sensor networks and strict-feedback nonlinear dynamics. As the sensors are attacked by ill-disposed hackers, the exactly measured state information is unavailable for state feedback control. After theory ratiocinations, the initial issue of false data injection attacks is transformed into nonlinear uncertainty dynamics and unknown control directions at the last step. At each step in the recursive backstepping control, extended state observers (ESOs) in active disturbance rejection control (ADRC) are investigated to approximate the lumped system uncertainties. Specially, the Nussbaum functions are introduced at the last step in the adaptive control. All the closed-loop signals are proved to be semi-globally uniformly ultimately bounded by Lyapunov theory. Finally, numerical simulations verify that the proposed control can afford favorable stabilization performance and counter false data injection attack.