Cyber–physical systems subject to false data injections: A model predictive control framework for resilience operations

In this paper, the resilient control problem for constrained cyber–physical systems subject to false data injections is addressed. The core of the proposed approach consists in defining an ad-hoc versatile framework whose main feature consists in the ability of being geared to different classes of attacks. This is formally achieved by resorting to the receding horizon philosophy that is fully exploited for detection, countermeasures and control purposes. In particular, set-theoretic model predictive arguments are combined with the perturbation analysis and sequential quadratic programming to reduce as much as possible the occurrence of refresh procedures on the communication network when resilient command actions are no longer available. Further, one of its main merits consists in the dismissal of constructive assumptions existing in recent competitors. In this respect, the framework is customized for covert attacks by specifying actuation/detection phases and proving feasibility and closed-loop stability properties.