Integrated cyberattack detection and resilient control strategies using Lyapunov-based economic model predictive control

The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov-based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when a threshold on the difference between state measurements and state predictions is exceeded. Finally, the third strategy utilizes redundant state estimators to flag deviations from normal process behavior as cyberattacks.