Mitigating Cyberattack Impacts Using Lyapunov-Based Economic Model Predictive Control

One of the pressing concerns for next-generation manufacturing is the development of techniques for guaranteeing that a control system is cyberattack-resilient in the sense that even if a cyberattack is successful at breaking information technology-based defenses (e.g., it succeeds at providing a false sensor measurement to the controller), closed-loop stability is still maintained. Our prior work has provided a nonlinear systems definition for cyberattacks. This work explores how a nonlinear systems perspective on cyberattack-resilience for false sensor measurements provided to controllers may allow an economic model predictive control (EMPC) formulation known as Lyapunov-based EMPC (LEMPC) to be designed such that if a cyberattack occurs at a sampling time, the closed-loop state will not leave a region where a known feedback control law exists that can stabilize the origin of the closed-loop system if the cyberattack is detected and non-falsified state measurements are then provided within that sampling period.