Integrated cyberattack detection and handling for nonlinear systems with evolving process dynamics under Lyapunov-based economic model predictive control

Safety-critical processes are becoming increasingly automated and connected. While automation can increase efficiency, it brings new challenges associated with guaranteeing safety in the presence of uncertainty especially control system cyberattacks. One for developing strategies guaranteed cybersecurity properties under sufficient conditions is development appropriate detection that work laws to prevent undetected attacks have immediate closed-loop stability consequences. Achieving this, brought about by plant/model mismatch process dynamics change time, requires a fundamental understanding characteristics be detected reasonable mechanisms characterizing verifying when cyberattacks changing behavior cannot distinguished. Motivated this paper discusses three cyberattack nonlinear whose time these operated an optimization-based strategy known as Lyapunov-based economic model predictive (LEMPC) until state either leaves characterizable region state-space or attack threshold related estimates predictions exceeded. Following maintained within larger operation updated period. A Taylor series-based used making allow theoretical guarantees explicitly tied numerical approximation LEMPC. example illustrates concept.