Journal
CHEMICAL ENGINEERING RESEARCH & DESIGN
Volume 170, Issue -, Pages 147-179Publisher
ELSEVIER
DOI: 10.1016/j.cherd.2021.03.024
Keywords
Control system cybersecurity; Model predictive control; Data-driven models
Categories
Funding
- Air Force Office of Scientific Research [FA95501910059]
- National Science Foundation [CNS1932026, CBET1839675]
- Wayne State University
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The paper discusses the challenges of developing control strategies in safety-critical processes facing uncertainty, and introduces cyberattack detection strategies for nonlinear processes, as well as the concept of Taylor series-based models.
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 in the presence of control system cyber-attacks. One of the challenges for developing control strategies with guaranteed safety and cybersecurity properties under sufficient conditions is the development of appropri-ate detection strategies that work with control laws to prevent undetected attacks that have immediate closed-loop stability consequences. Achieving this, in the presence of uncer-tainty brought about by plant/model mismatch and process dynamics that can change with time, requires a fundamental understanding of the characteristics of attacks that can be detected with reasonable detection mechanisms and characterizing and verifying system safety properties when cyberattacks and changing system behavior cannot be distinguished. Motivated by this, this paper discusses three cyberattack detection strategies for nonlinear processes whose dynamics change with time when these processes are operated under an optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC) until the closed-loop state either leaves a characterizable region of state-space or an attack detection threshold related to state estimates or state predictions is exceeded. Following this, the closed-loop state is maintained within a larger region of oper-ation under an updated cyberattack detection strategy for a characterizable time period. A Taylor series-based model is used for making state predictions to allow theoretical guar-antees to be explicitly tied to the numerical approximation of the model used within the LEMPC. A process example illustrates the Taylor series-based model concept. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
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