Detection of Cyber-Attacks and Resilient Operation of Nonlinear Processes Under Economic Model Predictive Control
- Type: Conference Presentation
- Conference Type: AIChE Annual Meeting
- Presentation Date: November 16, 2020
- Duration: 14 minutes
- Skill Level: Intermediate
- PDHs: 0.20
This work presents a resilient operating scheme for nonlinear processes subject to standard types of cyber-attacks, and proposes detection and handling strategies of these cyber-attacks. In particular, considering a general class of nonlinear systems, a modified Lyapunov-based Economic Model Predictive Controller (LEMPC) using combined closed-loop and open-loop control action implementation schemes is proposed with the control objective of optimizing economic benefits while maintaining closed-loop process stability. Process stability and resiliency against particular types of targeted destabilizing attacks will be ensured under the proposed controller modification and operation strategy. Moreover, machine-learning methods are used to develop sensor-data-based cyber-attack detectors, which are periodically activated online during process operation. Simulation results based on a continuously stirred tank reactor example demonstrate the effectiveness of the resilient LEMPC control strategy in the presence of various cyber-attacks, as well as the capability of the detection algorithm in reporting and differentiating the different types of cyber-attacks.
 Cárdenas, A., Amin, S., Lin, Z., Huang, Y., Huang, C., Sastry, S., 2011. Attacks against process control systems: risk assessment, detection, and response, in: Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security, pp. 355â366.
 Chen, S., Wu, Z., Christofides, P.D., 2020. A cyber-secure control-detector architecture for nonlinear processes. AIChE Journal 66, e16907.
 Durand, H., 2018. A nonlinear systems framework for cyberattack prevention for chemical process control systems. Mathematics 6, 169.
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