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Cyber-attack Detection and Resilient Operation of Nonlinear Processes under Economic Model Predictive Control
Computers & Chemical Engineering ( IF 3.9 ) Pub Date : 2020-03-14 , DOI: 10.1016/j.compchemeng.2020.106806
Scarlett Chen , Zhe Wu , Panagiotis D. Christofides

This work proposes resilient operation strategies for nonlinear processes that are vulnerable to targeted cyber-attacks, as well as detection and handling of standard types of cyber-attacks. Working with 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 to optimize economic benefits in a time-varying manner while maintaining closed-loop process stability. Although sensor measurements may be vulnerable to cyber-attacks, the proposed controller design and operation strategy ensure that the process will maintain stability and stay resilient against particular types of destabilizing cyber-attacks. Data-based cyber-attack detectors are developed using sensor data via machine-learning methods, and these detectors are periodically activated and applied online in the context of process operation. Using a continuously stirred tank reactor example, simulation results demonstrate the effectiveness of the resilient control strategy in maintaining stable and economically optimal operation in the presence of cyber-attacks. The detection results produced by the detection algorithm demonstrate the capability of the proposed method in identifying the presence of a cyber-attack, as well as in differentiating between different types of cyber-attacks. Upon successful detection of the cyber-attacks, the impact of cyber-attacks can be mitigated by replacing the attacked sensors by secure back-up sensors, and secure operation will resume with the process operated under the proposed resilient LEMPC control strategy.



中文翻译:

经济模型预测控制下的非线性过程网络攻击检测与弹性运行

这项工作提出了针对非线性过程的弹性操作策略,这些非线性过程容易受到有针对性的网络攻击以及检测和处理标准类型的网络攻击。与一般的非线性系统一起使用时,提出了一种基于Lyapunov的改进型经济模型预测控制器(LEMPC),该模型使用闭环和开环控制动作组合实施方案,可在保持闭环状态的同时以时变方式优化经济效益。循环过程的稳定性。尽管传感器的测量可能容易受到网络攻击的影响,但建议的控制器设计和操作策略可确保该过程将保持稳定性并针对特定类型的不稳定网络攻击保持弹性。基于数据的网络攻击检测器是通过机器学习方法使用传感器数据开发的,这些检测器会在过程操作中定期激活并在线应用。以一个连续搅拌釜反应器为例,仿真结果证明了在存在网络攻击的情况下,弹性控制策略在维持稳定且经济上最佳运行方面的有效性。检测算法产生的检测结果证明了该方法在识别网络攻击的存在以及区分不同类型的网络攻击方面的能力。成功检测到网络攻击后,可以通过用安全后备传感器替换受攻击的传感器来减轻网络攻击的影响,并且在建议的弹性LEMPC控制策略下运行的过程将恢复安全操作。

更新日期:2020-03-16
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