(355a) Control System Cyberattack Resilience and Discoverability for Nonlinear Systems with Changing Dynamics
AIChE Annual Meeting
2020 Virtual AIChE Annual Meeting
AIChE Futures: New Directions in Chemical Engineering Research I (Invited Talks)
Tuesday, November 17, 2020 - 9:45am to 10:00am
Motivated by these considerations, this work elucidates properties of cyberattack discoverability for nonlinear systems, both in the presence of changing and of unchanging process dynamics. In the case of changing process dynamics, cyberattack discoverability is discussed for an approach for updating the dynamics which extends prior work in [8,9] to provide conditions under which closed-loop stability under LEMPC can be maintained when the underlying process dynamics change over time for a nonlinear process. In , the process model must be re-identified within a certain time period after the closed-loop state leaves a characterizable region of state-space which it should not leave unless the process dynamics have changed. Due to difficulties in distinguishing process dynamics changes from sensor measurement cyberattacks, we discuss methods for adjusting this model update-triggering procedure to attempt to gain greater resilience of the control system against cyberattacks on the sensors (in the sense that the attacks can be detected or if not detected, cannot cause the closed-loop state to leave a bounded region of operation for at least some time period after the attack). Three detection strategies based on probing, state prediction-based attack flagging, and state estimate-based attack flagging are evaluated for their benefits and limitations in achieving these goals. A chemical process example involving a continuous stirred tank reactor is used to illustrate the developments.
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