ANZCC 2019 Paper Abstract


Paper TA1.5

Chamanbaz, Mohammadreza (Singapore University of Technology and Design), Dabbene, Fabrizio (Politecnico di Torino), Bouffanais, Roland (Singapore University of Technology and Design)

A Physics-Based Attack Detection Technique in Cyber-Physical Systems: A Model Predictive Control Co-Design Approach

Scheduled for presentation during the Regular Session "Complex and Nonlinear Systems" (TA1), Thursday, November 28, 2019, 11:15−11:30, WZ Building Room WZ416

2019 Australian & New Zealand Control Conference (ANZCC), November 27-29, 2019, Auckland, New Zealand

This information is tentative and subject to change. Compiled on September 25, 2020

Keywords Model Predictive Control, Sensor Networks and Networked Control, Nonlinear Systems and Control


In this paper a novel approach to co-design controller and attack detector for nonlinear cyber-physical systems affected by false data injection (FDI) attack is proposed. We augment model predictive controller with an additional constraint requiring the future---in some steps ahead---trajectory of the system to remain in some time-invariant neighborhood of a properly designed reference trajectory. At any sampling time, we compare the real-time trajectory of the system with the designed reference trajectory, and construct a residual. The residual is then used in a nonparametric cumulative sum (CUSUM) anomaly detector to uncover FDI attacks on input and measurement channels. The effectiveness of the proposed approach is tested with a nonlinear model regarding level control of coupled tanks.



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