Kalman Filter Based Detection of FDIA on a Hybrid Nonlinear Hydro-power Plant Control System Model

Abstract

Cyber-Physical Systems (CPSs) are becoming more relevant, and ever more present in today's world. The integration of cyber/computer systems with the physical world gives improvements on various efficiency and reliability parameters, as well as convenience. Unfortunately, by their very nature CPSs come with various risks and complications that come from the integration of the cyber and physical worlds. One of these risks are cyber and physical attacks on CPSs. Research across various disciplines on these attacks is growing each passing day. In this paper we simulate the possible effects of False Data Injection Attacks (FDIAs) on a hybrid nonlinear model of a hydropower plant (HPP), and then we implement a classical control engineering method - Kalman filtering, as a detection system for these attacks. It is proven that a Kalman filter designed on a linearized continuous system model is a successful detection method in various attack scenarios on the nonlinear hybrid system model.