Attack detection of nonlinear distributed control systems

Abstract

This paper considers a class of nonlinear distributed control systems subject to false data injection attacks, Byzantine attacks and switching attacks. The problem of attack detection is formulated as the simultaneous recovery of system states, attack vectors and system mode of a switched nonlinear system. In the proposed attack detection algorithm, the inverse system of each mode aims to estimate system states and attack vectors when the corresponding mode is input-output decoupled. A set-valued mode index map gives all modes which generate a switch-singular pair. A machine learning example is used to validate the performance of the developed algorithm.