Robust filtering algorithm against hybrid-attacks and randomly occurring nonlinearities: Application to a quadrotor UAV

Abstract

This paper addresses the filtering problem for a class of discrete-time cyber-physical system (CPS) in simultaneous presence of physical attack, denial of service attacks (DoS), false data injection (FDI) attacks and randomly occurring nonlinearities (RONs). The malicious attacks can be simultaneously launched at the physical and cyber space to assault/disturb the system's state or block the measurement transmission channels. Firstly, the physical attack is considered as an injected unknown information, which can modify the system's state; then, a unified framework is proposed under which the phenomena of DoS attacks and FDI attacks are depicted by two independent Bernoulli distributed random variables, respectively. Furthermore, the available random probability information of the hybrid attacks and RONs are taken into account in the developed state estimation algorithm. Subsequently, by employing the stochastic analysis and matrix techniques, the exponential boundedness of the state estimation error is discussed from the theoretical aspects. As a typical CPS, a quadrotor unmanned aerial vehicle(UAV) system is provided to demonstrate the effectiveness and practicability of the proposed state estimation method.