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Fault Detection for Unmanned Marine Vehicles Under Replay Attack

Qidong Liu, Yue Long, Tieshan Li, Ju H. Park, C. L. Philip Chen

2022IEEE Transactions on Fuzzy Systems37 citationsDOI

Abstract

This article investigates the fault detection problem of unmanned marine vehicles (UMVs) under the influence caused by replay attacks. First, the dynamics of UMV are modeled by a Takagi--Sugeno (T--S) fuzzy system with an unknown membership function, which includes the nonlinear coupling of the internal state of the system, the environmental multisource disturbance as well as the potential thruster failure on UMV. Then, the possible replay attack from the sensor to the shore-based center is considered, and a switching-type attack tolerant fault detection filter is designed. Sufficient conditions are given to ensure that the filtering augmented system is stable and with stochastic finite frequency <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{-}$</tex-math></inline-formula> performances, which reflect the robustness to the disturbance and sensitivity to the fault. On this basis, through a series of mathematical processing, the linear solvable conditions for the design of fault detection filters are obtained. Finally, the effectiveness of the proposed algorithm is verified by simulations.

Topics & Concepts

Robustness (evolution)Fault detection and isolationNotationComputer scienceNonlinear systemAlgorithmMathematicsArtificial intelligenceActuatorChemistryArithmeticGeneBiochemistryQuantum mechanicsPhysicsSmart Grid Security and ResilienceNetwork Security and Intrusion DetectionFault Detection and Control Systems