Event‐triggered fault detection for discrete‐time LPV systems with application to a laboratory tank system

Golabi, Arash; Davoodi, Mohammadreza; Meskin, Nader; Mohammadpour, Javad

doi:10.1002/acs.2932

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…The scheduling variables 𝜃 1 (t) and 𝜃 2 (t) are in [0.1826, 3.162] and [0.1826, 3.162], by assuming the tank level change between 10 and 30 cm. With sampling period of T s = 0.05 s, The discretized LPV model of ( 33) is presented in (34).…”

Section: Parameter Value Unitmentioning

confidence: 99%

“…A wide range of performance measurements has been taken into account for detecting anomalies in CPS. The performance measurements of

{H}_{-}/{H}_{\infty }

have been studied in References 33 and 34 for fault detection filter design problem in LPV systems. The paper 35 discusses the detection attacks problem on distributed estimator networks that ensure the detection of distributed input attacks utilizing an

{H}_{\infty }

method.…”

Section: Introductionmentioning

confidence: 99%

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Detecting deception attacks in cyber‐physical linear parameter varying systems with packet loss

Golabi

Erradi

Tantawy

et al. 2022

Adaptive Control & Signal

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The increased connectivity of cyber-physical systems (CPS) to enterprise networks raises challenging security concerns. Detecting attacks on CPS is a vital step to improving their security. Most of the existing attack detectors are for CPS with linear dynamics. In this study, an investigation is made for designing a detector of deception attacks in a cyber-physical linear parameter varying (LPV) system in the presence of packet loss. A model-based attack detector is designed to detect deception attacks on output measurements, actuators, or schedule variables. With an unreliable network, the LPV attack detector enhances detection capacity and attenuates disturbances on the detector module to improve detection accuracy. During communication, packet loss results in network unreliability, which is modeled by the Bernoulli process. Stochastic stability is used to determine LPV attack detector parameters. A residual signal is built by comparing the detector's output and the actual sensor measurement and provides the deception attack's essential data. However, the packet loss causes some impulse signals in the residual signal, resulting in false alarms. Therefore, the detector module is equipped with a median filter to suppress packet loss's effect on evaluating the residual signal. Tests and validations of the proposed approach are performed on a two-tank system and a continuous stirred tank reactor.According to evaluation results conducted on two testbeds, the proposed method accurately detects deception attacks even when there is packet loss.

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Section: Parameter Value Unitmentioning

confidence: 99%

“…A wide range of performance measurements has been taken into account for detecting anomalies in CPS. The performance measurements of

{H}_{-}/{H}_{\infty }

{H}_{\infty }

method.…”

Section: Introductionmentioning

confidence: 99%

Detecting deception attacks in cyber‐physical linear parameter varying systems with packet loss

Golabi

Erradi

Tantawy

et al. 2022

Adaptive Control & Signal

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several event-triggered mechanisms with extended Lyapunov-based triggered conditions in the continuous and discrete-time domains are designed for different applications. Periodic and discrete-time ETMs are proposed (see [5,7,9,10]) to avoid continuous monitoring. It is also noted that the update instants of the control input should not be very close to avoid the Zeno effect.…”

Section: Introductionmentioning

confidence: 99%

Input‐based event‐triggered control of a discrete‐time singularly perturbed system under a resource constrained environment

Sahu

Bhandari

Fulwani

2023

Asian Journal of Control

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This paper proposes an input‐based event‐triggered mechanism for a network‐controlled discrete‐time singularly perturbed system, where the latest measurements are transmitted when a predefined condition is satisfied on the input. The significant contribution of the proposed work is the separation of control updates for slow and fast dynamics such that the proposed event‐triggered mechanism updates and broadcasts the current measurements of slow and fast dynamics in their respective time scales and reduces the usage of network resources. Further, the proposed input‐based event‐triggered mechanism avoids redundant updates of the control input and reduces actuation and resource utilization in some instances. Furthermore, the ultimate boundedness of the system states is established. The simulation uses a quarter‐car suspension system to demonstrate the proposed theory.

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“…For instance, Ren et al designed an event‐triggered nonfragile

H_{\infty}

FDF for time‐delay systems with channel attenuation 24 . Golabi et al investigated an event‐triggered FD method for discrete‐time LPV systems 25 . Compared with the traditional periodic time‐triggered scheme, the event‐triggered scheme implements control operation merely when the current information meets the predefined triggering condition.…”

Section: Introductionmentioning

confidence: 99%

Adaptive event‐triggered fault detection for nonlinear networked systems in finite‐frequency domain under stochastic cyber‐attacks

Zhu

Jiang

Pan

2022

Adaptive Control & Signal

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This article investigates the fault detection problem in finite-frequency domain for a class of nonlinear networked systems under stochastic cyber-attacks.A novel adaptive event-triggered scheme is introduced to mitigate the transmission burden of the network. A unified measurement model is proposed to take the randomly occurring cyber-attacks and the transmission delays into account simultaneously. Under the consideration of fault sensitivity and disturbance robustness, the addressed fault detection problem is converted into an auxiliary H − ∕H ∞ filtering problem by properly augmenting the states of the original system and the fault detection filter. Intensive stochastic analysis is carried out to obtain sufficient conditions for the existence of the desired fault detection filter, and the corresponding optimal filter parameters can be easily derived by solving a convex optimization problem. Finally, an illustrative example is presented to show the effectiveness and applicability of the proposed method.

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Event‐triggered fault detection for discrete‐time LPV systems with application to a laboratory tank system

Cited by 10 publications

References 36 publications

Detecting deception attacks in cyber‐physical linear parameter varying systems with packet loss

Detecting deception attacks in cyber‐physical linear parameter varying systems with packet loss

Input‐based event‐triggered control of a discrete‐time singularly perturbed system under a resource constrained environment

Adaptive event‐triggered fault detection for nonlinear networked systems in finite‐frequency domain under stochastic cyber‐attacks

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