Fault Detection Filter Research Articles

Improved event-based fault detection filter for networked fuzzy systems under DoS attacks

This paper investigates an improved event-based fault detection method for networked fuzzy systems under denial-of-service (DoS) attacks. In order to solve the bandwidth occupation problem of communication network, a resilient event-triggered transmission strategy is developed. Additionally, a fault detection filter is designed to estimate the time of fault occurrence by using the residual signal. Under this framework, a novel Lyapunov functional related to attack parameters is established to analyze the exponential convergence of the error signals, and the filter gains and event-triggered parameters are obtained by solving linear matrix inequalities. The designed functional reduces the conservatism of the stability criteria significantly in contrast with the previous discontinuous Lyapunov functionals. Finally, a simulation example is provided to verify the effectiveness of the proposed method.

A randomized algorithm based approach to fault detection for uncertain systems subject to deception attack

This paper presents a fault detection strategy for discrete uncertain systems subject to deception attack based on the probabilistic framework. Probabilistic parameter models are utilized for characterizing model uncertainties, multiplicative faults and additive faults. An observer-based fault detection filter is constructed to generate fault information under deception attack. A randomized algorithm based approach is developed to determine the observer gain and threshold for attaining a trade-off between the false alarm rate (FAR) and fault detection rate (FDR). Simulation of an unmanned surface vehicle (USV) system and comparison against existing work are performed to illustrate the effectiveness of the proposed scheme.

Fault detection for saturated nonlinear system subject to redundant channel and additive time‐varying delays

AbstractUnder the influence of sensor saturation and packet dropout, this paper is concerned with the fault detection (FD) problem for a class of nonlinear systems with two additive time‐varying delay components. In the addressed measurement model, the sensor is assumed to have two communication channels, which can contribute to improving the probability of successfully delivering the measurements. A FD filter is designed to generate residual signals, and the sufficient criteria are established to ensure the stochastic finite‐time stability (SFTS) of the residual system with performance constraint by constructing new Lyapunov‐Krasovskii functionals. Based on the established criteria, the explicit expression of the desired FD filter is obtained via solving a set of linear matrix inequalities (LMIs). Finally, the usefulness of the proposed FD scheme is verified by a simulation example.

Explicit Formulas for the Equivalence Between Fault Detection Filters and Observers

Explicit Formulas for the Equivalence Between Fault Detection Filters and Observers

Resilient Event-Based Fuzzy Fault Detection for DC Microgrids in Finite-Frequency Domain against DoS Attacks.

This paper addresses the problem of fault detection in DC microgrids in the presence of denial-of-service (DoS) attacks. To deal with the nonlinear term in DC microgrids, a Takagi-Sugeno (T-S) model is employed. In contrast to the conventional approach of utilizing current sampling data in the traditional event-triggered mechanism (ETM), a novel integrated ETM employs historical information from measured data. This innovative strategy mitigates the generation of additional triggering packets resulting from random perturbations, thus reducing redundant transmission data. Under the assumption of faults occurring within a finite-frequency domain, a resilient event-based H-/H∞ fault detection filter (FDF) is designed to withstand DoS attacks. The exponential stability conditions are derived in the form of linear matrix inequalities to ensure the performance of fault detected systems. Finally, the simulation results are presented, demonstrating that the designed FDF effectively detects finite-frequency faults in time even under DoS attacks. Furthermore, the FDF exhibits superior fault detection sensitivity compared to the conventional H∞ method, thus confirming the efficacy of the proposed approach. Additionally, it is observed that a trade-off exists between fault detection performance and the data releasing rate (DRR).

Parameterization to fault detection filtering for Itô stochastic T‐S fuzzy systems

AbstractThis article focuses on the fault detection filtering problem for Itô stochastic Takagi–Sugeno (T‐S) fuzzy systems. In terms of line integral Lyapunov function, a sufficient condition of exponential stability in mean square and extended dissipativity for the systems under consideration is established which has less conservatism than the one based on quadratic Lyapunov function. The obtained sufficient condition is nonlinear, which makes the synthesis of fault detection filter being difficult and challenging. By choosing general matrix variables and constructing the appropriate orthogonal complement matrices, the nonlinear sufficient condition can be converted into linear one ingeniously via utilizing Finsler's lemma twice. Thus, the fault detection filter can be developed by virtue of parameterization. It should be pointed out that our filter determined by the parameterization approach includes the one obtained by the equivalent transformation method as a special case. Finally, we demonstrate the feasibility and superiority of our proposed approach through three numerical examples.

Attack-resilient fault detection for interconnected systems under DoS attack

In light of the expanding cyber-space applications, the imperative consideration of cyber-attack ramifications on system security is evident. This paper presents a resilient dynamic event-triggered fault detection scheme for a class of nonlinear interconnected systems subjected to denial of service (DoS) attacks. To counteract multifaceted threats, the co-design challenge involving switched-type fault detection filters and a resilient dynamic event-triggered transmission mechanism is addressed. In the design phase of the filters, the frequency information of the signal is considered comprehensively and linear solvable conditions ensuring desired augment system performance are delineated. Through a series of comparative simulation experiments, the findings support the conclusion that the proposed attack-tolerant fault detection mechanism not only conserves network resources but also demonstrates superior detection capabilities for specific frequency fault signals.

Improved asynchronous fault detection filter design for singular fuzzy Markovian jump systems against multi-cyber-attacks

This paper delves into the design of an asynchronous Fault Detection Filter (FDF) for Singular Fuzzy Markovian Jump Systems (SFMJSs), particularly under the influence of multi-cyber-attacks, leveraging an enhanced adaptive event-triggered mechanism (AETM). Initially, a Hidden Markovian Model (HMM) is employed to characterize the asynchronous interactions between SFMJSs and FDF. Subsequently, a mode-dependent AETM alongside a dynamic quantization protocol is synergistically utilized to optimize communication bandwidth and augment data transmission efficiency. Additionally, the study introduces an expansive range of multi-cyber-attacks, encompassing deception, replay, and Denial-of-Service (DoS) attacks, to mirror inherent vulnerabilities in wireless signal transmission. Furthermore, the H∞ performance of the FDF error system is assessed within a comprehensive framework using Linear Matrix Inequalities (LMIs), guided by a generalized performance index. This research establishes innovative admissibility criteria and filter conditions, aimed at guaranteeing the feasibility of desired FDF gains and ensuring the exponential admissibility of the FDF error system, underpinned by a generalized performance index. This manuscript concludes with two illustrative examples to demonstrate the efficacy of the proposed methodologies.

Adaptive event-triggered fault detection filter for unmanned surface vehicles against randomly occurring injection attacks

This paper focuses on the problem of event-triggered fault detection for network-based unmanned surface vehicles (USVs) subject to network-induced delay, external disturbance, and cyber attacks. First, a novel adaptive event-triggered strategy is presented to relieve the bandwidth burden of the communication network while mitigating the impact of cyber attacks on the USV performance. Second, the network-induced communication delay is characterized as a distributed delay with a probability density function as its kernel. Third, to identify the time when the fault occurs, a fault detection filter (FDF) is designed to obtain a residual system. Based on the established framework, criteria for asymptotic stability analysis are derived via the Lyapunov–Krasovskii functional approach, and then the co-design of FDF and the event-triggered parameter matrix is given by the matrix transformation technique. Finally, simulation results are provided to substantiate the feasibility of the proposed approach.

A bumpless transfer piecewise filtering approach for fault detection of switched linear systems

AbstractThis study focuses on bumpless transfer (BT) fault detection in switched linear systems operating under mode‐dependent average dwell time (MDADT) switching. We propose a piecewise fault detection filter (FDF) inspired by the segmentation concept inherent in the multiple discontinuous Lyapunov function (MDLF) approach. This filter generates a residual signal that effectively minimizes the amplitude of residual bumps, surpassing the performance of traditional non‐piecewise FDFs. We introduce a new definition of residual BT performance, aimed at reducing residual bump amplitude during filter transitions. The goal is to design the piecewise FDF such that the augmented system maintains asymptotic stability with weighted performance, while also meeting the residual BT performance criteria. The feasibility of achieving BT fault detection filtering is established through linear matrix inequalities (LMIs), leveraging the MDLF and MDADT strategies. The efficacy and benefits of the proposed BT piecewise FDF design are demonstrated through simulations on a boost converter.

Integrated fault detection filter and fault-tolerant control for the unmanned surface vehicle with deception attacks

This article investigates the fault detection and fault-tolerant control problem for an unmanned surface vehicle exposed to wave-induced disturbances and actuator faults in the physical layer, and delays and deception attacks in the cyber layer. First, a comprehensive vehicle model that includes physical disturbances, faults, time-varying delays, and Bernoulli random variable–based deception attacks is established. Second, an integrated fault detection filter and fault-tolerant controller design are developed to simultaneously provide a high degree of sensitivity to actuator faults and robustness and stability against cyber-physical threats (disturbances, faults, delays, and attacks). Delays and deception attacks are assumed to occur on the channel from fault detection filter to fault-tolerant controller. Finally, the performance and advantages of the integrated fault detection filter and fault-tolerant controller method with the solvability of inequality matrices are evaluated via comparative simulations in the unmanned surface vehicle with both low and high forward speeds.

Adaptive event‐triggered fault detection for Markov jump nonlinear systems with time delays and uncertain parameters

AbstractThis article proposes a fault detection (FD) method for a class of Markov jump nonlinear systems with time delays and uncertain parameters. The FD problem is transformed into a filtering question by designing a FD filter that satisfies appropriate performance index. An adaptive event‐triggered mechanism is introduced to conserve network resources, and the impact of time‐varying and network‐induced delay on the system is fully considered. Then, stochastical stability and appropriated performance index of the residual system are guaranteed using the Lyapunov–Krasovskii functional theory, discrete Wirtinger inequality and extended reciprocally convex matrix inequality. Finally, a simulation example verifies the feasibility and effectiveness of the designed FD filter.

Asynchronous Fault Detection for Memristive Neural Networks With Dwell-Time-Based Communication Protocol.

This article studies the asynchronous fault detection filter problem for discrete-time memristive neural networks with a stochastic communication protocol (SCP) and denial-of-service attacks. Aiming at alleviating the occurrence of network-induced phenomena, a dwell-time-based SCP is scheduled to coordinate the packet transmission between sensors and filter, whose deterministic switching signal arranges the proper feedback switching information among the homogeneous Markov processes (HMPs) for different scenarios. A variable obeying the Bernoulli distribution is proposed to characterize the randomly occurring denial-of-service attacks, in which the attack rate is uncertain. More specifically, both dwell-time-based SCP and denial-of-service attacks are modeled by means of compensation strategy. In light of the mode mismatches between data transmission and filter, a hidden Markov model (HMM) is adopted to describe the asynchronous fault detection filter. Consequently, sufficient conditions of stochastic stability of memristive neural networks are devised with the assistance of Lyapunov theory. In the end, a numerical example is applied to show the effectiveness of the theoretical method.

Distributed adaptive event-triggered fault detection filter of positive semi-Markovian jump systems

This paper presents a distributed fault detection filter (FDF) for positive semi-Markovian jump systems (PSMJSs) based on an adaptive event-triggered mechanism (AETM) scheme. A novel AETM is first proposed for the systems. A weighted fault model is introduced to assist the estimation of the original fault. Utilizing stochastic copositive Lyapunov function (CLF), a distributed FDF whose parameters are designed by virtue of linear programming (LP), is proposed. Under the designed filter, the positivity and stochastic stability with L1/L_-gain performance of a fault detection system is reached. The contribution of this paper contains three aspects: (i) An AETM is constructed for the considered systems, (ii) A distributed FDF is designed for the systems, and (iii) The hybrid L1/L_-gain performance is achieved with respect to the disturbance and the fault. Two illustrative examples are given for verifying the validity of the results.

Dissipative fault detection for time‐delay nonlinear Markov jump systems with measurement outliers under stochastic communication protocol

SummaryThis article investigates the dissipative fault detection (FD) problem for time‐delay nonlinear Markov jump systems with measurement outliers in the case of partially unknown transition probabilities. The stochastic communication protocol is utilized to save network bandwidth, where the scheduling model is described via a Markov chain. An outlier‐resistant FD filter is constructed with the help of adaptive saturation function technology. The sufficient conditions are derived to ensure that the FD system satisfies the stochastic stability and stochastic strict dissipativity. In addition, an FD filter without saturation constraint is also designed to compare with the outlier‐resistant FD filter, which verifies that the outlier‐resistant FD filter weakens the influence of measurement outliers effectively. Finally, two examples are provided to demonstrate the feasibility and effectiveness of the designed FD scheme.

Adaptive memory event-triggered double asynchronous fault detection and security control for fuzzy semi-Markov jump systems under cyberattacks

This paper studies the issue of event-triggered fault detection and security control for fuzzy semi-Markov jump systems (FSMJSs) under deception attacks. In particular, a novel adaptive memory event-triggered mechanism (AMETM) that avoids Zeno behavior is considered to improve the transmission efficiency. Meanwhile, the designed adaptive memory triggering condition includes current and historical triggered data. Furthermore, for the sake of realizing the objective of detecting system fault and implementing safety control simultaneously, a double asynchronous mixed fault detection and security control (MFDASC) module is proposed. The module integrated by the fault detection filter and the dynamic output feedback controller can deal with the mismatch of the premise variables and the modes between the system and the corresponding module. Then, the sufficient conditions for strict fault detect and security control dissipation of closed-loop systems are obtained by utilizing integral inequalities. Ultimately, the validity of the designed method is demonstrated by a tunnel diode circuit example.

Adaptive event-triggered based fault detection filtering for unmanned surface vehicles under DoS attacks

This paper proposes an adaptive event-triggered fault detection filter to warn of faults happening to unmanned surface vehicles in a network. First, the unmanned surface vehicle is modeled as a Markovian jump system which makes allowances for the influences of waves or other disturbances. Then, a fault detection filter is developed to produce crucial residual signals, despite disturbances and denial-of-service attacks. Inputs of the designed filter originate from a resilient adaptive event-triggered mechanism, of which the threshold can be adjusted for saving valuable network resources and mitigating adverse influences of denial-of-service attacks. By using the residual signals, detection evaluation functions are established and a detection logic algorithm is devised. Under this framework, the co-design of both the fault detection filter and the adaptive event-triggered scheme is given. Finally, the proposed method is proved to be applicable by simulating a real unmanned surface vehicle model.

Event‐triggered fault detection filter design for networked switched systems with all subsystems unstable and cyber attacks

SummaryThis article focuses on the issue of event‐triggered fault detection filters (FDF) design for networked switched systems. Compared with the existing fault detection literature, this article investigates the situation that all subsystems are unstable, and considers that stochastic cyber attacks will disrupt fault detection. An event‐triggered mechanism (ETM) that excludes Zeno behavior naturally is designed to economize limited network resources. Then considering the ETM‐induced delay term, the dynamics of the initial system combined with the ETM, fault detection filters, and the effects of cyber attacks are formulated as a new augment switched delayed residual model. Based on the constructed multiple piecewise discretized Lyapunov–Krasovskii function (MPDLKF) and the mode‐dependent dwell time (MDDT) method, sufficient conditions are obtained to guarantee globally mean‐square uniformly asymptotically stability of the new augment system. Moreover, a co‐design method of ETM matrices and FDF gains is proposed. Finally, simulation results are provided to verify the feasibility and effectiveness of the proposed method.

Asynchronously switched fault detection filter design for full-envelope flight vehicle

The fault detection problem of a class of full-envelope flight vehicles with time delays and packet losses is investigated. Their model is established as locally overlapped switched systems to reduce conservatism. The delays and the packet losses are transformed into the parameters of polytopic systems. The switched parameter-dependent fault detection filter (FDF) is then designed. The fault detection system stability and its [Formula: see text] performance under asynchronous switching with average dwell time are analyzed. Moreover, a parity-space–based optimization approach is presented to guarantee that the modified residual signal is sensitive to fault but robust to disturbance. An example of applying this method to the highly maneuverable technology vehicle is given to verify the method’s effectiveness.

Co-Design of Adaptive Event Generator and Asynchronous Fault Detection Filter for Markov Jump Systems via Genetic Algorithm.

This article investigates the co-design problem of adaptive event-triggered schemes (AETSs) and asynchronous fault detection filter (AFDF) for nonhomogeneous higher-level Markov jump systems, involving the hidden Markov model (HMM), higher-level Markov chain (MC), and conic-type nonlinearities. The transformation of the system transition probability can be reflected by the designed higher-level MC. An HMM with another conditional transition probability is applied to detect higher-level Markov processes and make the system be more practical. In order to balance the utilization of network resources and system performance, a novel AETS is proposed and used in the construction of the AFDF. By the Lyapunov theory, sufficient conditions are given to ensure the existences of the AETS and AFDF. It is not only an appropriate tradeoff between the utilization of network resources and system performance, but also reduces the conservatism. Finally, a numerical example is given to detect the faults effectively by the co-designed AFDF.