Event-triggered Fault Detection Filter Research Articles

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.

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.

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.

Protocol-based fault detection for discrete-time memristive neural networks with quantization effect

This paper is concerned with the event-triggered fault detection filter design problem for discrete-time memristive neural networks with measurement quantization. Aiming at saving communication bandwidth and improving communication efficiency, a new component-based adjusted dynamic event-triggered protocol is proposed. The transmission status of each measurement component can be determined based on the individual prescribed triggering condition. The quantizer with variable density is introduced to meet different performance requirements, in which the quantization densities vary among a finite set of modes. By constructing an augmented Lyapunov functional, an asynchronous filter is designed to achieve the desired performance while assuring the stochastic stability of the filtering error system. Finally, a simulation example is provided to verify the effectiveness of obtained theoretical results.

Retraction: State estimation of Takagi‐Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks

International Journal of Adaptive Control and Signal ProcessingVolume 36, Issue 8 p. 2150-2150 RETRACTION STATEMENTFree Access Retraction: State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks This article retracts the following: Retracted: State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks Muhammad Shamrooz Aslam, Volume 35Issue 7International Journal of Adaptive Control and Signal Processing pages: 1336-1353 First Published online: June 22, 2021 First published: 13 July 2022 https://doi.org/10.1002/acs.3469AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat The above article from the International Journal of Adaptive Control and Signal Processing, published online on June 22, 2021 in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor in Chief, Professor Mike Grimble, and John Wiley and Sons Ltd. The retraction has been agreed due to unattributed overlap between this article and the following article submitted to IEEE Transactions on Fuzzy Systems: “Event-triggered fault detection filter design for networked switched T-S fuzzy systems with deception attacks and data disorders (TFS-2019-1136)”. Authors: Qi, Yiwen; Yuan, Shuo; Zhao, Xudong. Submitted Nov 2019. REFERENCE 1Aslam, MS. State estimation of Takagi-Sugeno fuzzy system in networked control system with stochastic time delays under unknown attacks. Int J Adapt Control Signal Process 2021; 35: 1336– 1353. https://doi.org/10.1002/acs.3241 Volume36, Issue8August 2022Pages 2150-2150 ReferencesRelatedInformation

Dynamic event-triggered fault detection filter design for dynamical systems under fading channels

This article investigates the dynamic event-triggered fault detection filter (FDF) design problem for linear continuous-time networked systems, considering the fading channels phenomenon and randomly occurring faults. A dynamic event-triggered mechanism (ETM) is introduced to reduce the network bandwidth occupation more efficiently by utilizing an internal variable which can enlarge the event-triggered intervals. Besides, the Zeno phenomenon is eliminated fundamentally by ensuring that the event-triggered intervals are positive lower bounded. After that, sufficient conditions are derived to guarantee the stochastic stability of the residual system with a desired [Formula: see text] performance and the co-design criterion of the FDF and the dynamic ETM is developed. Finally, an unmanned surface vehicle (USV) system is used to illustrate the applicability of the presented approach.

An H i/H ∞ optimisation approach to distributed event-triggered fault detection over wireless sensor networks

ABSTRACT This paper is concerned with the problem of distributed event-triggered fault detection (FD) for linear discrete time-varying systems over resource-constrained wireless sensor networks. To reduce unnecessary communication frequency of sensor measurements and thus communication resource expenditure, an event-triggered communication mechanism is employed to determine whether or not each sensor's measurement should be broadcast to the distributed fault detection filter (FDF) over the wireless network at each time step. Then, an optimisation approach is proposed to achieve distributed event-triggered fault detection for the concerned system. Specifically, a set of distributed event-triggered FDFs is constructed based on the event-triggered measurement information from each sensor node and its adjacent nodes. Different from the existing distributed event-triggered FD schemes, the major contributions of this paper are twofold. First, the proposed FDF for each sensor node can be designed individually and the residual signal on each node is completely decoupled from the event-triggered transmission error. Second, the design of distributed event-triggered FDFs is formulated as an optimisation problem and an optimal solution can be obtained by recursively computing some Riccati recursions. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

Event-Triggered Fault Detection Filter Design for Discrete-Time Memristive Neural Networks With Time Delays.

In this article, the fault detection (FD) filter design problem is addressed for discrete-time memristive neural networks with time delays. When constructing the system model, an event-triggered communication mechanism is investigated to reduce the communication burden and a fault weighting matrix function is adopted to improve the accuracy of the FD filter. Then, based on the Lyapunov functional theory, an augmented Lyapunov functional is constructed. By utilizing the summation inequality approach and the improved reciprocally convex combination method, an FD filter that guarantees the asymptotic stability and the prescribed H∞ performance level of the residual system is designed. Finally, numerical simulations are provided to illustrate the effectiveness of the presented results.

Integral-Based Event-Triggered Fault Detection Filter Design for Unmanned Surface Vehicles

This paper is concerned with the event-triggered fault detection filter (FDF) design for an unmanned surface vehicle (USV) under the network environment. A framework of fault detection is established for a USV subject to wave-induced disturbance and actuator failures, in which an FDF is utilized to construct a residual model and an integral-based event generator is introduced to save communication resources. Compared with the traditional instantaneous value based event-triggering scheme and periodic sampling, the proposed event-triggering mechanism can not only reduce bandwidth utilization of the network more significantly, but also get rid of the Zeno phenomenon fundamentally. The event-triggering scheme and the FDF are co-designed. Finally, the efficient performance of the proposed fault detection method based on integral-based event-triggering scheme is illustrated by simulation.

Event-triggered fault detection for continuous-time networked polynomial-fuzzy-model-based systems

The paper deals with the event-triggered fault detection filter design problem for continuous-time networked polynomial-fuzzy-model-based (PFMB) systems. Unlike some existing results, a novel polynomial event-triggered mechanism (PETM) is introduced to reduce the network resource occupancy. Moreover, the resultant event-triggered conditions are checked only at each sampling instant. A polynomial fault detection filter (PFDF), whose membership functions (MFs) and fuzzy rules are different from the considered PFMB systems, is designed to ensure the augmented PFMB fault detection system is asymptotically stable with H∞ performance. The communication delay in communication network transmission is also considered. By adopting an appropriate Lyapunov–Krasovskii (L-K) functional, the sum of square (SOS)-based design conditions are less conservative and time-delay dependent. Two examples are used to demonstrate the effectiveness of the proposed method.

Event-triggered fault detection filter design for uncertain stochastic systems with package dropouts

In this article, the event-triggered fault detection filter design problem is concerned with uncertain stochastic systems subject to package dropouts. First, a filter structure is constructed to achieve the desired fault detection objective. Second, an integrated model with an event-triggered scheme and a Bernoulli stochastic process are employed to save the limited network resources and describe the package dropouts phenomenon, which always appears in the real network environment. A new sufficient condition is provided to ensure that the obtained residual system is mean square robustly exponentially stable and satisfies the desired detection performance. Then, a novel co-design algorithm is derived to obtain the parameters of filter and event-triggered scheme. Finally, two simulation examples are provided to verify the effectiveness of the proposed design scheme.

Fault detection filtering for nonlinear switched systems via event-triggered communication approach

This paper considers the fault detection problem for networked switched control systems subject to repeated scalar nonlinearities and stochastic disturbance under an event-triggered scheme. A nonlinear fault detection filter is proposed to generate the residual signal and detect system faults, and an event-triggered strategy is applied to limit signal transmission. Sufficient conditions to guarantee an event-based residual system is mean-square exponentially stable with the desired performance are obtained using average dwell time stability theory and a positive diagonally dominant Lyapunov functional approach. The corresponding fault detection mechanism parameters are calculated using the linearization technique. The event-triggered fault-detection filter and controller coordinated design are extended and then applied to cognitive radio networks. Two examples are provided to verify the proposed new design method.

Event-Triggered Fault Detection Filter Design for Nonlinear Networked Systems

This paper investigates the problem of event-triggered fault detection (FD) filter design for nonlinear networked systems in the framework of interval type-2 fuzzy systems. In the system model, the parameter uncertainty is captured effectively by the membership functions (MFs) with upper and lower bounds. For reducing the utilization of limited communication bandwidth, an event-triggered communication mechanism is applied. A novel FD filter subject to event-triggered communication mechanism, data quantization, and communication delay is designed to generate a residual signal and detect system faults, where the premise variables are different from those of the system model. Consequently, the augmented FD system is with imperfectly matched MFs, which hampers the stability analysis and FD. To relax the stability analysis and achieve a better FD performance, the information of MFs and slack matrices are utilized in the stability analysis. Finally, two examples are employed to demonstrate the effectiveness of the proposed scheme.

Event-triggered fault detection filter design for nonlinear networked systems via fuzzy Lyapunov functions

This paper investigates the problem of event-triggered fault detection filter design for nonlinear networked control systems with both sensor faults and process faults. First, Takagi–Sugeno (T–S) fuzzy model is utilized to represent the nonlinear systems with faults and disturbances. Second, a discrete event-triggered communication scheme is proposed to reduce the utilization of limited network bandwidth between filter and original system. At the same time, considering network-induced delays and event-triggered scheme, a novel T–S fuzzy fault detection filter is constructed to generate a residual signal, which has nonsynchronous premise variables with the original T–S fuzzy system. Then, the fuzzy Lyapunov functional based approach and the reciprocally convex approach are developed such that the obtained sufficient conditions ensure that the fuzzy fault detection system is asymptotically stable with H∞ performance and is less conservative. All the conditions are given in terms of linear matrix inequalities (LMIs), which can be solved by LMI tools in MATLAB environment. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed results.

Adaptive Event-Triggered Fault Detection for Fuzzy Stochastic Systems With Missing Measurements

This paper discusses adaptive event-triggered fault detection filter design for fuzzy stochastic models with missing measurements. First, a novel event-triggered strategy is introduced, while an adaptive law is provided to adjust communication threshold dynamically. Compared with traditional event-triggered methods with fixed threshold, the proposed strategy is more effective on saving network communication resources. Second, a Bernoulli stochastic process is proposed to describe the measurement missing phenomenon, which always appears in real network environment. Then, an integrated fault detection model for fuzzy stochastic systems is constructed by taking network-induced delays, adaptive event-triggered strategy and missing measurements into account. A new method is provided to achieve mean-square asymptotical stability of residual model with one desired fault detection objective. Finally, simulation cases are introduced to verify the validity of the designed strategy.

Event-triggered fault detection filtering for discrete-time Markovian jump systems

Abstract This paper addresses the problem of fault detection for discrete-time Markovian jump systems in an event-triggered scheme. An event-triggered scheme from the plant to the fault detection filter is used to reduce the transmission frequency. The purpose is to design a fault detection filter such that the residual system is stochastically stable and satisfies the performance expectation. The conditions for existence are obtained for a class of discrete-time Markovian jump systems. If these conditions are feasible, a desired event-triggered fault detection filter can be easily constructed. In addition, the cone complementarity linearization procedure is used to cast the filter design problem with a sequential minimization problem, which can be efficiently solved using the current optimization techniques. Finally, a numerical example is given to illustrate the effectiveness of the proposed theory.

Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System.

This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.