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This paper presents a distributed fault diagnosis scheme able to deal with process and sensor faults in an integrated way for a class of interconnected input–output nonlinear uncertain discrete-time systems. A robust distributed fault detection scheme is designed, where each interconnected subsystem is monitored by its respective fault detection ag...
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This article proposes a fault diagnosis method for closed-loop satellite attitude control systems based on a fuzzy model and parity equation. The fault in a closed-loop system is propagated with the feedback loop, increasing the difficulty of fault diagnosis and isolation. The study uses a Takagi-Sugeno (T-S) fuzzy model and parity equation to diag...
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... Existing work in the literature relies on several methods of detecting and isolating sensor faults. This objective is achieved in [3][4][5] through fault detection and isolation techniques (FDI) in non-linear systems. Besides the authors of [6,7] used Predictive Control for sensor fault accommodation in nonlinear systems. ...
The authors’ work deals with modelling with coloured Petri nets (CPN) of network controlled systems (NCS) and exposes a proposal of a sensor fault detection and prevention mechanism. In NCS, the network must be viewed as part of the system and not just a means of communication. For this, two issues must be considered. The first consists of adapting the control and diagnostic laws to the performance of the network. The second is to guarantee the performance of the system. Each control loop containing a network is vulnerable to faults and cyber attacks and malicious users can intercept and listen to data during transmission. For that reason, it is essential to protect transmitted data against unauthorized access and modification and to diagnose components. In this paper, the authors presented a model with CPN of a NCS, the authors proposed a sensor fault detection and correction mechanism, then the authors injected a sensor fault and the authors tested the effectiveness of the proposed mechanism in detecting that fault and correcting its influence. Simulation results proved the success of the preventive mechanism in overcoming the influence of the fault and returning to normal behaviour.
... The sensor faults will make the state unavailable [18], which presents great challenges to the design of the controller. The non-linear systems with sensor faults were investigated in [19][20][21]. For instance, [20] realized real-time monitoring and isolation of system faults based on the neural network (NN) adaptive structure. ...
... For instance, [20] realized real-time monitoring and isolation of system faults based on the neural network (NN) adaptive structure. A distributed FTC method for the process and sensor faults was proposed in [21]. For FTC of uncertain non-linear systems, backstepping technology has been widely used in order to facilitate the design of the controller. ...
In this article, an adaptive fuzzy finite‐time fault‐tolerant control (FTC) scheme for uncertain non‐linear systems under sensor faults is proposed. Compared with the existing methods, the considered system contains unknown time‐varying fault parameters, uncertain non‐linear functions, and can guarantee the performance of the system in finite time. The coupling between fault parameters and actual states is solved by the fault parameters separation method. The fuzzy logic system (FLS) is used to approximate the unknown functions, and combining the backstepping technology an adaptive fault‐tolerant controller is designed. The finite‐time stability of the closed‐loop system is proved by the Lyapunov theory. At last, the numerical simulation and the real physical system simulation verified the effectiveness of the proposed scheme.
... A generalized autonomous guard events identification (AGEI) scheme is developed that: (a) identifies promptly potential autonomous guard events before they occur in the system and adjust the detection thresholds accordingly so that false alarms, due to mode mismatch, are prevented in the fault detection scheme, and (b) detects the occurrence of autonomous guard events promptly and triggers them in the hybrid estimator, allowing effective mode estimation. 2. The filtering approach devised in [26] for discrete-time systems is extended for the case of nonlinear uncertain hybrid systems. Specifically, the filtering was incorporated into the detection scheme for detecting not only faults in the time-driven dynamics part as in [26] but also faults in the discrete dynamics part. ...
... 2. The filtering approach devised in [26] for discrete-time systems is extended for the case of nonlinear uncertain hybrid systems. Specifically, the filtering was incorporated into the detection scheme for detecting not only faults in the time-driven dynamics part as in [26] but also faults in the discrete dynamics part. Moreover, rigorous analytical results for detectability/isolability conditions in the context of uncertain hybrid systems are presented. ...
... Moreover, rigorous analytical results for detectability/isolability conditions in the context of uncertain hybrid systems are presented. Lastly, a new elegant formulation based on filtering notation is adopted compared to the convolution summation used in [26] to derive the detection threshold, providing a simple and intuitive presentation for the whole filtering approach. 3. A fault isolation scheme that uses the filtering approach is developed which anticipates possible faults and dynamically employs only the necessary isolation estimators for efficient fault isolation utilizing an exclusion based isolation logic and suitable thresholds. ...
This paper presents a fault diagnosis architecture for a class of hybrid systems with nonlinear uncertain time-driven dynamics, measurement noise, and autonomous and controlled mode transitions. The proposed approach features a hybrid estimator based on a modified hybrid automaton framework. The fault detection scheme employs a filtering approach that attenuates the effect of the measurement noise and allows tighter mode-dependent thresholds for the detection of both discrete and parametric faults while guaranteeing no false alarms due to modeling uncertainty and mode mismatches. Both the hybrid estimator and the fault detection scheme are linked with an autonomous guard events identification (AGEI) scheme that handles the effects of mode mismatches due to autonomous mode transitions and allows effective mode estimation. Finally, the fault isolation scheme anticipates which fault events may have occurred and dynamically employs the appropriate isolation estimators for isolating the fault by calculating suitable thresholds and estimating the parametric fault magnitude through adaptive approximation methods. Simulation results from a five-tank hybrid system illustrate the effectiveness of the proposed approach.
... Moreover, the MVFP model provides a greater generalization ability of the results for different engines, since it can be easily reconfigured in its parameters and can also be expanded to host more subsystems and sensors. Compared to the state-of-theart in distributed model-based fault diagnosis literature where mostly systems described by ordinary differential equations (ODE) are considered [Reppa et al. (2016); Boem et al. (2017); Keliris et al. (2015)], this work focuses on systems described by nonlinear DAE. The design of algebraic residuals and adaptive thresholds is a challenging task that affects the detectability of sensor faults. ...
This paper proposes a distributed model-based methodology for the detection and isolation of sensor faults in marine fuel engines. The proposed method considers a Mean Value First Principle model and a wide selection of heterogeneous sensors for monitoring the engine components. The detection of faults is realised based on residuals generated using nonlinear Differential Algebraic estimators combined with adaptive thresholds. The isolation of faults is, then, realised in two levels; local sensor fault detection and isolation agents are designed to monitor specific sensor sets and aim to detect faults in these sets; and a global decision logic is designed to isolate multiple sensor faults that may be propagated between the local monitoring agents. Finally, simulation results are used to illustrate the application of this method and its efficiency.
... In fact, naturally, the architecture of the underlying subsystem is decentralized or distributed, which means that it is necessary to develop distributed FD and FR frameworks. In other words, local fault diagnosis and reconstruction should be performed [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. However, since the interconnected systems are becoming increasingly complex, the problem of system fault reconstruction has also become increasingly difficult, especially problems related to fault propagation, due to the fact that faults occurring in one subsystem influence adjacent subsystems. ...
... Therefore, in order to better understand the fault propagation problems, there is research concerning both local and global systems such as in Refs. [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. An important method is to propose a local observer for individual subsystems using its own input and output measurements. ...
The problem of local fault (unknown input) reconstruction for interconnected systems is addressed in this paper. This contribution consists of a geometric method which solves the fault reconstruction (FR) problem via observer based and a differential algebraic concept. The fault diagnosis (FD) problem is tackled using the concept of the differential transcendence degree of a differential field extension and the algebraic observability. The goal is to examine whether the fault occurring in the low-level subsystem can be reconstructed correctly by the output at the high-level subsystem under given initial states. By introducing the fault as an additional state of the low subsystem, an observer based approached is proposed to estimate this new state. Particularly, the output of the lower subsystem is assumed unknown, and is considered as auxiliary outputs. Then, the auxiliary outputs are estimated by a sliding mode observer which is generated by using global outputs and inverse techniques. After this, the estimated auxiliary outputs are employed as virtual sensors of the system to generate a reduced-order observer, which is caplable of estimating the fault variable asymptotically. Thus, the purpose of multi-level fault reconstruction is achieved. Numerical simulations on an intensified heat exchanger are presented to illustrate the effectiveness of the proposed approach.
... For instance, a distributed sensor fault diagnosis method for a class of interconnected nonlinear discrete-time systems was presented. 15 However, the diagnosis was achieved in a high-level isolation scheme. Moreover, a distributed fault diagnosis method was presented to identify sensor/actuator faults in a mobile robots formation with a leader-follower topology. ...
... where h(e q i ) is defined in (15). The second condition of the Schur's complement is ...
... Fault diagnosis is considered as fault detection, isolation, and identification. 15 In addition, the diagnosis should be decentralized to be applicable on each satellite to be able to diagnose the sensor fault of neighbors. It is assumed that each satellite communicates only its attitude tracking errors of its neighbors. ...
This article presents a decentralized framework of active fault tolerant control for attitude synchronization in satellite formation flying. By employing a nonlinear observer and a static approximator, the fault in both the angular velocity and orientation sensors can be diagnosed whether the sensor belongs to the satellite or its neighbors. The convergence of the observer is guaranteed by utilizing Lyapunov's direct method and Barbalat's lemma. The proposed approach is based on unknown input and requires only the angular velocity and orientation of the states in a decentralized architecture. Moreover, by designing a sensor fault tolerant controller, the tracking synchronization among the satellites' attitudes with individual set-points is guaranteed and the uniformly ultimate boundedness of the synchronization/tracking errors is provided. The simulation results are presented to illustrate the performance of the developed algorithm.
... When analysing a WDN during its normal operation, one faces sensor faults that manifest in various forms, such as missing data, measurement drift/bias, stuck at a value, etc. Unfortunately, the leak detection literature does not typically consider sensor faults, since simultaneous system/sensor fault detection requires specific assumptions, whether they are temporal conditions [12], physical modeling assumptions [13] or probabilistic assumptions [14]. ...
Detecting leaks in Water Distribution Networks (WDN) using sensors has become crucial towards an efficient management of water resources. The leak detection methods that use this data rely on the correctness of the acquired data. However, this assumption is often violated in practice. Consequently, leak detection under sensor faults is a problem of practical importance. This relates to the more general problem of simultaneous detectability in sensor and process faults for a class of systems modelled as a network, by exploiting the redundancies available through the topological relationship between the sensors. This paper hence aims at i) modeling WDN as graphs containing both systems and sensors faults ii) providing theoretical joint detectability results for such graphs and iii) applying these results to the scenario of leak identification under sensor faults conditions on real data issued from a rural WDN.
... The fault detection scheme utilizes the filtering approach devised in Keliris et al. (2015) for uncertain discrete-time systems and later adapted for the case of uncertain hybrid systems in Heracleous et al. (2018a). The use of filtering dampens the effect of measurement noise and allows the derivation of tighter detection thresholds, which enhances the detectability of smaller magnitude faults. ...
... whereH p (z) is a filter with impulse responseh p (t) that satisfiesh p (t) ≥ |h p (t)| for all t ≥ 0 (methods for selecting a suitable filterH p (z) are discussed thoroughly in Keliris et al. (2015)), andv i is a bounding estimate of v i,0 , i.e., v i ≥ |v i,0 |. Note that the term |h(k)|v i affects the detection threshold only during the initial transient, because the impulse response h(k) of a proper and asymptotically stable transfer function H(z) converges to zero exponentially fast. ...
This paper presents a sensor bias fault diagnosis approach for a class of hybrid systems with nonlinear uncertain discrete-time dynamics, measurement noise, and autonomous and controlled mode transitions. The proposed approach uses an observer based on a modified hybrid automaton framework and a fault detection scheme that employs a filtering method tighter mode-dependent thresholds for the detection of sensor faults (even with small magnitude). An autonomous guard events identification (AGEI) module is also developed and linked with both the fault detection scheme and the hybrid observer to eliminate any false alarms due to autonomous mode transitions and allow effective mode estimation. Finally, an adaptive sensor fault estimation scheme is included, which is activated once a fault is detected to isolate and estimate the sensor bias fault magnitude.
... There are some results that consider only the problem of FDI in networked and large-scale systems using a distributed architecture only accounting for faults in local variables and propagation of their effect via distributed variables (see e.g., Refs. [14][15][16][17][18][19]. In Ref. 15, a distributed FDI framework is proposed for a class of interconnected uncertain nonlinear systems using adaptive estimation techniques. ...
The problem of distributed fault detection and isolation (FDI) for heating, ventilation, and air conditioning (HVAC) systems has been addressed in this work. First, a linear model is identified for subunits of an HVAC system. Next, a local FDI (LFDI) framework is designed for each unit under consideration. A distributed FDI architecture is designed where the LFDI frameworks communicate to exchange information to achieve enhanced FDI in each unit. As a result, each LFDI framework functions as intended even in the presence of faults that affect multiple units. Effectiveness of the proposed distributed FDI framework is shown for various commonly occurring fault scenarios. © 2018 American Institute of Chemical Engineers AIChE J, 65: 640–651, 2019
... There are some results that only consider problem of fault detection in networked and large scale systems using a distributed architecture (see e.g., Boem et al. (2017)). In Keliris et al. (2015), an integrated distributed fault detection scheme is proposed for detection of sensor and process faults in nonlinear uncertain discrete systems. However, fault isolation is not achieved. ...
... Also, the results addressing isolation of actuator faults are based on the assumption that full state measurements are available (see e.g., Ferrari et al. (2012)) or only valid for cascade process networks in the absence of uncertainty ( see e.g., Yin and Liu (2017)). More importantly, the conditions under which the network structure allows fault isolation in the presence of uncertainty is not discussed in the existing results available in the literature (see e.g., Zhang and Zhang (2012), Ferrari et al. (2012), Keliris et al. (2015) and Reppa et al. (2015)). ...
... Remark 1. Note that in this work (as with other existing results (see e.g., Ferrari et al. (2012), Keliris et al. (2015) and Reppa et al. (2015)) the direct interconnection terms are not allowed to be a function of neighboring subsystems inputs u j . This follows from the assumption that each subsystem can be operated with a local controller (possibly utilizing measurements from the other subsystems). ...
In this work, we address the problem of simultaneous fault diagnosis in nonlinear uncertain networked systems utilizing a distributed fault detection and isolation (FDI) strategy. The key idea is to design a bank of local FDI (LFDI) schemes that communicate with each other for improved FDI. The proposed distributed FDI scheme is shown to be able to handle local faults as well as those that affect more than one subsystem. This is achieved via appropriate adaptation of the LFDI filters based on information exchange with other subsystems and using the proposed notion of detectability index. The detectability index and isolability conditions are rigorously derived for the distributed FDI scheme. Effectiveness of the proposed methodology is shown via application to a reactor-separator process subject to uncertainty and measurement noise.
