Fault Detection And Isolation Filter Research Articles

Stochastic Event-Triggered Fault Detection and Isolation Based on Kalman Filter.

In this article, the robust fault detection and isolation (FDI) Kalman filter is extended based on stochastic event-triggered schedulers for discrete linear systems consisting of deterministic/stochastic unknown inputs with nonzero mean and colored measurement noise. In the proposed FDI method, first, a subspace of the main system that significantly attenuates disturbance effects is proposed. After that, the fusion method is proposed for dealing with the colored measurement-noise problem in designing the Kalman filter and preventing from leading to measurement noise with zero mean and zero covariance. The stochastic event-triggered schedulers are considered as Gaussian functions. Therefore, the Gaussian property of innovation sequence is preserved, and consequently, the recursive equation of the Kalman filter need not be extended based on approximation techniques. Finally, design parameters are chosen based on the convex optimization problem such that the lowest communication rate between the sensor node and FDI filter, and also the best FDI performance are achieved. The proposed FDI method is evaluated to detect and isolate stator interturn short circuit and broken rotor bars faults with unbalanced voltage as disturbance in three-phase induction motors.

Fault Detection and Isolation for a Class of Nonlinear Systems Based on Gerschgorin Theorem and Optimization Approach

This article is concerned with the fault detection and isolation (FDI) problem for a class of nonlinear systems described by the T–S fuzzy models. Based on the concept of minimum unobservability subspace and geometric property of factor space, a set of FDI filters where each residual is only affected by one fault and completely decoupled from other faults is designed. Furthermore, in the decoupling space, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty }/H_{-}$ </tex-math></inline-formula> performance indexes are provided to enhance the sensitivity of residual to faults and robustness to disturbances. In particular, to solve the nonconvex filter design problem caused by introducing the <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> index, the Gerschgorin theorem is first used to linearize the corresponding filter design conditions in the outer region of a ball. Then, the FDI filter design problem is converted into a convex optimization one, which is solved via the linear matrix inequality (LMI) control Toolbox, and the advantages and effectiveness of the proposed FDI method are verified through two simulation examples.

Fault-Tolerant Control for a High Altitude Long Endurance Aircraft

High Altitude Long Endurance (HALE) aircraft consist of extremely light-weight structures in combination with a high wingspan and high aspect ratio. The combination of these properties results in an unique dynamic behavior of the aircraft system featuring a strong interaction of structural and rigid body eigenmodes. These characteristics lead to specific demands on the robustness and fault tolerance of flight control algorithms of such aircraft. The control system must be able to navigate the aircraft safely along defined tracks even in case of fault scenarios. Due to the size of these aircraft they are usually over-actuated featuring multiple redundant control surfaces. This redundancy is used in this paper to design a fault tolerant control system ensuring optimal control performance during fault scenarios. The strategy is based on a fault detection and isolation (FDI) algorithm to detect malfunctioning control surfaces. This fault information is used to switch to alternate control laws in a multi-model control approach. The FDI filters are designed using the nullspace-based design paradigm, while the alternate controllers are synthesized applying structured H∞ control design techniques.

Asynchronous Fault Detection and Isolation for Markov Jump Systems With Actuator Failures Under Networked Environment

This paper is concerned with the asynchronous fault detection and isolation (FDI) strategy in finite frequency domain for Markov jump systems (MJSs) with actuator failures under networked environment. A set of binary-valued Bernoulli distributed sequences is introduced to describe the transmission and the scheduling of the sensor nodes. Then, an MJS directing by two Markov process and with multiple stochastic parameters is derived to characterize the whole system dynamics. Subsequently, by means of the stochastic $\mathcal {H}_{-}$ index in finite frequency domain and the geometric mapping approach, an asynchronous FDI scheme is investigated, in which the filters complete the FDI mission with only partial information of the measurements. Meanwhile, each FDI filter is only sensitive to one possible actuator fault and decoupled from others. Then the existence of the desired filters is ensured by some novel sufficient conditions. Finally, an application example is presented to show the effectiveness of the proposed theoretical results.

Modeling and fault diagnosis design for HVAC systems using recurrent neural networks

In this work, we develop models and a fault detection and isolation (FDI) methodology for heating, ventilation and air conditioning (HVAC) systems that utilizes recurrent neural networks (RNN). The FDI design does not require the existence of plant fault history, mechanistic models or a set of expert rules to isolate faults. The key is to first use plant data to build predictive models and input/output estimators, and then embed them within FDI filters. A distributed FDI framework is designed consisting of local FDI (LFDI) schemes that communicate with each other for improved FDI. The distributed FDI framework enables diagnosis of multiple faults in different components of the HVAC system when a fault in one of the control components directly affects the other subsystems. The effectiveness of the proposed FDI scheme is shown via simulation examples on a simulation test bed, as well as using real data. The simulations revealed superior performance of the proposed FDI methodology over FDI approaches using subspace based models for both simulation and real data cases.

Fault detection of discrete-time delay Markovian jump systems with delay term modes partially available

This paper focuses on the fault detection problem for a class of discrete-time delay Markovian jump systems with delay term modes partially available. A crucial but general hypothesis considered here is there is a suitable and effective detector to provide a measurement signal of operation mode of delay term. The fault detection filter used as the residual generator could depend on the original system operation mode or the signal emitted from detector. Via minimizing the error between the residual and fault signal, the problem of fault detection and isolation (FDI) is converted into an H∞ filtering problem and closely related to a probability representing the degree of dependence between the original and measurable signals. An improved Lyapunov function depending on such two operation modes is exploited to study the corresponding problems. Sufficient conditions for the existence of the desired FDI filter are presented in terms of LMIs. When such a probability is uncertain or partially unknown, similar problems are also considered. A practical example is used to demonstrate the effectiveness and superiority of the proposed methods.

An Observer-Based Fault-Tolerant Controller for Flexible Buildings-Based on Linear Matrix Inequality Approach

Since failures in sensors will degrade the performance of Active Mass Damper (AMD) control systems, a dynamic filter design method, a state observer design method, and a robust control strategy are developed and presented in this paper to overcome this deficiency. The filter design method will be transformed into a H2/H∞ control problem that can be solved by Linear Matrix Inequality (LMI) approach. Thus, it can be used to perform fault detection and isolation (FDI) for the control systems. And, the state observer design method uses the acceleration responses as the feedback signal. The detected and isolated fault signals in accelerometers are used to estimate the whole states that are used to calculate the control force though a robust control strategy based on regional pole-assignment algorithm. Then, the active fault-tolerant control (FTC) will be accomplished. To verify its effectiveness, the proposed methodology is applied to a numerical example of a ten-storey frame and an experiment of a single span four-storey steel frame. Both numerical and experimental results demonstrate that the performances of FTC controller and the control system will be improved by the designed dynamic FDI filter and that it can effectively detect and isolate fault signal.

Transmission-Dependent Fault Detection and Isolation Strategy for Networked Systems Under Finite Capacity Channels.

This paper addresses a novel transmission-dependent fault detection and isolation (FDI) scheme in finite frequency domain for networked control systems with consideration of limited communication capacity, which includes multiple transmission intervals and delays, media accessing constraints as well as packet losses. By focusing on these phenomena, a switched stochastic system with multistochastic parameters is first modeled to represent the network-induced features. Then, with the aid of finite frequency stochastic performance index and geometric analysis method, a novel FDI scheme is proposed in finite frequency domain. The FDI filters are designed corresponding to the different transmission intervals and complete the task of detection and isolation only by partially available measurements. A novel lemma is investigated subsequently to capture the desired finite frequent stochastic performance for derived systems. Based on this lemma, sufficient conditions are developed to characterize the filter gains. Finally, an application to the VTOL aircraft is presented to show the effectiveness of the proposed approach.

Decentralized fault detection and isolation of Markovian jump interconnected systems with unknown interconnections

SummaryThis paper investigates the decentralized fault detection and isolation (FDI) problem for Markovian jump interconnected systems with unknown interconnections. Different from the existing decentralized FDI approaches, the requirement for access to operation modes of all subsystems, which is unreasonable and hard to meet in realistic applications, is removed. By utilizing local measurements and neighboring mode information, a decentralized FDI filter is constructed to generate a residual for each subsystem of Markovian jump interconnected system. Then, a new design method is developed such that the resulting augmented system is stochastically stable and the generated residual is sensitive to local fault. In addition, the proposed method can achieve fault detection and isolation simultaneously. Finally, two examples are given to illustrate the effectiveness and merits of the new results. Copyright © 2017 John Wiley &amp; Sons, Ltd.

Distributed state estimation, fault detection and isolation filter design for heterogeneous multi‐agent linear parameter‐varying systems

In this study, the authors present a new approach for the design of distributed state estimation and fault detection and isolation (FDI) filters for a class of linear parameter-varying multi-agent systems, where the state-space representations of the agents are not identical. The developed formulation for the FDI offers a distributed filter design method, in which each agent uses sensor measurements both locally and from the neighbouring agents. Each FDI filter is in the ‘unknown input observer’ form which are designed so that their outputs, i.e. residual signals, are: (i) robust with respect to the external disturbance inputs and (ii) sensitive with respect to the fault signals. Moreover, it is shown that using the proposed methodology each agent is able to estimate not only its own states, but also states of its nearest neighbours in the presence of external disturbances and faults. Finally, a numerical example is given to illustrate the efficacy of the main results of the paper.

Fault Detection for Markovian Jump Systems With Partially Available and Unmatched Modes

In this paper, the fault detection problem for a class of continuous-time Markovian jump systems is considered. A residual generator is constructed by a fault detection filter. The corresponding fault detection and isolation (FDI) problem is converted into an $H_\infty $ filtering problem by minimizing the error between residual and fault in $H_\infty $ sense. Particularly, the filter designed here is neither mode-dependent nor mode-dependent, whose operation mode is partially available but unmatched. Sufficient conditions for the existence of an FDI filter are derived in terms of linear matrix inequalities. A numerical example is given to illustrate the effectiveness and potential application of the developed theoretical results.

Fault Detection for Discrete-Time Systems With Fault Signal Happening Randomly: The Markov Approach

In this paper, the fault detection problem is considered for a class of discrete-time systems with fault signal happening randomly. First, the random occurrence of fault is described by a Markov approach, which is transformed into some matrices experiencing Markov switchings. By using a fault detection filter as a residual generator, the fault detection and isolation (FDI) problem is transformed into an $H_\infty $ filtering problem. Moreover, a mode-dependent Lyapunov functional is exploited to make its analysis and synthesis and is also named to be a fault-dependent approach. Then, sufficient conditions on the existence of an FDI filter are all provided in terms of linear matrix inequalities, in which two general cases about transition probability matrix are included. Finally, a practical example is used to illustrate the effectiveness and potential application of the developed theoretical results.

Fault Detection and Isolation for Affine Fuzzy Systems With Sensor Faults

This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method.

Fault detection and isolation analysis and design for solution copolymerization of MMA and VAc process

The problem of detecting and isolating distinguishable actuator and sensor faults in the solution copolymerization of methyl methacrylate and vinyl acetate monomers are considered in this work. To this end, first state estimates are generated using a bank of high‐gain observers, and nonlinear fault detection and isolation (FDI) residuals are defined. The process dynamics are further analyzed to categorize fault scenarios as distinguishable and indistinguishable, and the necessary and sufficient conditions for the classification are presented. Subsequently, filters are designed that enable FDI for the distinguishable fault scenarios, with the advantage of detecting and confining possible locations for indistinguishable faults. The FDI filters are implemented on the copolymerization process, and the results compared with a linear model based filter design. © 2015 American Institute of Chemical Engineers AIChE J, 62: 1054–1064, 2016

A new approach to deal with sensor errors in structural controls with MR damper

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order H FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

Distributed Fault Detection and Isolation Filter Design for a Network of Heterogeneous Multiagent Systems

In this brief a distributed fault detection and isolation (FDI) methodology for a network of heterogeneous multiagent systems with different dynamics and order from one another is proposed. An FDI filter is designed such that the effects of disturbances and control inputs on the residual signals are minimized (for accomplishing the fault detection task) subject to the constraint that the transfer matrix function from the faults to the residuals is equal to a preassigned diagonal transfer matrix (for accomplishing the fault isolation task). Moreover, by utilizing the proposed methodology, isolation of simultaneous occurring faults can also be handled. Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. The extended LMI characterization is then used to reduce the conservativeness of the solution by eliminating the couplings between the Lyapunov matrices and the agents' matrices. Simulation results presented demonstrate the effectiveness and capabilities of our proposed design methodology.

Fault detection and isolation for discrete-time switched linear systems based on average dwell-time method

This article is concerned with the problem of fault detection and isolation (FDI) for discrete-time switched linear systems based on the average dwell-time method. The proposed FDI framework consists of a bank of FDI filters, which are divided into N groups for N subsystems. The FDI filters belonging to one group correspond to the faults for a subsystem, and generate a residual signal to guarantee the fault sensitivity performance for the subsystem, the fault attenuation performance for other subsystems and the disturbance attenuation performance for all subsystems. Different form employing the weighting matrices to restrict the frequency ranges of faults for each subsystem, the finite-frequency H − performance for switched systems is first defined. Sufficient conditions are established by linear matrix inequalities (LMIs), and the filter gains are characterised in terms of the solution of a convex optimisation problem. Two examples are used to demonstrate the effectiveness of the proposed design method.

Fault Tolerant Control for Civil Structures Based on LMI Approach

The control system may lose the performance to suppress the structural vibration due to the faults in sensors or actuators. This paper designs the filter to perform the fault detection and isolation (FDI) and then reforms the control strategy to achieve the fault tolerant control (FTC). The dynamic equation of the structure with active mass damper (AMD) is first formulated. Then, an estimated system is built to transform the FDI filter design problem to the static gain optimization problem. The gain is designed to minimize the gap between the estimated system and the practical system, which can be calculated by linear matrix inequality (LMI) approach. The FDI filter is finally used to isolate the sensor faults and reform the FTC strategy. The efficiency of FDI and FTC is validated by the numerical simulation of a three-story structure with AMD system with the consideration of sensor faults. The results show that the proposed FDI filter can detect the sensor faults and FTC controller can effectively tolerate the faults and suppress the structural vibration.

Fault detection and isolation for networked control systems with finite frequency specifications

SUMMARYThe fault detection and isolation (FDI) problem with finite frequency specifications is addressed in this paper under the framework of geometric approach for networked control systems subject to communication constraints and packet losses. The considered communication constraint is that only one of the transmission nodes is allowed to gain access to the shared channel. Also, those transmission nodes are scheduled to transmit data according to a specified stochastic protocol. Then by virtues of the common unobservable subspace and the finite frequency stochastic H − index, a novel FDI scheme is developed in which a set of FDI filters that perform the FDI task with only partially available measurements are designed such that each residual is only sensitive to one fault in certain frequency domain and decoupled from the others. Further, less conservative conditions including some previous existing results have been presented to construct the FDI filters. Finally, an example is given to illustrate the effectiveness of the proposed method.Copyright © 2012 John Wiley &amp; Sons, Ltd.

A numerically reliable approach for the synthesis of periodic FDI filters

We propose an integrated numerically reliable computational approach to solve fault detection and isolation (FDI) problems for periodic systems. For this purpose, a bank of periodic fault detection filters providing a structured residual set is designed using a new least order synthesis technique of periodic fault detection filters. The synthesis procedure relies on a recently developed numerically stable algorithm to compute least order annihilators of periodic systems. This approach is extended with two additional steps for the synthesis of least order filters by using periodic dynamic cover techniques and periodic stable coprime factorizations to achieve a desired dynamics of the filters. The proposed integrated synthesis algorithm has strongly coupled computational steps, where the available structural information at the end of each step is fully exploited in the subsequent computations. All computations are done directly on the original problem data, without explicitly building time-invariant lifted system representations.