Fault Reconstruction Research Articles

Robust observer-based sensor fault reconstruction for discrete-time systems via a descriptor system approach

This paper addresses the problem of observer-based sensor fault reconstruction for discretetime systems subject to external disturbances via a descriptor system approach. First, an augmented descriptor system is formulated by letting the sensor fault term be an auxiliary state vector; then a discrete-time descriptor state observer is constructed to achieve concurrent reconstructions of original system states and sensor faults. Sufficient and necessary conditions for the asymptotic stability of the proposed observer are explicitly provided. To broaden its application scope, less restrictive existence conditions are further discussed. Further, sufficient conditions for the robust stability of the proposed observer are formulated in terms of linear matrix inequalities (LMIs) that can be conveniently solved using LMI optimization techniques. After that, an extension of the proposed linear approach to discretetime nonlinear systems with Lipschitz constraint is investigated. At last, two illustrative examples are given to verify the effectiveness of the proposed techniques.

Sensor fault diagnosis using a non‐homogeneous high‐order sliding mode observer with application to a transport aircraft

In avionics and aerospace multisensor systems, reliable and early detection of individual sensor faults present substantial challenges to health monitoring designers of such systems. This study addresses the problem of sensor fault diagnosis. The proposed solution is based on a non-homogeneous high-order sliding mode observer used to estimate the faults, theoretically in finite time and in the presence of bounded disturbances. The sensor faults are estimated for the class of systems satisfying the structural property of strong observability. A key feature of the proposed solution is concerned by the effect that measurement noise could have on fault reconstruction. It is shown that the fault estimation error is bounded in the L∞-norm sense, and an upper bound is theoretically derived. The method is applied to the problem of sensor fault estimation of a large transport aircraft. Simulation results as well as a pilot experiment are presented to demonstrate the potential of the proposed method.

Robust Fault Reconstruction in Discrete-Time Lipschitz Nonlinear Systems via Euler-Approximate Proportional Integral Observers

The problem of observer-based robust fault reconstruction for a class of nonlinear sampled-data systems is investigated. A discrete-time Lipschitz nonlinear system is first established, and its Euler-approximate model is described; then, an Euler-approximate proportional integral observer (EPIO) is constructed such that simultaneous reconstruction of system states and actuator faults are guaranteed. The presented EPIO possesses the disturbance-decoupling ability because its architecture is similar to that of a nonlinear unknown input observer. The robust stability of the EPIO and convergence of fault-reconstructing errors are proved using Lyapunov stability theory together withH∞techniques. The design of the EPIO is reformulated into convex optimization problem involving linear matrix inequalities (LMIs) such that its gain matrices can be conveniently calculated using standard LMI tools. In addition, to guarantee the implementation of the EPIO on the exact model, sufficient conditions of its semiglobal practical convergence are provided explicitly. Finally, a single-link flexible robot is employed to verify the effectiveness of the proposed fault-reconstructing method.

Fault Reconstruction Approach for Distributed Coordinated Spacecraft Attitude Control System

This work presents a novel fault reconstruction approach for a large-scale system, that is, a distributed coordinated spacecraft attitude control system. The attitude of all the spacecrafts in this distributed system is controlled by using thrusters. All possible faults of thruster including thrust magnitude error and alignment error are investigated. As a stepping stone, the mathematical model of thruster is firstly established based on the thruster configuration. On the basis of this, a sliding mode observer is then proposed to reconstruct faults in each agent of the coordinated control system. A Lyapunov-based analysis shows that the observer asymptotically converges to the actual faults. The key feature of this fault reconstruction approach is that it can achieve a faster reconstruction of the fault in comparison with the conventional fault reconstruction schemes. It can globally reconstruct thruster faults with zero reconstruction error, and this is accomplished within finite time. The effectiveness of the proposed approach is analytically authenticated via simulation study.

Fault Reconstruction and Fault-tolerant Control via Learning Observers in Takagi-Sugeno Fuzzy Descriptor Systems with Time Delays

This paper addresses the problems of observer-based fault reconstruction and fault-tolerant control for Takagi–Sugeno fuzzy descriptor systems subject to time delays and external disturbances. A novel fuzzy descriptor learning observer is constructed to achieve simultaneous reconstruction of system states and actuator faults. Sufficient conditions for the existence of the proposed observer are explicitly provided. Utilizing the reconstructed fault information, a reconfigurable fuzzy fault-tolerant controller based on the separation property is designed to compensate for the impact of actuator faults on system performance by stabilizing the closed-loop system. In addition, the design of the fault reconstruction observer and the fault-tolerant controller is formulated in terms of linear matrix inequalities that can be conveniently solved using convex optimization techniques. Finally, simulation results on a truck–trailer system are presented to verify the effectiveness of the proposed approaches.

Fault-tolerant control of wind turbines with hydrostatic transmission using Takagi–Sugeno and sliding mode techniques

In this paper, a Takagi–Sugeno Sliding Mode Observer for actuator fault diagnosis and fault-tolerant control scheme of wind turbines with hydrostatic transmission are presented. It will be shown that sliding mode techniques have the advantages that several actuator faults of the wind turbine drive train can be simultaneously reconstructed with one and the same observer and directly applied for fault compensation. Furthermore, a simple compensation approach is implemented by subtracting the reconstructed faults obtained from the (faulty) inputs. These corrected inputs act on the system as virtual actuators, such that the originally designed controller for the nominal, i.e. fault-free situation, can still be used. The fault reconstruction and fault tolerant control strategy are tested in simulations with several faults of different types.

Actuator fault reconstruction in an 8-DOF vehicle active suspension system using sliding mode observer

In this paper, an 8–DOF vehicle model including driver seat dynamics, subjected to random road disturbances, is introduced in order to aid the fault detection of actuators in the active suspension system. State feedback control approach is taken in the eight degrees of freedom active suspension system. To estimate the system unavailable states, a sliding mode observer is used. Also, using the sliding mode observer, fault detection of actuators in the active suspension system is performed. The most important specification of this method is its robustness against system uncertainties and external disturbances. In the used fault detection method a direct estimate of the size and severity of the fault is provided which can be important in many applications. The simulation results indicate that actuator faults in the full active suspension system in the presence of external disturbances and model uncertainties are well reconstructed.

Fault Reconstruction for a Quadrotor Using an LPV Sliding Mode Observer1

This paper deals with actuator fault reconstruction in an uncertain quadrotor using a linear parameter varying (LPV) sliding mode observer. First an LPV model of a quadrotor is presented and then an LPV sliding mode observer is developed to reconstruct faults in the actuators. Unlike many existing LPV fault detection schemes for quadrotors, in this paper the measured LPV scheduling parameter is also allowed to potentially be faulty. The main focus of this paper is to detect actuator faults in the motors of an uncertain quadrotor with inaccurate scheduling parameters using a sliding mode observer. Simulations are performed on the full nonlinear model to show the efficacy of the LPV sliding mode observer in reconstructing the faults.

Fault Prediction Algorithm for Multiple Mode Process Based on Reconstruction Technique

In the framework of fault reconstruction technique, this paper studies the problems of multiple mode process fault detection, fault estimation, and fault prediction systematically based on multi-PCA model. First, a multi-PCA model is used for fault detection in steady state process under different conditions, while a weighted algorithm is applied to transition process. Then, describe the faults quantitatively and use the optimization method to derive the fault amplitude under the sense of fault reconstruction. Fault amplitude drifts under different conditions even if the same fault occurs. To solve the above problem, consistent estimation algorithm of fault amplitude under different conditions has been studied. Last, employ the support vector machine (SVM) to predict the trend of the fault amplitude. Effectiveness of the algorithms proposed in this paper has been verified using Tennessee Eastman process as the study object.

Fault Reconstruction for Continuous‐Time Systems Via Learning Observers

ABSTRACTThis paper addresses the problem of learning observer (LO)‐based fault reconstruction in continuous‐time systems. An LO is constructed such that simultaneous reconstruction of system states and actuator faults can be guaranteed. Then, existence conditions of LOs are first introduced to verify whether or not the LOs for fault reconstruction exist. An effective LO‐design algorithm is explored such that observer gain matrices can be conveniently solved using linear matrix inequality technique. An extension to sensor‐fault reconstruction is also investigated. Finally, two simulation examples are employed to demonstrate the effectiveness of the proposed LO‐based fault‐reconstructing approaches.

Design of a non-homogeneous differentiator for actuator oscillatory failure case reconstruction in noisy environment

This work addresses the problem of oscillatory failure case detection in the electrical flight control system of a generic commercial airplane. A non-homogeneous differentiator is first used to provide accurate derivatives in noisy environment and fast convergence time. In this study case, fault detection is addressed in the unknown input estimation issue for fault reconstruction with the same evaluation techniques currently employed in Airbus A380 airplanes. Based on the non-homogeneous differentiator theory, an algorithm for differentiator tuning is provided to manage a trade-off between the accuracy of fault reconstruction and the convergence time that is compliant with specified detection time requirements. Performance and robustness of the developed monitoring strategy are assessed using a high-fidelity Airbus benchmark and a parametric test campaign for the flight scenarios defined in the EU-FP7 ADDSAFE project.

Reliability Evaluation for Distribution System Considering the Access of Distributed Generations

The construction and operating mode of distribution network have changed due to the access of distributed generations (DGs), which has a deep influence on reliability evaluation. A new approach and the related analytical formulation is proposed in this paper to get a better evaluation for distribution network connected to DGs, after considering the fault reconstruction, switch type, DGs types and access locations, islands abundance probabilities and other factors. We propose a classification that includes various cases defined by the relative position of load points (LPs), faults, and switches, in networks with and without DGs. Taking IEEE RBTS BUS6 distribution system for example, the simulation results in the proposed method indicate that DGs improved the reliability for distribution network effectively.

Fault diagnosis of nonlinear process based on KCPLS reconstruction

In this paper, a new kernel concurrent projection to latent structure (KCPLS) reconstruction method for process monitoring is proposed. The main contributions of the proposed approach are as follows: (1) the KCPLS method provides a complete monitoring of faults that happen in the predictable output subspace and the unpredictable output-residual subspace; (2) after the fault reconstruction approach is proposed, the fault-relevant direction is determined; (3) the fault is effectively diagnosed compared to the conventional KPLS method. The proposed method is applied to penicillin fermentation process and is compared to the KPLS method. Experiment results show that the KCPLS can more accurately detect the fault compared to the KPLS method. In addition, the fault-relevant direction is identified more effectively by using the KCPLS reconstruction algorithm compared to the KPLS reconstruction approach.

State and Fault Estimation For Infinitely Unobservable Descriptor Systems Using Sliding Mode Observers

AbstractThis paper presents a novel scheme for estimating states and faults for a class of infinitely unobservable descriptor systems using sliding mode observers (SMOs). Treating certain states of the original infinitely unobservable system as unknown inputs results in a reduced‐order system that is infinitely observable. Then by designing the SMO based on the reduced‐order system, state estimation and fault reconstruction is achieved, thus relaxing the infinite observability requirement of the original system. The necessary and sufficient conditions in terms of the original system matrices are also investigated. A simulation example verifies the claims made in this paper.

Simultaneous time‐varying actuator and sensor fault reconstruction based on PI observer for LPV systems

SummaryWe consider problems of actuator and sensor fault reconstruction simultaneously for linear parameter varying systems expressed in polytopic forms. By extending the sensor fault as an auxiliary state, a polytopic unknown input proportional‐integral observer in which the actuator fault signals are assumed to be time varying is developed to estimate the system states and the actuator and sensor fault at the same time. The existence conditions of the observer are derived in terms of linear matrix inequalities that can be readily handled via some efficient tools. An example is given to demonstrate the advantages of the proposed method in comparison to the existing results. Copyright © 2014 John Wiley & Sons, Ltd.

Fault reconstruction in descriptor linear parameter-varying systems via polytopic unknown-input proportional-integral observers

SUMMARY In this paper, a fault reconstruction scheme for a class of discrete-time descriptor linear parameter-varying systems is investigated. A discrete-time polytopic descriptor linear parameter-varying system subject to external disturbances and actuator faults is first established; then, using H∞ techniques and regional pole constraints, a novel polytopic unknown-input proportional-integral observer is constructed to simultaneously reconstruct system states and actuator faults. Existence conditions for the new polytopic unknown-input proportional-integral observer are explicitly derived. The stability and convergence of the presented observer are proved through Lyapunov theory and linear matrix inequalities. Using a slack-matrix-variable technique, less conservative results for observer design are obtained. At last, an illustrative example is simulated to verify the effectiveness of the proposed fault reconstruction approach. Copyright © 2014 John Wiley & Sons, Ltd.

Fault reconstruction observer design for continuous-time systems with measurement disturbances via descriptor system approach

This paper addresses a problem of observer-based sensor fault reconstruction for continuous-time systems subject to sensor faults and measurement disturbances via a descriptor system approach. An augmented descriptor plant is first formulated, by assembling measurement disturbances and sensor faults into an auxiliary state vector. Then a novel descriptor state observer for the augmented plant is constructed such that simultaneous reconstruction of original system states, sensor faults and measurement disturbances are obtained readily. Sufficient conditions for the existence of the proposed observer are explicitly provided, and the application scope of the observer is further discussed. In addition, an extension of the proposed linear approach to a class of nonlinear systems with Lipschitz constraints is investigated. Finally, two numerical examples are simulated to illustrate the effectiveness of the proposed fault-reconstructing approaches.

Fault reconstructions using aeromagnetic data in the Great Bear magmatic zone, Northwest Territories, Canada

The Great Bear magmatic zone, located in Wopmay orogen, is a 1.875–1.84 Ga belt, 450 km long by 100 km wide of volcanic and allied plutonic rocks interpreted as a Paleoproterozoic magmatic arc. The belt, which contains economically important mineralization, was folded and subsequently cut by a swarm of northeast-striking transcurrent faults, which are part of a regional conjugate fault system interpreted to result from terminal collision of the Nahanni – Fort Simpson terrane. Fault reconstructions based on the interpretation of aeromagnetic data and geological maps provide first-order models of deformation mechanisms associated with, and the configuration of the Great Bear magmatic zone prior to, its dissection by northeast-striking transcurrent faults. The models show that vertical axis block rotation (plane strain) of ∼4.5° can explain fault offsets in the south, but that greater rotation is required to explain many of the displacements in the north. However, offsets on transcurrent faults that border the Camsell River district are greater than can be explained by vertical axis block rotation model alone and may include a component of Mesoproterozoic contractional deformation associated with the Racklan–Forward orogeny. Following reconstruction, iron oxide alkali alteration and associated mineralization, which pre-date transcurrent faulting, form a pair of northerly trending zones on the east and west margins of the belt. We suggest that these zones, whose exposure is related to broad synclinal folding of some of the oldest rocks in the Great Bear magmatic zone, are where iron oxide copper–gold (IOCG)-targeted exploration efforts should be focused on these areas in both outcrop and subcrop.

Fault reconstruction of thruster for autonomous underwater vehicle based on terminal sliding mode observer

The motion modeling and thruster fault reconstruction for autonomous underwater vehicle (AUV) system are addressed in this paper. Considering the modeling uncertainty of the AUV motion model given by dynamics analysis method, we present an AUV motion modeling method based on RBF neural networks. Since there is asymptotic convergence problem in the process of using traditional sliding mode observer to estimate the state signal, which cannot be measured directly by sensor, the fault signal cannot be reconstructed timely. Therefore, a Terminal sliding mode observer is presented to ensure each estimated state signal converge in a finite time. According to the output of Terminal sliding mode observer, the equivalent output injection method is used to reconstruct thruster fault. Finally, the feasibility and effectiveness of the proposed approach is demonstrated with pool experiments of the experimental prototype.

Development and application of sliding mode LPV fault reconstruction schemes for the ADDSAFE Benchmark

This paper describes the development and the evaluation of a robust sliding mode observer fault detection scheme applied to an aircraft benchmark problem as part of the ADDSAFE project. The ADDSAFE benchmark problem which is considered in this paper is the yaw rate sensor fault scenario. A robust sliding mode sensor fault reconstruction scheme based on an LPV model is presented, where the fault reconstruction signal is obtained from the so-called equivalent output error injection signal associated with the observer. The development process includes implementing the design using AIRBUS׳s the so-called SAO library which allows the automatic generation of flight certifiable code which can be implemented on the actual flight control computer. The proposed scheme has been subjected to various tests and evaluations on the Functional Engineering Simulator conducted by the industrial partners associated with the ADDSAFE project. These were designed to cover a wide range of the flight envelope, specific challenging manoeuvres and realistic fault types. The detection and isolation logic together with a statistical assessment of the FDD schemes are also presented. Simulation results from various levels of FDD developments (from tuning, testing and industrial evaluation) show consistently good results and fast detection times.