Fault Parameter Estimation Research Articles

Robust H∞ Fault-Tolerant Control for Linear Systems with Fast Adaptive Fault Estimation

The problem of adaptive fault-tolerant control for linear systems with time-varying actuator faults including outage and loss of effectiveness is investigated in this paper. After presenting a time-varying actuator fault model, a novel adaptive observer is designed so that the fault parameter can be estimated fast. Here, the inevitable fault estimation error, as well as the exogenous disturbance, is regarded as a part of the combined disturbance to be attenuated. Then, based on the Lyapunov stability theory and the estimated fault parameters, some sufficient conditions for designing the adaptive robust H∞ fault-tolerant controller are presented in the framework of linear matrix inequalities (LMIs), which can guarantee that the closed-loop system is asymptotically stable and robust for both time-varying fault and exogenous disturbance. Finally, the effectiveness and applicability of the proposed method is illustrated by a linearized longitudinal motion equation of the F-18 aircraft.

A GRAY-BOX NEURAL NETWORK-BASED MODEL IDENTIFICATION AND FAULT ESTIMATION SCHEME FOR NONLINEAR DYNAMIC SYSTEMS

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

A Novel Fault Diagnostics and Prediction Scheme Using a Nonlinear Observer With Artificial Immune System as an Online Approximator

In this paper, an observer-based fault diagnostics and prediction (FDP) scheme for a class of nonlinear discrete-time systems via output measurements is introduced by using artificial immune system (AIS) and a robust adaptive term. Traditionally, AIS was considered as an offline tool for system identification and pattern recognition whereas here AIS is utilized as an online approximator in discrete-time (OLAD) in a fault detection (FD) observer. A fault is detected when the output residual exceeds a predefined threshold. Upon detection, the OLAD is initiated to learn the unknown fault dynamics online while the robust adaptive term ensure asymptotic convergence of the output residual for a state fault whereas a bounded result for an output fault. Additionally, a mathematical equation is introduced to estimate the time-to-failure (TTF) by using the output residual and the estimated fault parameters. Finally, the performance of the proposed FDP scheme is demonstrated on an axial piston pump hardware test-bed.

Rapid Estimation of Fault Parameters for Tsunami Warning along the Mexican Subduction Zone: A Scenario Earthquake in the Guerrero Seismic Gap

Online Material: Color figures; synthetic‐data links. The devastating tsunami produced by the Sumatra–Andaman earthquake ( M w 9.2) of 24 December 2004 heightened the interest of the scientific community in tsunami early warning systems. Global efforts have been successful in achieving a robust ocean basin‐wide tsunami warning in which there is enough time to obtain accurate source parameters, determine the tsunami potential, model the tsunami propagation through the oceans, and update it with real‐time sea‐surface height observations. However, local systems are still not reliable. In such cases, rapid estimation of accurate source parameters that are expeditious in discriminating a tsunamigenic earthquake and its potential tsunami are essential. The 2011 Tohoku–Oki earthquake ( M w 9.0) revealed that tsunami‐warning techniques based on traditional seismic instrumentation could lead to an underestimation of the event magnitude (Ozaki, 2011), which can translate into tragic loss of life and infrastructure (e.g., Cyranosky, 2011). The Pacific coast of Mexico has been struck by at least 26 historic tsunamis originating from local subduction earthquakes (Sanchez and Farreras, 1993; Farreras, 1997). Tide‐gauge recording in Mexico began in 1952. Since then, the maximum height recorded is 3 m for the 1985 Michoacan earthquake ( M w 8.0). However, historic documents suggest that tsunamis as high as 8–11 m may have hit the Mexican Pacific coast during the Guerrero–Oaxaca earthquake of 28 March 1787, M w 8.4–8.6 (Sanchez and Farreras, 1993; Farreras, 1997; Nunez‐Cornu et al. , 2008; Suarez and Albini, 2009) and the Colima–Jalisco earthquake of 22 June 1932, M w 7.0 (Sanchez and Farreras, 1993; Farreras, 1997). An effective tsunami early warning system for the Mexican Pacific coast should be able to emit a reliable alert in less than 10 minutes, given that the peak in the tsunami height may reach the coast about 10–15 minutes after the …

Integrated Adaptive Fault-Tolerant H Infinity Output Feedback Control with Adaptive Fault Identification

An adaptive fault-tolerant H1 output feedback controller is designed for a linear system with actuator faults by incorporating an observer for actuator faults. This observer is improved from anunknown input observer tomake it more appropriate for tracking all fault parameters. The sufficient condition of the existence for this observer is provided. Then, the adaptive fault-tolerant H1 output feedback controller is proposed by using the estimated fault parameters. This controller can ensure the H1 performance of system and accommodate actuator faults simultaneously, but it requires solving nonlinear matrix inequalities. An implementation scheme is designed by translating the nonlinear inequalities to solvable linear matrix inequalities. Finally, the effectiveness of the adaptive H1 output feedback controller is validated by stabilizing a vertical takeoff and landing helicopter when its actuators suffer from faults.

Fault Tolerant Control Using Proportional-Integral-Derivative Controller Tuned by Genetic Algorithm

Problem statement: The growing demand for reliability, maintainability and survivability in industrial processes has drawn significant research in fault detection and fault tolerant control domain. A fault is usually defined as an unexpected change in a system, such as component malfunction and variations in operating condition, which tends to degrade the overall system performance. The purpose of fault detection is to detect these malfunctions to take proper action in order to prevent faults from developing into a total system failure. Approach: In this study an effective integrated fault detection and fault tolerant control scheme was developed for a class of LTI system. The scheme was based on a Kalman filter for simultaneous state and fault parameter estimation, statistical decisions for fault detection and activation of controller reconfiguration. Proportional-Integral-Derivative (PID) control schemes continue to provide the simplest and yet effective solutions to most of the control engineering applications today. Determination or tuning of the PID parameters continues to be important as these parameters have a great influence on the stability and performance of the control system. In this study GA was proposed to tune the PID controller. Results: The results reflect that proposed scheme improves the performance of the process in terms of time domain specifications, robustness to parametric changes and optimum stability. Also, A comparison with the conventional Ziegler-Nichols method proves the superiority of GA based system. Conclusion: This study demonstrates the effectiveness of genetic algorithm in tuning of a PID controller with optimum parameters. It is, moreover, proved to be robust to the variations in plant dynamic characteristics and disturbances assuring a parameter-insensitive operation of the process.

Extension on the Tibetan plateau: recent normal faulting measured by InSAR and body wave seismology

We use InSAR and body wave modelling to determine the faulting parameters for a series of five Mw 5.9–7.1 normal faulting earthquakes that occurred during 2008, including the March 20 Yutian earthquake (Mw 7.1), one of the largest normal faulting events to have occurred recently on the continents. We also study three earlier normal faulting earthquakes that occurred in southern Tibet between 1992 and 2005. Coseismic deformation for each of these eight events is measured with ascending and descending interferograms from ENVISAT, ERS and ALOS SAR data. Elastic dislocation modelling of the line-of-sight InSAR displacements and body wave seismological modelling of P and SH waves are used to estimate fault parameters and are found to be in good agreement for all the events studied. The use of InSAR to measure deformation allows a relatively precise determination of the fault location in addition to resolving the focal plane ambiguity. Only five of the eight events are associated with a clear surface topographic feature, suggesting that an underestimation of the amount of extension would result from using the surface expressions of normal faulting alone. The observations, in all cases, are consistent with slip on planar surfaces, with dips in the range 40–50°, that penetrates the uppermost crust to a depth of 10–15 km. We find no evidence for active low-angle (dip less than 30°) normal faulting. The contribution of the normal faulting to overall extension estimated by summing seismic moments over earthquakes for the past 43 yr is 3–4 mm yr−1, or 15–20 per cent of the rates of extension measured across the plateau using GPS. 85 per cent of the moment release in normal faulting over the past 43 yr has occurred in regions whose surface height exceeds 5 km. This observation adds weight to the suggestions that the widespread normal faulting on the plateau is the result of variations in the gravitational potential energy of the lithosphere.

Mode Identification of Hybrid Systems in the Presence of Fault

A mode identification method for hybrid system diagnosis is proposed. The method is presented as a module of a quantitative health monitoring framework for hybrid systems. After fault occurrence, the fault is detected and isolated. The next step is fault parameters estimation, where the size of the fault is identified. Fault parameter estimation is based on data collected from the hybrid system while the system is faulty, and its dynamical model is partially unknown. A hybrid system's dynamics consists of continuous behavior and discrete states represented by modes. Fault parameter estimation requires knowledge of the monitored system's operating mode. The new method utilizes the partially known dynamical model to identify hybrid system modes in the presence of a single parametric fault.

Modeling the strong ground motion and rupture characteristics of the March 31, 2006, Darb-e-Astane earthquake, Iran, using a hybrid of near-field SH-wave and empirical Green’s function method

We analyze the strong motion accelerograms of the moderate (Mw = 6.1), March 31, 2006, Darb-e-Astane earthquake of western Iran and also those of one of its prominently recorded, large (Mw = 5.1) foreshock and (Mw = 4.9) aftershock. (1) Using derived SH-wave spectral data, we first objectively estimate the parameters \(\mathit{\Omega} _{\rm o}\) (long period spectral level), fc (corner frequency) and Q(f) (frequency dependent, average shear wave quality factor), appropriate for the best-fit Brune ω − 2 spectrum of each of these three events. We then perform a non-linear least square analysis of the SH-wave spectral data to provide approximate near-field estimates of the strike, dip, and rake of the causative faults and also the seismic moment, moment magnitude, source size, and average stress drop of these three events. (2) In the next step, we use these approximate values and an empirical Green’s function approach, in an iterative manner, to optimally model the strong ground motion and rupture characteristics of the main event in terms of peak ground acceleration/velocity/displacement and duration of ground shaking and thereby provide improved, more reliable estimates of the causative fault parameters of the main event and its asperities. Our near-field estimates for both the main moderate event and the two smaller events are in good conformity with the corresponding far-field estimates reported by other studies.

A Nonlinear Hybrid Fault Detection, Isolation and Estimation using Bank of Neural Parameter Estimators

Abstract This paper presents two novel hybrid schemes for component fault diagnosis in a general nonlinear system. Unlike most fault diagnosis techniques, the proposed solution detects, isolates, and identifies the severity of faults in the system within a single integrated framework. The proposed technique is based on a bank of adaptive neural parameter estimators (NPE) and a set of parameterized fault models. At each instant of time, the NPEs provide estimates of the unknown fault parameters (FP) that are used for fault diagnosis. Two structures of NPE, namely series-parallel and parallel, are proposed with their respective fault isolation policies. While the series-parallel structure possesses fast convergence, the parallel scheme is extremely robust to measurement noise. Although, it has a more complex isolation policy, the parallel structure exhibits a more robust fault isolation capability. The parameter estimation for both architectures is based on an on-line minimization of instantaneous output estimation error. Simple network architecture and straightforward weight adaptation laws make our proposed technique appropriate for real-time implementation. Simulation results presented in this paper for detection, isolation, and identification of faults in nonlinear reaction wheel actuators of a 3-axis stabilized satellite in the presence of disturbances and noise demonstrate the effectiveness of our proposed fault diagnosis schemes.

Bicausal bond graphs for supervision: From fault detection and isolation to fault accommodation

Model-based fault detection and isolation (FDI) requires an analytical system model from which fault indicators can be derived by assigning proper computational causalities. Many bond graph (BG) model-based techniques for FDI have been developed in recent past. Furthermore, many other advances have been made in the field of control engineering applications of BG modelling. Supervision systems not only perform FDI, but also take the necessary steps for fault accommodation. Fault accommodation is done either through system reconfiguration or through fault tolerant control (FTC). In this paper, it is shown that bicausal BG modelling proves to be a unified approach for sensor placement from the FDI and FTC viewpoint, identification of hardware redundancies for system reconfiguration, generation of fault indicators, estimation of fault parameters for fault accommodation, inversion of systems and actuator sizing for FTC, etc. It is shown that the use of bicausalled BG helps to integrate many of the recently developed advances made in the field of control engineering into development of complex supervision systems.

A dense GPS observation immediately after the 2004 mid-Niigata prefecture earthquake

AbstractTo investigate the postseismic crustal deformation associated with the 2004 mid-Niigata prefecture earthquake (M6.8), we newly started GPS observation to fill a gap of the nationwide continuous GPS network. Our GPS sites were mainly distributed in the focal region without permanent GPS site, and succeeded in obtaining the postseismic deformation. Coseismic displacements of two aftershocks were clearly detected because of immediate observation. Estimated fault parameters of the aftershock (M5.9) on November 8 occurring just beneath our GPS network indicated that geodetic data could be explained by either east- or west-dipping fault model inferred from detailed aftershock data. Moreover, clear postseismic deformation, which could be characterized by a logarithmic decay function, was observed. This signal probably suggests possible aseismic slip. Our results indicated that dense GPS observation could give important and interesting data to clarify the properties of shallow inland middle-size earthquakes.

Effects of a soft surface layer on near-fault static and dynamic displacements

While detailed crustal structure around a damaged area is surveyed for source parameters obtained by seismic waveform inversions (e.g. the ‘damage belt’ of the 1995 Hyogoken-nambu earthquake in Japan), the effects of a layered medium are often not considered in practical analyses of geodetic data. In this study, we calculate static as well as dynamic displacements with the discrete wavenumber method and compare them with analytical as well as numerical solutions for a half-space. The existence of a soft surface layer is found to affect both the amplitude and the spatial distribution of static displacement near a fault, in a different manner from those of dynamic displacement. The largest effect of a surface layer is shown in the case of a vertical strike-slip fault. While dynamic motions are amplified monotonically with the thickness of the surface layer, the amplification of static displacement is limited if the surface layer reaches the top of the fault because the moment release there is then reduced. Errors in the estimation of the fault depth and the amount of slip reaches as large as 30 per cent of the true values in the worst case. Our results strongly suggest that a strong bias may be introduced to the conventional estimation of fault parameters, assuming a medium to be a half-space, from static displacement or geodetic data by the existence of a low-velocity or low-rigidity surface layer.

A Robust Method for Hybrid Diagnosis of Complex Systems

The AI model-based diagnosis community has developed qualitative reasoning mechanisms for fault isolation in dynamic systems. Their emphasis has been on the fault isolation algorithms, and little attention has been paid to robust online detection and symbol generation that are essential components of a complete diagnostic solution. This paper discusses a robust diagnosis methodology for hybrid systems that combines fault detection with a combined qualitative and quantitative fault isolation scheme. We focus on fault detection, symbol generation, and parameter estimation, and illustrate the effectiveness of this method by running experiments on the fuel transfer system of aircraft

Estimation of causative fault parameters of the Rudbar earthquake of June 20, 1990 from near field SH-wave data

We analyze the strong motion accelerograms recorded for the large (MS=7.7, MW=7.3, mb=6.4) Rudbar earthquake of June 20, 1990. The earthquake had a complex source process. We have identified the imprints of rupture of three localized asperities on the major causative fault on the accelerograms. These asperities are interpreted to correspond to (i) the main shock that initiated the rupture process and was located in the domino block between the Kabateh and Zard Goli faults, (ii) a foreshock that occurred about 10 s earlier in the Kabateh fault and (iii) a later shock, on the western end of the Baklor fault, which terminated the bilateral rupture process at the western end. We estimate the strike, dip and slip of these causative sub-event rupture planes using the SH spectral amplitudes, based on a point source representation of sub-events and a non-linear least square formulation for inversion of the amplitude data. The results of our inversion of the near field data are comparable to other studies based on teleseismic data.

Active fault-tolerant control system against partial actuator failures

A novel approach for integrated fault detection, diagnosis and reconfigurable control systems design against actuator faults is proposed. The scheme is based on a two-stage adaptive Kalman filter for simultaneous state and fault parameter estimation, statistical decisions for fault detection, and activation of controller reconfiguration. Using the information from the fault detection and diagnosis scheme, the reconfigurable feedback controller is designed automatically based on an eigenstructure assignment technique. To eliminate the steady-state tracking error, a reconfigurable feedforward controller is also incorporated using a command generator tracker technique. The following fault types and input signals are considered: abrupt and incipient, single, multiple and consecutive faults, constant and arbitrarily varying reference inputs. The effectiveness and the superiority of the proposed approach are demonstrated using an aircraft example.

An optimal retry policy based on fault classification

An optimal retry policy in a computer system is usually derived under the unrealistic assumption that fault characteristics are known a priori and remain unchanged throughout the mission lifetime. In such a case, the optimal retry period depends only upon the system's status at the time of fault detection. We propose to remedy this deficiency by formulating the optimal retry problem as a Bayesian decision problem where not only the time of fault detection but also the results of earlier retries are used to estimate the current fault characteristics. Previous knowledge about fault characteristics is represented by the prior distributions of fault-related parameters which are updated whenever new samples are obtained from retry and detection mechanisms. A new fault classification scheme is proposed to assign a temporal fault type (i.e. permanent, intermittent or transient) to each detected fault so that the corresponding fault parameters can be estimated. The estimated fault parameters are then used to derive the optimal retry period that minimizes the mean task completion time. Efficient algorithms are developed to determine the optimal retry period online upon detection of each fault. To evaluate the goodness of the proposed retry policy, it is compared with, and is always found to outperform, a number of fixed retry period policies.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Fault parameters and tsunami excitation of the May 23, 1989, MacQuarie Ridge Earthquake

The Macquarie Ridge earthquake of May 23, 1989, is one of the largest events in the last decade. Furthermore, it is the largest strike‐slip earthquake ever recorded instrumentally. We analyzed long‐period surface waves and body waves recorded at global networks (GDSN, IRIS, GEOSCOPE, and IDA) to estimate the fault parameters and computed tsunamis from the estimated parameters. The Centroid Moment Tensor (CMT) solution from surface waves shows that the mechanism is almost pure strike‐slip with one of the nodal planes parallel to the strike of the Macquarie Ridge. The seismic moment is 1.6 × 1021 Nm (× 1028 dyn·cm) and the corresponding moment magnitude is Mw =8.1. Teleseismic P and S waves from 10 stations with good azimuthal coverage are used to model the temporal and spatial distribution of the subevents. Four subevents are located sequentially from south to north along the ridge system in about 30 sec. All of them have a mechanism similar to the CMT solution. The fault length is estimated to be about 120 km from the subevent and the aftershock distributions. The rapture propagates from south to north at a relatively high speed. The average slip on the fault depends on the estimate of the fault width, but is probably larger than 9 m. A large strike‐slip earthquake like this event produces significant vertical displacements on the ocean bottom and excites tsunamis. Computation of tsunamis using the estimated fault parameters predicts that small tsunamis are expected at Australia and New Zealand. In fact, small tsunamis were observed on the southern coast of Australia.

A Bayesian approach to fault classification

According to their temporal behavior, faults in computer systems are classified into permanent, intermittent, and transient faults. Since it is impossible to identify the type of a fault upon its first detection, the common practice is to retry the failed instruction one or more times and then use other fault recovery methods, such as rollback or restart, if the retry is not successful. To determine an “optimal” (in some sense) number of retries, we need to know several fault parameters, which can be estimated only after classifying all the faults detected in the past. In this paper we propose a new fault classification scheme which assigns a fault type to each detected fault based on its detection time, the outcome of retry, and its detection symptom. This classification procedure utilizes the Bayesian decision theory to sequentially update the estimation of fault parameters whenever a detected fault is classified. An important advantage of this classification is the early identification of presence of an intermittent fault so that appropriate measures can be taken before it causes a serious damage to the system. To assess the goodness of the proposed scheme, the probability of incorrect classification is also analyzed and compared with simulation results.

Characteristics of the 1983 Tottori earthquake sequence and its relation to the tectonic stress field

Good azimuthal coverage of the 1983 Tottori Earthquake sequence provided an opportunity to analyze not only the main shock and aftershock, but also the causal relation between them. Source parameters of the main shock were calculated by the waveform analysis of strong motion seismograms. The fault relevant to the main shock was predominantly strike-slip. The estimated fault parameters are as follows; length 5 km, seismic moment 5.5 × 10 24, average displacement 50 cm and stress drop 3.9 MPa. The spatial distribution of aftershocks was generally consistent with the field of the maximum increase in shear stress after the main shock. Most aftershock sequences occurred in the regions with high maximum shear stress, but there were a few exceptions. Mechanisms of the aftershocks were investigated by comparing the maximum shear stress distribution with the direction of principal axes calculated theoretically from corresponding fault-plane solutions. The results indicate that an ambient tectonic stress is necessary to account for the observed mechanisms of aftershocks. The compressive tectonic stress acting in the Tottori area is estimated to be about 40 MPa or more, and to form an angle of 35–40° with respect to the strike of the fault of the main shock. Precise observations and analysis of the earthquake sequence are shown to be capable of estimating the tectonic stress in a seismotectonic.