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Analytical redundancy based fault detection of gyroscopes in spacecraft applications
Abstract
Spacecraft are generally designed with very high reliability to operate for many years through fault avoidance practices. But, in spite of fault avoidance, faults do occur. Hence there is a need for on-board fault detection and isolation without creating significant degradation in the spacecraft services. Analytical redundancy or model reference method of fault detection provides such a solution as most spacecraft are now equipped with an on-board computer, which is an ideal platform for implementing the analytical redundancy based fault detection algorithms.In this paper, analytical redundancy based fault detection technique has been applied for detecting the faults in gyroscopes used in a three-axis stabilized low earth orbiting satellite like the Indian Remote Sensing (IRS) spacecraft. The scheme proposed is an observer based on a dynamic model having attitude and rates as states and the gyro sensed rates and the horizon sensor outputs as measurements. The torque computed by the AOCS processor is used as the control input for this observer. Eigen-structure assignment approach has been applied to the design of this dedicated fault detection observer. Design exercise has been carried out using MATLAB tools. Spacecraft dynamics and kinematic equations, the models for gyroscopes and the other sensors, the on-orbit normal mode controller have been included in the simulations. Extensive simulation studies have been conducted to validate the design and the results are presented. It is believed that this approach will help in achieving the larger goal of autonomy in spacecraft.
... Most recently, signal processing techniques and analytical redundancies were used for dealing with the problem of the fault diagnosis for gyroscopes, e.g., a fault diagnosis scheme using independent component analyses was proposed in [3]. Reference [15] designed FDI observers via the eigenstructure assignment method. And FDI approaches based on Kalman filter were also reported in [4,14]. ...
... It can be seen that the descriptor state vectorx k in (18) and (19) is made up of x k and f k in (14) and (15). Therefore, if there exists an estimator for the plant (18) and (19), the estimates of the state vector x k and the sensor fault f k in (14) and (15) will be obtained simultaneously. ...
... The sensor fault f (k) in (15) is considered as the unknown input d k in [26], and then apply the unbiased minimum variance input and state estimation method to obtain the estimationd k for d k , i.e., the fault is reconstructed. For the discrete-time linear system (14) and (15), basic steps of the unbiased minimum variance input and state estimation method are described as follows [26]: ...
To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to estimate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.
... Considering the easy availability of ACS mathematical models and the scarcity of flight history data, model-based fault diagnosis methods occupy the majority of the research, particularly, the methods for diagnosing by establishing observers have attracted wide attention [3]. For example, in [4], an actuator fault diagnosis method was studied for the design of corresponding observers for satellite attitude control systems. In [5], the fault-tolerant control of a flight control system under sensor/actuator failure is accomplished using the Kalman filter technique and control reconstruction approach. ...
... The distance from the rocket's pneumatic centre to the top of the rocket xj 1 , xj 2 The two core engines zt 1 , zt 2 , zt 3 , zt 4 The four booster engines δ xj1 , δ xj2 , δ xj3 , δ xj4 ...
For the launch vehicle attitude control problem, traditional methods can seldom accurately identify the fault types, making the control method lack of pertinence, which largely affects the effect of attitude control. This paper proposes an active fault tolerant control strategy, which mainly includes fault diagnosis and fault tolerant control. In the fault diagnosis part, a small deviation attitude dynamics model of the launch vehicle is established, Kalman filters with different structures are designed to detect and isolate faults through residual changes, and the fault quantity of the actuator is further estimated. In the fault tolerant control part, the following control scheme is adopted according to the above diagnostic information: when the sensor fault is detected, the sensor measurement data is reconstructed; when the actuator fault is identified, the control allocation matrix is reconstructed. Simulation results show that the proposed method can effectively diagnose sensor fault and actuator faults, and significantly improve attitude tracking accuracy and control adjustment time.
... atellite pointing accuracy is one of the main requirements the achievement of which depends on the desired and un-faulty performance of the attitude determination and control system (ADCS). On the other hand, exposure to space radiations and inaccessibility of them make the fault event in this subsystem be inevitable [1]. Investigation of the fault event cases in different missions demonstrates that fault occurrence in sensors and actuators have led to the degradation or loss of the mission [2]. ...
... In [15] a robust UKF is used which provides a more effective convergence of the state estimation error. In Indian Remote Sensing (IRS) satellite, the scheme proposed is an eigen structure assignment technique based on a dynamic model having attitude and rates as states and the gyro sensed rates and the horizon sensor outputs as measurements [1]. In [16], a fault diagnosis technique has been proposed based on a nonlinear Predictive Filter (PF) that estimates the modeling errors and uses them to correct the estimate of the system states. ...
This paper presents a new scheme for fault detection in satellite Attitude Determination (AD) sensors. The proposed method is based on derivation of all possible relations which result in Euler angles and comparison of these angles provided by them. Accordingly, significant changes in the distribution of Euler angles set, is used as a benchmark for fault detection. The features which have been achieved by this philosophy make it possible to provide an analytical approach for fault detection without imposing any additional sensors, mass, power consumption and costs. Also, the outlined method is a free-model based approach which allows combination of this algorithm with the model-based algorithms utilized in the attitude control subsystem. So it provides the detection of sensor faults independent of the actuators situations. The numerical simulations presented in this paper demonstrate the accuracy and robustness of the designed algorithms.
... To avoid these problems, analytical redundancy approaches are considered. Most of these approaches are relied on the generation of the residuals by the Kalman Filters (KF), using of the eigen structure assignment techniques or sensor fault estimation by different types of observers [3][4][5][6][7][8]. In [3] two Kalman Filters have been used for fault detection that are based on measured outputs from gyros, sun sensor and magnetometer. ...
... The authors of [6] have suggested a robust unscented Kalman Filter which provides a more effective convergence of the state estimation error. In Indian Remote Sensing (IRS) satellite, an eigen structure assignment technique has been used for fault detection of gyros [7]. Another category of fault detection mechanisms are observer based methods that have been used extensively for fault detection purposes [8]. ...
This paper presents a new scheme for fault detection in satellite Attitude Determination (AD) sensors. The proposed method is based on derivation of all possible rotations between orbital and body frames and comparison of Euler angles provided by them. Accordingly, significant variations in the variance of the obtained Euler angles sets utilized as a benchmark for fault detection. The features which have been achieved by this philosophy make it possible to provide an analytical approach for fault detection without imposing of any additional sensors, mass, power consumption and costs. Also, the outlined method is a model-free based approach which allows combination of this algorithm with the model-based algorithms that used in the attitude control subsystem. So it provides the detection of sensor faults independent of the faulty conditions of actuators. The numerical simulations presented in this paper demonstrate the accuracy and robustness of the designed algorithms. Also, designed algorithms are implemented using the hardware in the loop test bed together with manufactured space sensors to evaluate their functions in a practical situation.
... It is well known from the literature that gyroscopes can be applied in a lot of technological applications, such as in systems of localisation on Earth (GPS) [1][2][3], in electronic games [4,5], in systems of navigation [6], and other cases, based on the physical properties related to the inertia of such devices. Besides, there is much interest in the research for new and more modern applications. ...
We performed several measurements of anomalous forces on a dielectric rotor under electrostatic operation conditions. The device operated under constant and intense angular velocity for each high voltage applied. The measurements were made in a similar way to an analogue magnetic gyroscope, by considering clockwise and counterclockwise rotations. We found that there is significant weight reduction on the device in the clockwise case, one order of magnitude higher than in the magnetic case. In addition, we detected a similar asymmetry in the observation of the effect, that is, there are smaller results for the anomalous forces in counterclockwise rotation for higher values of the voltage applied on the device. We also propose a theoretical model to explain the quantitative effect based on average values of macroscopic observables of the device rotation and concluded that it is consistent with the experimental findings.
... It is well known from literature that gyroscopes can be applied in a lot of technological applications, as in systems of localization on Earth (GPS) [1][2][3], in electronic games [4,5], in systems of navigation [6] and other cases, based on the physical properties related to the inertia of such devices. Besides, there is much interest in the research for new and more modern applications. ...
We performed several measurements of anomalous forces on a dielectric rotor in operation, subjected to high voltage. The device operated under constant and intense angular velocity for each high voltage applied. The measurements were made in the similar way than an analogue magnetic gyroscope, by considering clockwise and counterclockwise rotations. We found that there are significant weight reduction on the device in the clockwise case, with one order of magnitude higher than the magnetic case. In addition, we detected a similar asymmetry in the observation of the effect, that is, there are smaller results for the anomalous forces in counterclockwise rotation. We also propose a theoretical model to explain the quantitative effect based on average values of macroscopic observables of the device rotation and concluded that it is consistent with the experimental results.
... Due to the diversity, complexity, and harsh working environment of a spacecraft in orbit, the key components of the ACS inevitably experience faults. The faults will not only affect the performance of attitude control system, but even cause casualties and economic losses [1]. Therefore, the fault diagnosis of spacecraft ACSs has attracted significant attention and extensive research [2][3][4][5][6][7]. ...
In this paper, a novel multiple-fault diagnosis (MFD) scheme using radial basis function neural network (RBFNN)-based observers is presented for a spacecraft attitude control system (ACS) in the presence of external disturbances and nonlinear uncertainties. Based on dynamic and kinematic models, robust fault detection observers (FDOs) are designed to detect the simultaneous occurrence of actuator, gyro, and star sensor faults. Then, a series of RBFNN-based fault isolation observers (FIOs) are designed to decouple the faults of different components completely. This complete decoupling will guarantee that the diagnosis result of one component is not affected by the faults of other components; thus, multiple faults can be diagnosed simultaneously. To improve the accuracy of fault detection and reconstruction, disturbance compensation observers (DCOs) based on the RBFNN are also designed to compensate for the external disturbances. It is worth noting that the developed fault diagnosis scheme can be used to detect and isolate small faults. Finally, simulation results are presented to show the effectiveness and feasibility of the proposed method.
... Due to the diversity, complexity, and harsh working environment of a spacecraft in orbit, the key components of the ACS inevitably experience faults. The faults will not only affect the performance of attitude control system, but even cause casualties and economic losses [1]. Therefore, the fault diagnosis of spacecraft ACSs has attracted significant attention and extensive research [2][3][4][5][6][7]. ...
... For instance, sole thruster and RW faults were studied in Fonod et al. (2015b) and in Meskin and Khorasani (2007), respectively. Gyroscope sensor faults were studied in Venkateswaran et al. (2002). Only very few examples of model-based FDI systems dealing with a combination of different type of actuators or sensors exist for agile spacecraft. ...
Fast and large-angle attitude slew maneuvers often imply simultaneous use of multiple actuators such as thrusters and reaction wheels (RWs). A fault in any of these actuators might lead to partial or full damage of sensitive spacecraft instruments. In this paper, a model-based Fault Detection and Isolation (FDI) strategy is proposed, which aims at detecting various actuator faults, such as stuck-open/closed thruster, thruster leakage, loss of effectiveness of all thrusters, and change of RW friction torque due to change of Coulomb and/or viscosity factor. The proposed FDI strategy is also able to detect and isolate faults affecting the RWs tachometer sensor. The FDI system design is based on a multiplicative extended Kalman filter and a generalized likelihood ratio thresholding of the residual signals. The performance and robustness of the proposed FDI strategy is evaluated using Monte Carlo simulations and carefully defined FDI performance indices. Preliminary results suggest promising performance in terms of detection/isolation times, miss-detection/isolation rates, and false alarm rates.
... These meth- ods are mostly model-based approaches [4]. Model-based sensor fault detection methods could be categorized based on the sensor type; 1) Methods that fo- cus on angular rate sensors fault such as those on eigen structure assignment 20 technique [5], parity equation [6], and independent component analysis [7]. 2) ...
This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.
... Eigen structure assignment techniques propose another alternative for fault detection based on residual generation. In [9], an Eigen structure assignment technique has been used for fault detection of gyros in the Indian satellite named IRS. Residual generation in this approach can be accomplished such that the fault isolation between different sensors becomes possible. ...
This paper presents fault detection and isolation (FDI) algorithms for attitude determination system (ADS) of a satellite including a sun sensor and a magnetometer. The suggested methodology is based on derivation of all possible rotations between reference and body frames and computation of Euler angles by them. Using the resulted Euler angles, some variance measures have been derived that offer a solution for analytical model-free fault detection mechanism. Consequently, when significant variations occur in these variances a fault occurrence is declared. It is shown that by properly categorizing the Euler angles computation methods, not only the faulty sensors but also their faulty components could be isolated. Based on the mentioned feature, four steps of fault isolation have been proposed. In the first step, fault occurrence in only one component of a sensor is isolated. In the second step, two faults in two different sensors are investigated. In the third step, two faults in one sensor are evaluated that means a high level of failure in the sensor. Finally, if fault does not belong to the above categories, it means that more than 50% damage has been occurred in the ADS hardware. Through extensive simulation studies, the desired performance and accuracy of the outlined methods have been demonstrated.
... Many approaches have been proposed to overcome the aforementioned problems [9][10][11][12][13]. Among them, the analytical redundancy method is particularly effective. ...
The aim of this paper is to present a sensor fault-tolerant control (FTC) scheme for a two-axis fast steering mirror (FSM) system with minimum power consumption and without changing the controller structure. In this paper, an adaptive PI-based sliding mode observer (APISMO) is adopted firstly to estimate the fault signal, which does not require any prior knowledge of the fault. The estimation is then used by the fault isolation logic to identify the fault. The redundant sensor would be powered up to replace the faulty one when faults occur. During the backup sensor booting up, for maintaining the normal performance of the closed-loop system approximately, a fault-free estimation of the position provided by the APISMO is used as feedback signal. Experimental studies on a prototype system show that the proposed APISMO can effectively reconstruct the fault signals even when the two primary position sensors are faulty simultaneously. Meanwhile, the effectiveness and performance of the proposed scheme have been verified.
... In addition it involves some hardness and intricacy in practical applications to design and confirm a proper the filter gain matrix of fault detection. In reference [2] based on the satellite kinematic and dynamic models a fault detection observer is designed to diagnose faults from the gyros of a three-axis-stabilized and low-orbit satellite through the eigenstructure assignment way. An extended Kalman Filter to determine the satellite attitude and identify faults from gyros, star sensors, thrusters is designed in reference [3] and a filter with strong robustness for the process noise is demonstrated in the simulation results. ...
Based on the traditional method of analytical redundancy fault diagnosis, the advanced machine learning technology is combined with the model-based fault diagnosis so as to form a new intelligent approach to the fault diagnosis for satellite control systems. The support vector regression technique in statistical learning theory is employed to model the control system with a little sampling data firstly. Then the feasibility of detecting and identifying faults for the satellite attitude control system with the Mahalanobis distance is analyzed in detail. Finally a set of fault-detection observers are designed and implemented based on the residual evaluation. The simulation result indicates that the diagnosing method proposed in this paper is characterized with light computation burden and good real-time performance.
... The concept of analytical redundancy has been investigated in the context of aerospace applications, primarily utilizing Eigen-structure theory (Patton et al [1986]). However, most of these articles were aimed at isolated subsystems in an aircraft or a spacecraft (Venkateswaran et al [2002], Zolghadri et al [1998], Suzuki et al [1999], Dong et al [1996], Kelly [1996]). Fly-By-Wire (FBW) systems are mostly based on full hardware redundancies. ...
This paper presents a nonlinear observer and prediction based analytical redundancy for a Steer-By-Wire (SBW) system. A Sliding Mode Observer was designed to estimate the vehicle steering angle by using the combined linear vehicle model, SBW system, and the yaw rate feedback. The estimated steering angle along with the current input was used to predict the steering angle at various prediction horizons via a long range prediction method. This analytical redundancy methodology was utilized to reduce the total number of redundant road-wheel angle (RWA) sensors, while maintaining a high level of reliability. The Fault Diagnosis algorithm was developed using a majority voting scheme, which was then used to detect faulty sensor(s) in order to maintain safe drivability. The proposed observer-prediction based fault detection algorithms as well as the linearized vehicle model were modelled in MATLAB-SIMULINK. Two different fault types were used to evaluate the effectiveness of the proposed algorithms: persistent, and incipient faults. Simulation results show that the faulty sensor identification time decreases with the increase of prediction horizon illustrating advantages of the predictive analytical redundancy based algorithms against single point faults.
... A fault detection method based on eigenstructure assignment for gyroscopes is presented in the study of Venkateswaran et al. 12 Wang et al. 14 have proposed an adaptive fault diagnosis observer for the satellite attitude control system. Fault detection and estimation methods using the approximation ability of neural networks have been developed in other studies. ...
This article proposes an indirect approach for fault diagnosis and fault-tolerant control in the satellite attitude control system with sampled-data measurements. The proposed method is based on a discrete-time approximation model of the continuous attitude dynamics. By considering the fault term as an auxiliary state vector, an augmented plant is constructed. Then an observer is designed to simultaneously estimate the system state vector and the fault term. Specifically, the observer design problem is reformulated as a set of linear matrix inequalities and can be conveniently solved by standard linear matrix inequality tools. The fault-tolerant controller is easily derived using the fault diagnosis result and the H-infinity index is adopted to analyze the fault-tolerant control performance. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed method.
... High hardware redundancy increases the weight and cost of a satellite system. Thus, software redundancy is a more efficient choice for satellites (Venkateswaran et al. 2002). Development of fault detection, isolation and recovery algorithms has received a lot of attention in the past two decades. ...
The simulator development for fault detection and isolation (FDI) of a LEO satellite is presented. The simulator was constructed using satellite dynamics, FDI, sensors and actuators, flight software and a visualization block. Two FDI algorithms were applied. The first was an outlier detection method. The outlier detection method was based on the Kalman filter incorporating thresholds, data windows and average methods. This filter detected, isolated and recovered sudden abnormal data. The second FDI algorithm was a parity space approach for the gyro sensor FDI. The simulator was developed under the Matlab/Simulink environment. The results indicated that the simulator can be used for any LEO satellite
... [2001]), the fault detection observerbased approaches (Jensen andWisniewski [2002], Patton et.al. [2006], Venkateswaran [2002] ) and the optimal filtering methods (Castro et.al. [2006], Henry [2008]), the overall gain of the obtained fault diagnosis schemes is not so well clear and defined (see for instance the interesting discussions in Osder [1999] and Bonfe et.al. ...
This paper presents a formalized isolation technique for multiple and simultaneous failure diagnosis in the orbiter measurement unit during the rendezvous phase of the Mars Sample Return (MSR) mission. The MSR mission is a spacecraft mission whose aim is to bring tangible samples from Mars to Earth for analysis. The proposed methodology aims at combining judiciously available hardware redundancy-based fault indicating signals with analytic-based fault indicating signals. Within this topic, the problem of finding the minimal number of residuals for a given isolation task, is addressed. To cope with the diagnosis problem, logical tools derived from the set theory are used. Simulation results are presented in order to show the effectiveness of the proposed method.
... In the aerospace field, different model-based FDI techniques have been considered in the past. In (Venkateswaran et al., 2002) the problem of gyroscopes faults is considered using a FDI observer combined with a residual weighting matrix. The proposed procedure involves eigenstructure assignment. ...
This paper addresses the fault diagnosis task of the satellite Microscope actuators. The considered faults are the Field Emission Electric Propulsion (FEEP) thrusters faults occurring when a thruster blocks itself or closes itself during operating. The proposed diagnosis scheme is based on the non-conservative residual generation scheme proposed in (Henry and Zolghadri, 2005a) for LTI uncertain systems under feedback control, combined with a post-residual auto-piloted filter. The proposed scheme is optimal in the sense that the effects that thrusters faults have on the residuals is maximized and the influence of both spatial disturbances and sensor noises, minimized, in the H∞/H_-norm sense.
... For this reason, a lot of different FDI techniques have been considered. In (Venkateswaran et al., 2002), a FDI observer combined with a residual weighting matrix is used to consider the gyroscopes faults problem, and the proposed design procedure involves eigenstructure assignment. Directional nonlinear observers are used to detect and isolate faults in small satellites' actuators in (Jensen and Wisniewski 2002); however, as it is outlined by the authors, there exist some conditions regarding the distribution functions of the disturbances and faults, which basically rely on rank conditions. ...
Driven by the satellite's features such as closed-loop, limited storage space and computing capacity constraint, a fault detection scheme based on the coprime factorization and Youla parameterization is proposed for the on-orbit satellite attitude control system. Based on the SISO dynamic of the satellite in pitch direction and the MIMO one in roll/yaw direction, the residuals equal to y(k)-ŷ(k) is generated by a simple computation using the plant input and control error signals without running the state observer in parallel, therefore the computing expense is reduced to a certain extent, and the related theorems are provided synchronously. Simulation results are presented to show the performance of the proposed fault detection algorithm.
... High hardware redundancy increases the weight and cost of a satellite system. Thus, software redundancy is a more efficient choice for satellites (Venkateswaran et al. 2002). Development of fault detection, isolation and recovery algorithms has received a lot of attention in the past two decades. ...
The simulator development for fault detection and isolation (FDI) of a LEO satellite is presented. The simulator was constructed using satellite dynamics, FDI, sensors and actuators, flight software and a visualization block. Two FDI algorithms were applied. The first was an outlier detection method. The outlier detection method was based on the Kalman filter incorporating thresholds, data windows and average methods. This filter detected, isolated and recovered sudden abnormal data. The second FDI algorithm was a parity space approach for the gyro sensor FDI. The simulator was developed under the Matlab/Simulink environment. The results indicated that the simulator can be used for any LEO satellite.
... Also, the problem of FDI for satellite nonlinear dynamics has been addressed using the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). 12,13 In Venkateswaran et al., 14 an Eigen structure assignment technique has been used for fault detection of gyros in the Indian satellite of IRS. Another category of FDI mechanisms are observer-based methods. ...
This article presents a fault tolerant attitude determination system for a three-axis satellite including a sun sensor and a magnetometer. The suggested methodology is developed based on all possible rotations between reference and body frames and computation of Euler angles by them. Using the resulted Euler angles, some variance measures have been derived that offer a solution for analytical model-free fault detection. It is demonstrated that by categorizing different computation methods, the contaminated measurement data could be isolated. Also, utilizing the methods in which the contaminated data are not used, we can continue to provide correct Euler angles. The cited features provide a fault tolerant attitude determination system that always generates the correct attitude angles for attitude control purposes. Since these algorithms are model-free, the fault detection and isolation in the attitude determination system is accomplished independent of the health status of actuators in the attitude control system. In this article, through extensive simulation studies, the desired performance and accuracy of the outlined methods are demonstrated.
Prognostic and health management (PHM) is an approach that allows real-time health monitoring of any system. With the advancement of Industry 4.0, which integrates updated technologies, such as the Internet of Things, artificial intelligence, and automation, to optimize the efficiency, productivity, and flexibility of manufacturing processes. PHM is critical for ensuring the dependability and availability of smart factory components, which due to continuous operation, are prone to wear and tear. This paper presents a comprehensive examination of the component level-based PHM in the smart factory. It introduces PHM, smart factory and its various subcomponents. Various aspects of PHM are discussed for robotic systems, sensors, electrical machines, and auxiliary components. The paper concludes with practical recommendations for researchers interested in implementing PHM in the smart factory.
This paper investigates the finite-time attitude tracking control problem of spacecraft with angular velocity sensor failures and actuator saturation. A model-free angular velocity observer is proposed first to reconstruct the unmeasurable angular velocity in finite time. Invoking the reconstructed information, a saturated finite-time attitude tracking controller is then designed via the fast terminal sliding mode control technique, while the Legendre polynomial-based neural network is incorporated to approximate the unknown nonlinear dynamics. The finite-time stability of the closed-loop attitude tracking system from the proposed observer and the controller is proved despite the external disturbances. The main feature of the proposed controller is that it can accomplish the attitude tracking maneuver without model and angular velocity information. Numerical and experimental results are presented to verify the effectiveness of the proposed scheme.
We study a fault detection problem in the context of Markovian Jump Linear Systems (MJLS). The major contribution of this paper is the design of a mode-dependent mixed H∞/H− Fault Detection Filter (FDF) under the MJLS formulation, which is obtained by solving a Linear and Bilinear Matrices Inequalities (LMI / BMI) optimization problem. As a secondary contribution, we present a simulation of the theoretical results using a Control Moment Gyroscope unit, which is extensively used as an actuator for attitude control of spacecraft and satellites. The attitude control of satellites is a class of problem that is within the framework of MJLS, since it allows us to model the loss of communication between the various components of the network system. Therefore, designing Fault Detection Filters under this framework provides reliable solutions. From the simulations results, it is possible to observe that the proposed mixed H∞/H− fault detection solution outperformed the approach using only the H∞ norm, showing that it could be a valuable alternative for the fault detection problem.
To achieve the safe, reliable autonomous operation of spacecraft, research on the fault diagnosis of control systems has attracted the attention of engineers and academicians throughout the aerospace field. Diagnosability can characterize the fault diagnosis capability of control systems. Connecting diagnosability analysis to the design of a spacecraft control system’s structure and diagnosis method can fundamentally improve the system’s fault diagnosis capability, improving the safety and reliability of autonomous spacecraft operation. In this paper, the diagnosability of spacecraft control systems is systematically studied from five perspectives: necessity, the current research status, the connotation, a novel index system and current development trends of diagnosability. First, the current status of spacecraft reliability analysis and reliability-based design is briefly reviewed, and existing problems are described, highlighting the advantages and importance of diagnosability research. Furthermore, the basic concepts of diagnosability are briefly introduced. By analyzing the current status of existing research on the diagnosability of both general and spacecraft control systems, the application scope of the diagnosability of spacecraft control systems is summarized. Moreover, the definition and influencing factors of the diagnosability of spacecraft control systems are presented to refine existing concepts, and a universal evaluation index system is proposed for the diagnosability of spacecraft control systems to further enhance the applicability of diagnosability evaluation and diagnosability-based design to spacecraft. Finally, the existing shortcomings and future development trends of diagnosability research for spacecraft control systems are discussed.
To improve the reliability of the attitude determination system with redundant gyroscopes, this article proposes a gyroscope fault accommodation method using a bank of dedicated Kalman filters. The redundant gyroscopes are divided into several groups and then a dedicated Kalman filter is designed for each group of gyroscopes. The residuals generated by the dedicated Kalman filters indicate the consistency levels between the measurements of the star sensor and the gyroscopes. Based on the estimation results provided by the Kalman filters, a fault accommodation method using online selection strategy is proposed to attenuate the effect of the fault. Numerical simulations are used to demonstrate the effectiveness of the proposed method.
In this paper, a supervisory algorithm for attitude determination sensors of a three-axis satellite is suggested to classify different fault types of this system. The presented solution is based on the computation of rotation matrices between the orbital and body frames. Using the Euler angles provided by these rotations, some variance measures are computed, which utilized as an analytical tool for the determination of faulty sensors and the related fault sources. According to the mentioned idea, it is shown that the fault sources could be categorized into four levels. Each level shows the fault extent and its criticality. To include the reliability aspects in this paper, a failure mode effect criticality analysis is conducted to determine different failure modes, which really occur in sensors. For this, the probability levels and the severity numbers were assigned to derive the critical ones. It is shown that most of the critical failure modes could be isolated by the proposed methods; in other words, the design process is based on real faulty scenarios that can improve the system reliability. Finally, by performing some numerical simulations, performance of the developed algorithms are validated.
This chapter presents briefly the motivations and the book outline. This book presents a number of advanced fault detection and diagnosis and reconfiguration technologies for aerospace vehicles. An attempt is made to develop useful solutions that can be relevant and viable candidates for future space and aeronautical systems. The presented techniques have been tested and validated on highly representative benchmarks, real flight data, or real-world aerospace systems. The examples presented in this book are taken mainly from four recent projects related to fault detection and diagnosis and fault-tolerant control and guidance of aircraft and space systems:
As signal monitoring method of ship borne radar's rate gyros is too single to fulfill the users, the real-time detection system is designed and realized. This system can help users to judge the gyros' working order more intuitively and quickly through real-time data acquisition and graphic processing. At the same time, real-time index test and correlation detection between the correlated signals are proposed innovatively to improve the detection efficiency. So this detection system has realized the functions of real-time signal detection and fault alarm for two pairs of rate gyros, and it helps to improve the efficiency of checking and maintaining gyros' reliability. The design of this detection system can contribute to automation design of ship borne radar's servo system.
This paper presents a scheme for satellite multi-sensor fault-tolerant attitude estimation. It can both detect a faulty sensor online and conduct fault tolerance in time. First, a satellite attitude estimator based on error states is presented as the unified filter algorithm, in which the filter state equation is built with the gyro model and satellite kinematics, and the measurement equations are built with angle sensors. Meanwhile, typical fault models of the angle sensors are given. Then, a fault-tolerant federated Kalman filter (FTFKF) scheme is designed. Its three sub-filters include the respective angle sensors and share the public gyro measurement. Under the sensor fault condition, a FTFKF can detect the faulty sensor by contrasting and analysing the dimensionless fault detection factors and then selectively fusing the sub-filters’ outputs to enable the satellite attitude determination accuracy to approach normal. The comparative analysis of simulation results in typical fault cases shows that the proposed satellite multi-sensor fault-tolerant attitude estimation scheme may achieve the expected fault-tolerant performance. It is promising for enhancing the reliability of satellite attitude determination and control systems.
This chapter is dedicated to techniques for ensuring fault tolerance in redundant aircraft sensors involved in computation of flight control laws. The objective is to switch off the faulty sensor and to compute a reliable (a.k.a. as “consolidated”) parameter using data from valid sensors, in order to eliminate any anomaly before propagation in the control loop. The benefit of the presented method is to improve the consolidation process with a fault detection and isolation approach when only few sources (less than three) are valid. Different techniques are compared to accurately detect any behavioral change of the sensor outputs. The approach is tested on a recorded flight dataset. This chapter is dedicated to fault detection and isolation of redundant aircraft sensors involved in the computation of flight control laws. The objective is to switch off the erroneous sensor and to compute a so-called consolidated parameter using data from valid sensors, in order to eliminate any anomaly before propagation in the control loop. We will focus on oscillatory failures and present a method for integrity control based on the processing of any flight parameter measurement in the flight control computer (FCC) like, e.g., anemometric and inertial data. One of the main tasks dedicated to the FCC is the flight control laws (FCL) computation which generates a command (position order) to servo-control each moving surface (see Fig. 5.1). The comparison between the pilot commands (or the piloting objectives) and the aircraft state is used for FCL computation. The aircraft state is measured by a set of sensors delivering, e.g., anemometric and inertial measurements that characterize the aircraft attitude, speed, and altitude. The data is acquired using an acquisition system composed by several dedicated redundant units (usually three). The FCC receives three redundant values of each flight parameter data from the sensors and must compute unique and valid flight parameters required for the FCL computation. This specific data fusion processing, called “consolidation,” classically consists of two simultaneous steps (Fig. 5.2): selection or computation of one unique parameter from the three available sources, and, in parallel, monitoring of each of the three independent sources to discard any faulty one. As a consequence, the consolidation allows reliable flight parameters computation with the required accuracy by discarding any involved failed source.
This paper presents a practical solution to achieve a fault tolerant attitude control system capable of Fault Detection and Diagnosis (FDD). The novelty of our proposed strategy is in the accurate modeling of satellite dynamics by the Takagi-Sugeno method. Based on this model, an adaptive observer has been utilized to achieve fault diagnosis in reaction wheels of the Attitude Control System (ACS). For this, the occurred faults in reaction wheels have been estimated using an adaptive algorithm which provides fault detection and identification abilities. Moreover, in this paper, a recovery algorithm has been utilized, combined with fault detection and identification algorithm, to provide an advanced decision support system. In this regard, for undertaking the remedial actions, a backstepping feedback linearization control law has been considered in which the estimated fault has been utilized. Accordingly, the boundedness of the attitude control error is guaranteed, despite actuators fault. The developed algorithms provide a significant degree of autonomy to effectively handle satellite operation in the presence of ACS faults, without the ground segment intervention. Through extensive simulation results, the designed algorithms are shown to be robust and accurate. Also, designed algorithms are assessed through hardware in the loop test bed to evaluate their functions in an experimental situation.
This paper proposes an actuator fault diagnosis approach based on unknown input observers for the attitude control system of satellite. More specifically, by considering an actuator fault as the unknown input vector, an unknown input observer is designed so that the residual is sensitive to the other faults while insensitive to the appointed one. In this work, the design of unknown input observer is formulated as a set of linear matrix inequality (LMI), which can be solved by the LMI toolbox conveniently. Finally, the proposed approach is applied to the satellite attitude control system. Simulation examples illustrate the presented method is able to detect and isolate the actuator fault effectively.
A novel fault diagnosis approach for gyroscopes in satellites is proposed in this paper. The fault diagnosis problem is transformed to calculation of numerical differentiation by using the concept of algebraic observable. Based on the satellite attitude kinematics equation, it is proved that the fault of gyroscopes is algebraic observable. And then the numerical derivatives of the measurement outputs of attitude sensors are approximated via high gain observers analyzed and designed by the Lyapunov stability theory. Since the fault of gyroscopes is algebraic observable and the numerical derivative of the measurement of attitude sensors is available, the gyroscope faults can be estimated directly. Finally, numerical simulations for several fault scenarios are conducted to verify the effectiveness of the fault diagnosis scheme. Simulation results demonstrate that the presented method can not only detect the occurence of faults, but also estimate their magnitudes.
The pre-processing method of blind source separation based on multifactor analysis is proposed to solve the blind source with noise. Firstly, the shortcomings of existing methods of blind source separation are point out after analyzing their principles. The multifactor analysis is introduced in blind source separation and the maximum likelihood estimate based on expectation maximum is used to estimate the common factor and random error. Finally the FastICA algorithm is used to separate BSS result. The validity and the advantage of this method are illustrated by an example.
This chapter is dedicated to space applications. Three application cases will be presented: an Earth observation satellite, a deep space mission and an atmospheric re-entry vehicle. The design method is based on H
∞
/H
−
tools and is associated with a suitable post-analysis process, the so-called generalized μ-analysis. It is shown that the resulting design/analysis procedure provides an iterative refinement cycle which allows the designer to get “as close as possible” to the required robustness/performance specifications and trade-offs. This chapter is dedicated to actuator fault detection and diagnosis in space applications. Fault tolerance in terms of control and guidance will also be discussed. The design method is based on H
∞
/H
−
and robust pole assignment tools. Three space applications will be studied:
The work presented in this thesis deals with the synthesis of algorithms for the diagnosis of simple and multiple faults. The main objective which is pursued is to design a fault diagnosis scheme by merging a minimum number of analytic redundancy with the available hardware redundancy. The main contribution of the proposed technique concerns the general architecture of the proposed diagnosis method. The originality of the research work is the combination of ideas and tools originated from two research communities : the FDI (Fault Detection and Isolation) community and the DX (Diagnosis) community whose foundations are derived from Computer Science and Artificial Intelligence fields. Hence, the fault detection problem (as well as the isolation task when structural constraints allow it) is solved by means of FDI techniques while the fault isolation problem is solved through the DX approaches, thus resulting in an aggregated methodology. The proposed method is divided in two steps. The first step deals with the construction of a mutually exclusive signature matrix. Hence, the problem of the minimal number of analytic redundancy relations (ARR), necessary for generating a diagnosis without any ambiguity, is treated. This problem is formalised as an optimized problem under constraints which is efficiently solved by means of a genetic algorithm. The second step concerns the generation of diagnoses. Thus, for an observed situation, the identification of conflicts results in the determination of the non satisfied ARRs for the given observation. The diagnoses are obtained by means an algorithm based on the concept of MNF (Maximal Normal Form) formulas. The main interest of this approach is its capacity to deal with the diagnosis of simple and multiple faults as well as the diagnosis of multi-modes faults (i.e., multiple types of faults) associated to each component of the system. Furthermore, it exists proofs on optimality both at a local level (proof of robustness/sensitivity) and at a global level (proof of minimal diagnoses). The proposed method is applied to the Mars Sample Return (MSR) mission. This spacecraft mission, undertaken jointly by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA), aims at returning tangible samples from Mars atmosphere and ground to Earth for analysis. The critical phase of the mission is the rendezvous phase between the sample container vehicle and the orbiter spacecraft. The research work aims at realising sensor fault diagnosis on the orbiter during the rendezvous phase of the mission. Simulation results from the MSR high fidelity simulator, provided by Thalès Alenia Space, demonstrate the feasibility and the efficiency of the proposed approach.
This paper proposes a novel fault diagnosis approach for the satellite attitude control system with flywheel faults. The key contributions include fault estimation by sparse approximation algorithm and diagnosis of multiple faults. In this paper, a Taylor series expansion is used to derive a fault estimation representation. Based on the sparse property of the faults, fault estimation is formulated as a sparse approximation problem and solved using the orthogonal matching pursuit (OMP) algorithm. Simulation results demonstrate the effectiveness of the proposed method.
This paper presents robust fault detection based on adaptive thresholds for a three axis satellite. For this purpose, first, the attitude control system (ACS) is described as a quasi linear parameter model that includes both bounded parametric modeling errors and measurement noises. Next, using the interval arithmetic tools, an interval linear parametric varying observer is designed to propagate the effect of satellite parametric uncertainties into the alarm limits. This idea enhances the robustness of fault detection system at the decision making stage. In other words, the adaptive thresholds are generated for evaluating the residuals. Obtained results show that the missing alarm rates are minimized by the developed method; also this approach detects small or incipient faults more effectively than the classical robust fault detection algorithms with constant thresholds. In the next part of paper, an isolation algorithm has been proposed using the fault tree approach. Also, an accommodation system has been designed based on reconfiguration of available actuators. Accordingly, after isolation of faulty reaction wheels using the developed fault tree library, the accommodation system turned them off and replaced the suitable magnetic tourqers instead of faulty reaction wheels. Therefore, despite occurrences of several failures in the ACS, attitude control error is kept limited.
This paper presents an integrated fault detection and diagnosis (FDD) scheme based on analytical redundancy for satellite attitude control systems (ACS). The faults of actuators, angular rate sensors and attitude sensors are all taken into account, and the nonlinear ACS considered is subject to both space disturbance torques and sensor uncertainties. The proposed scheme is developed in two phases. In the first phase, two nonlinear observers are designed, and based on the proposed strategy which called observer redundancy the fault source (actuators, angular rate sensors or attitude sensors) can be verified. In the second phase, two banks of fault isolation observers (FIOs) activated by the previous detection results are designed to perform the diagnosis within the fault part. The first bank of FIOs are obtained based on nonlinear unknown input observers to isolate the fault actuator and the second bank of FIOs are obtained based on nonlinear adaptive observers to isolate and estimate the fault of angular rate sensor. The effectiveness of the proposed scheme is simulated on a closed-loop satellite attitude control system with some typical faults of these components.
This paper deals with the problem of fault estimation for satellite attitude control system with typical component configuration. In order to understand sensor and actuator faults propagation in the attitude control system, we have built the overall system model firstly, which includes the attitude dynamics model, sensor measurement model, attitude determination model, controller model and the moment distribution model. The faults are then considered as unknown inputs and are estimated using a classical proportional-integral observer, more over constant or time-varying fault can be estimated. The proposed observer is derived as a solution of off-line Linear Matrix Inequality (LMI) conditions. Additionally, simulation results are presented to illustrate the efficiency of the proposed method.
This paper presents a novel observer-based analytical redundancy for a steer-by-wire (SBW) system. In order to achieve high level of reliability for a By-Wire system, double, triple, or even quadruple redundant sensors, actuators, communication networks, and controllers are needed. But this added hardware increases the overall cost of the vehicle. This paper utilizes a novel analytical redundancy methodology to reduce the total number of redundant road-wheel angle (RWA) sensors in a triply redundant RWA-based SBW system, while maintaining a high level of reliability. The self-aligning torque at road-tire interface due to the steering dynamics has been modeled as a function of the linear vehicle states. A full state observer was designed using the combined model of the vehicle and SBW system to estimate the vehicle body side slip angle. The steering angle was then estimated from the observed and measured states of the vehicle (body side slip angle and yaw rate) as well as the current input to the SBW electric motor(s). With at least two physical road-wheel angle sensors and the analytical estimation of the RWA value (which replaces the third physical sensor), a fault detection and isolation (FDI) algorithm was developed using a majority voting scheme. The FDI algorithm was then used to detect faulty sensor(s) in order to maintain safe drivability. The proposed analytical redundancy based fault detection & isolation algorithms and the linearized vehicle model were modeled in SIMULINK. Simulation of the proposed algorithm was performed for both single and multiple sensor faults. Simulation results show that the proposed analytical redundancy based fault detection and isolation algorithm provides the same level of fault tolerance as in an SBW system with full hardware redundancy against single point failures.
The satellite attitude control system is composed of measuring component, executing component and controller. When the satellite works in the space, the fault probability of optical sensors, inertial sensors, and the reaction flywheels is very high. Fault diagnosis for each subsystem is the premise to identify the cause of the malfunction and avoid the disaster, which can guarantee the safe and reliable running of the satellite. In this paper, a combined diagnosis approach based on observer redundancy is proposed to isolate the faults of optical sensors, inertial sensors and the flywheels. It solves a diagnosis problem that the common diagnosis method based on state estimation has difficulty in separating the input fault (actuator fault) and output fault (sensor fault) of the system. Then the attitude control system of earth-oriented three-axis stabilized satellite has been studied, and the fault isolation strategy for flywheel, gyro and star sensor based on observer redundancy is given. Finally, the results of simulation show that this method can accurately diagnose the faults of the three key components and proved effectiveness of the combined diagnosis method based on observer redundancy.
Microscope is a satellite due to be launched in March 2008 (Microscope is undertaken jointly by the Centre National d'Etudes Spatiales, France, the ESA, the Office National d'Etude et de Recherche en Aerospatial, France, and the Cote d'Azur Observatory, France). It has the mission of testing the equivalence principle, which postulates the equality between gravitational mass and inertial mass. This paper addresses the fault diagnosis task of the Microscope thrusters. The faulty situations correspond to thrusters blocking themselves and/or closing when in operation. Two model-based diagnosis schemes based on H-infinity/H- filters are proposed and compared with each other in terms of performances and complexity. Nonlinear simulations show that both schemes are able to detect and isolate faults, despite the presence of measurement noises, measurement delays, sensor misalignment phenomena, and disturbances (i.e., third-body disturbances, J(2) disturbances, atmospheric drag, and solar radiation pressure).
This paper deals with the problem of robust fault detection and isolation (FDI) in dynamic systems using analytical redundancy. In order to reduce the effect of process parameter variations, two novel observer schemes for FDI are described. The first makes use of nonlinear observers in order to avoid parameter variations that would be caused by a linearization of the nonlinear process model in the observer scheme. The second considers robust observers that are totally invariant to unknown inputs or parameter variations. The achievements of the resulting FDI schemes are demonstrated by two examples of application, a level control system in a three tank system and a position control system of an inverted pendulum.
A set of seven unique parity equations (linear dependence relationships)
are derived for an octahedron inertial measurement unit (IMU) having six
skew-redundant sensing axes. Single and dual axis gyro failure detection
and isolation (FDI) algorithms, utilizing the parity equations, are
evaluated for a typical earth launch to geosynchronous orbit mission.
The IMU implemented with single degree-of-freedom gyros had better FDI
characteristics but was relegated in favor of the more cost effective
IMU with two degree-of-freedom gyros. A life cycle cost analysis showed
that to be more cost effective the latter IMU was required to yield an
FDI probability greater than 0.98 with false alarm rate less than 0.001.
This capability was verified by Monte Carlo simulation.
A closed-loop observer that can identify states and inputs simultaneously is developed for linear time-invariant systems with unknown inputs. The necessary and sufficient conditions for the existence of the observer are derived and proved. Parameter identification of a system with a few unknown or time-varying parameters is investigated by applying the observer technique developed in this paper. Potential usage in machine monitoring (machine diagnostics) appears promising.
Spacecraft perform a variety of useful tasks in our day-to-day life. These are such that spacecraft need to function properly without interruptions for 7 to 15 years in space without any maintenance. Though most spacecraft have redundant systems to serve as back-ups in case of failures, they greatly depend on human assistance through ground stations for failure analysis, remedial actions and redundancy management, resulting in itnerruption in services rendered. There is, therefore, need for a fault-tolerant system that functions despite failures and takes remedial action, without human assistance/intervention, autonomously on board the spacecraft.
Commonly used techniques for fault-tolerance in computers cannot be directly used for fault-tolerance in sensors and actuators of a closed loop control system. Further, for space applications fault-tolerance needs to be achieved without much penalty in weight and computational requirements.
This paper describes briefly the attitude control system (acs) of a spacecraft and highlights the essential features of a fault-tolerant control system. Schemes for fault tolerance in sensors and actuators are presented with an analysis on various failure modes and their effects. Newly developed fault-detection, identification and reconfiguration (fdir) algorithms for various elements ofacs are described in detail. Also an optimum symmetrically skewed configuration for the attitude reference system using dynamically tuned gyros is developed.
Some of the schemes have already been used in Indian Spacecraft. As future Indian space missions will directly cater to various applications on an operational basis, the ultimate objective is to have a totally fault-tolerant ‘intelligent’ autonomous spacecraft.
Model-based Monitoring (MBM) systems based on state observer theory are attractive for machine monitoring because practical, inexpensive, and reliable sensors can be located remote to the signal(s) of interest. Then, a model of the machine plus an estimation algorithm convert the output of the remote sensors to signals representing the desired local behavior. While this type of monitoring system has shown much promise in the laboratory, it has not been widely accepted by industry because, in practice, these systems often have poor performance with respect to accuracy, bandwidth, reliability (false alarms), and robustness. In this paper, the limitations of the deterministic state observer are investigated quantitatively from the machine monitoring viewpoint. The limitations in the transient and steady-state observer performance are quantified by the estimation error bounds, and from these error bounds performance indices are selected. Then, based on the relationships between the indices, a main index is determined in order to represent the overall observer performance. This index could form the basis for an observer design methodology that should improve the performance of model-based monitoring systems.
A new scheme for robust estimation of the partial state of linear time-invariant multivariable systems is presented, and it is shown how this may be used for the detection of sensor faults in such systems. We consider an observer to be robust if it generates a faithful estimate of the plant state in the face of modelling uncertainty or plant perturbations. Using the Stable Factorization approach we formulate the problem of optimal robust observer design by minimizing an appropriate norm on the estimation error. A logical candidate is the 2-norm, corresponding to an H¿ optimization problem, for which solutions are readily available. In the special case of a stable plant, the optimal fault diagnosis scheme reduces to an internal model control architecture.
In this paper we survey a number of methods for the detection of abrupt changes (such as failures) in stochastic dynamical systems. We concentrate on the class of linear systems, but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity vs performance are discussed.
Problems of designing fault detection and identification filters in the frequency domain are formulated and solved. Using the factorization approach a characterization of all fault detection filters is derived. This enables the derivation of necessary and sufficient conditions for the existence of fault identification as well as detection and isolation filters. It is shown that these conditions are a generalization of existing results. The formulas of constructing the filters are also derived. In comparison with the algorithms given in previous work they are computationally straightforward and simple. Finally, the proposed method for designing fault identification filters is extended so that more practical cases can be handled.
Robust eigen value/vector selection in a linear state feedback system
- Srinath Kumar
Srinath Kumar, S., Robust eigen value=vector selection in a linear state feedback system. Proceedings of the 27th IEEE Conference on Decision and Control, Austin, TX. 1988, pp. 1303–1307.
Fault-tolerance in spacecraft systems
- P S Goel
- N Venkateswaran
Goel, P. S., Venkateswaran, N., Fault-tolerance in spacecraft systems. IAF Congress, 1997.