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4 pages, 172 KiB

Open AccessEditorial

Editorial for Special Issue: Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft

by Yuehua Cheng, Qingxian Jia, Guang Jin and Yuqing Li

Appl. Sci. 2023, 13(13), 7791; https://doi.org/10.3390/app13137791 - 1 Jul 2023

Cited by 1 | Viewed by 1030

Abstract

In order to complete the various tasks in advanced space missions, such as communication, navigation, and remote sensing, single complicated spacecraft and many distributed spacecraft systems have been launched into orbit [...] Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

Research

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13 pages, 3156 KiB

Open AccessArticle

Fault Reconstruction for a Giant Satellite Swarm Based on Hybrid Multi-Objective Optimization

by Guohua Kang, Zhenghao Yang, Xinyu Yuan and Junfeng Wu

Appl. Sci. 2023, 13(11), 6674; https://doi.org/10.3390/app13116674 - 30 May 2023

Cited by 2 | Viewed by 1188

Abstract

To perform indicator selection and verification for the on-orbit fault reconstruction of a giant satellite swarm, a hybrid multi-objective fault reconstruction algorithm is proposed and then verified by Monte Carlo analysis. First, according to the on-orbit failure analysis of the satellite swarm, several [...] Read more.

To perform indicator selection and verification for the on-orbit fault reconstruction of a giant satellite swarm, a hybrid multi-objective fault reconstruction algorithm is proposed and then verified by Monte Carlo analysis. First, according to the on-orbit failure analysis of the satellite swarm, several optimization indicators, such as the health state of the satellite swarm, the total energy consumption of reconstruction, and the balance of fuel consumption, are proposed. Then, a hybrid multi-objective fitness function is constructed, and a hybrid multi-objective genetic algorithm is used to optimize the objective function to obtain the optimal reconstruction strategy. Finally, the algorithm is statistically verified by Monte Carlo analysis. The simulation results not only show the algorithm’s validity but also reveal the relationship between the number of satellite faults and the health of the satellite swarm. From this, the maximum number of faulty satellites allowed in the giant satellite swarm is calculated, which is significant for assessing the swarm’s health. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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21 pages, 5190 KiB

Open AccessArticle

State Observer Based Robust Backstepping Fault-Tolerant Control of the Free-Floating Flexible-Joint Space Manipulator

by Limin Xie and Xiaoyan Yu

Appl. Sci. 2023, 13(4), 2634; https://doi.org/10.3390/app13042634 - 17 Feb 2023

Cited by 7 | Viewed by 1764

Abstract

Actuator failure and joint flexibility will dramatically impact space robot system control. In this paper, free-floating flexible-joint space-manipulator dynamic-modeling is studied and a state-observer-based robust backstepping fault-tolerant control is proposed for the system joint actuator failure. Based on the flexible-joint simplified model, the [...] Read more.

Actuator failure and joint flexibility will dramatically impact space robot system control. In this paper, free-floating flexible-joint space-manipulator dynamic-modeling is studied and a state-observer-based robust backstepping fault-tolerant control is proposed for the system joint actuator failure. Based on the flexible-joint simplified model, the system’s rigid-flexible coupled-dynamic equations are established according to momentum conservation, angular momentum conservation, and the Lagrange equation. Then the system is decoupled based on the singular perturbation method. For the slow subsystem, a robust backstepping fault-tolerant controller base on a state observer is designed to eliminate the angle error, compensate for the uncertain parameter and the external disturbance, and achieve the joint-trajectory asymptotic-tracking. The use of a speed filter makes it inappropriate to measure and provide feedback about the system’s velocity signals, so the controller is simpler and more precise. For the fast subsystem, a velocity differential-feedback control is adopted to suppress the system vibration caused by the flexible joint, to ensure the stability of the system. Finally, the feasibility and effectiveness of the model and control method are proved by some simulations. The simulation results indicate that the proposed fault-tolerant control method can make the free-floating flexible-joint space manipulator system track the desired trajectory accurately and steadily, regardless of whether the actuator fails or not. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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27 pages, 7851 KiB

Open AccessArticle

Experimental and Numerical Study on Stress Distribution Characteristics of Traveling Wave Resonance of High-Speed Bevel Gear in Aero-Engine

by Xiaochi Luan, Yuhan Gao, Zhenpeng Zhang, Yundong Sha and Gongmin Liu

Appl. Sci. 2023, 13(3), 1814; https://doi.org/10.3390/app13031814 - 31 Jan 2023

Cited by 4 | Viewed by 1926

Abstract

Gear failure caused by traveling wave resonance (TWR) generally occurs quite suddenly and causes catastrophic results in aero-engines. In this study, the TWR characteristics and stress distribution characteristics of a high-speed bevel gear in an aero-engine are analyzed in detail by means of [...] Read more.

Gear failure caused by traveling wave resonance (TWR) generally occurs quite suddenly and causes catastrophic results in aero-engines. In this study, the TWR characteristics and stress distribution characteristics of a high-speed bevel gear in an aero-engine are analyzed in detail by means of experiments and simulations. Based on the acoustic waveguide system and dynamic stress test system, the TWR fatigue failure monitoring experiment of the central drive bevel gear in an aero-engine is carried out, and the TWR frequency, dangerous speed, dynamic stress and fatigue fracture characteristics of a driven bevel gear are obtained. Based on the transient dynamic analysis method and Hertz contact theory, the stress distribution characteristics of the driven bevel gear, which cannot be obtained in the test under the condition of TWR, are analyzed. The influence of the changes in the working temperature and the thickness of the spoke on the TWR characteristics and the stress distribution characteristics are discussed. The simulation and test results show that the gear has the problem of stress concentration at the root of the tooth and the back of the spoke plate under the 4th node-diameter (ND) TWR, and the stress distribution form is consistent with the fracture form of the test gear, covering 12 teeth. The relationship between the stress at the test monitoring point and the maximum stress at the tooth root is obtained, and the generality of the relationship is verified. Based on this relationship, the maximum stress of tooth root, which is difficult to monitor in the test, is predicted to be 1271.7 MPa. An accurate and convenient means to obtain the maximum stress at the tooth root of the central transmission bevel gear under TWR is obtained so as to provide a basis for failure cause analysis and central transmission bevel gear design and lay the foundation for future research focusing on the propagation of the gear under TWR conditions. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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22 pages, 1184 KiB

Open AccessArticle

Adaptive Fault-Tolerant Control of Hypersonic Vehicles with Unknown Model Inertia Matrix and System Induced by Centroid Shift

by Hui Ye and Yizhen Meng

Appl. Sci. 2023, 13(2), 830; https://doi.org/10.3390/app13020830 - 6 Jan 2023

Cited by 1 | Viewed by 1518

Abstract

In this paper, the fault-tolerant control problem of hypersonic vehicle (HSV) in the presence of unexpected centroid migration, actuator failure and external interference is studied in depth. First, the proposed dynamics for HSV with the aforementioned unexpected factors are modeled to demonstrate the [...] Read more.

In this paper, the fault-tolerant control problem of hypersonic vehicle (HSV) in the presence of unexpected centroid migration, actuator failure and external interference is studied in depth. First, the proposed dynamics for HSV with the aforementioned unexpected factors are modeled to demonstrate the peculiar nature of the subject under study. The adverse effects of accidental centroid migration are mainly reflected in the following aspects: (1) the change of inertia matrix of the system, (2) the uncertainty of the system and (3) the eccentric moment, which are coupled and unknown. Subsequently, to account for the effect of unexpected centroid shifts, a sliding-mode observer and an adaptive estimator are designed to obtain unknowns useful for subsequent FTC controller designs. Later, we derived an innovative adaptive FTC scheme by employing the observer in conjunction with a specific adaptive controller consisting of a sixth-order dynamic compensator, which can guarantee the achievement of the control objective without resorting to the exact knowledge of the inertial matrix. Moreover, the analysis of boundedness with respect to the entire signal in this closed system is performed by means of the Lyapunov stability theory. Ultimately, simulation results show that the proposed FTC strategy is efficient and powerful. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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23 pages, 3837 KiB

Open AccessArticle

Labeling Expert: A New Multi-Network Anomaly Detection Architecture Based on LNN-RLSTM

by Xiaoyu Tang, Sijia Xu and Hui Ye

Appl. Sci. 2023, 13(1), 581; https://doi.org/10.3390/app13010581 - 31 Dec 2022

Cited by 3 | Viewed by 2371

Abstract

In network edge computing scenarios, close monitoring of network data and anomaly detection is critical for Internet services. Although a variety of anomaly detectors have been proposed by many scholars, few of these take into account the anomalies of the data in business [...] Read more.

In network edge computing scenarios, close monitoring of network data and anomaly detection is critical for Internet services. Although a variety of anomaly detectors have been proposed by many scholars, few of these take into account the anomalies of the data in business logic. Expert labeling of business logic exceptions is also very important for detection. Most exception detection algorithms focus on problems, such as numerical exceptions, missed exceptions and false exceptions, but they ignore the existence of business logic exceptions, which brings a whole new challenge to exception detection. Moreover, anomaly detection in the context of big data is limited to the need to manually adjust detector parameters and thresholds, which is constrained by the physiological limits of operators. In this paper, a neural network algorithm based on the combination of Labeling Neural Network and Relevant Long Short-Term Memory Neural Network is proposed. This is a semi-supervised exception detection algorithm that can be readily extended with business logic exception types. The self-learning performance of this multi-network is better adapted to the big data anomaly detection scenario, which further improves the efficiency and accuracy of network data anomaly detection and considers business scenario-based anomaly data detection. The results show that the algorithm achieves 96% detection accuracy and 97% recall rate, which are consistent with the business logic anomaly fragments marked by experts. Both theoretical analysis and simulation experiments verify its effectiveness. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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14 pages, 472 KiB

Open AccessArticle

Research on the Diagnosability of a Satellite Attitude Determination System on a Fault Information Manifold

by Ruotong Qu, Bin Jiang and Yuehua Cheng

Appl. Sci. 2022, 12(24), 12835; https://doi.org/10.3390/app122412835 - 14 Dec 2022

Cited by 5 | Viewed by 1297

Abstract

In this paper, a new method for fault diagnosability research based on information geometry is proposed. The problem of the diagnosability evaluation of dynamic system faults is transformed into a distance calculation problem on a manifold. The Fisher information distance is used to [...] Read more.

In this paper, a new method for fault diagnosability research based on information geometry is proposed. The problem of the diagnosability evaluation of dynamic system faults is transformed into a distance calculation problem on a manifold. The Fisher information distance is used to realize a quantitative judgment of diagnosability, and a quantitative evaluation index of the fault diagnosability of a satellite attitude determination system is designed. This includes a fault detectability index and a fault isolability index. The validity and superiority of the new indexes are verified through a mathematical simulation. In addition, the fault information is visually presented by the geodesics of the fault manifold, and the properties and behavior of the fault are mined and analyzed on the fault information manifold, which lays a foundation for further exploration of fault information through geometric methods. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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18 pages, 5637 KiB

Open AccessArticle

Predefined-Time Nonsingular Attitude Control for Vertical-Takeoff Horizontal-Landing Reusable Launch Vehicle

by Mingze Wang, Changzhu Wei, Jialun Pu and Naigang Cui

Appl. Sci. 2022, 12(19), 10153; https://doi.org/10.3390/app121910153 - 9 Oct 2022

Cited by 4 | Viewed by 2024

Abstract

This paper presents a novel predefined-time nonsingular tracking control system for a vertical-takeoff horizontal-landing (VTHL) reusable launch vehicle (RLV) in the face of parameter uncertainties, model couplings and external disturbances. Firstly, this paper proposes a novel predefined-time prescribed performance function (PTPPF) with desired [...] Read more.

This paper presents a novel predefined-time nonsingular tracking control system for a vertical-takeoff horizontal-landing (VTHL) reusable launch vehicle (RLV) in the face of parameter uncertainties, model couplings and external disturbances. Firstly, this paper proposes a novel predefined-time prescribed performance function (PTPPF) with desired steady-state and transient performance. The convergence time of PTPPF from the transient state to the steady state can be flexibly adjusted by changing one parameter. Moreover, the decreasing rate of PTPPF in the transient phase can also be adjusted by changing one parameter on the premise of not changing the convergence time of PPF to reach steady state. A novel predefined-time terminal sliding mode surface (SMS) is designed to avoid the singularity, and the attitude tracking errors on SMS are predefined-time stable. By utilizing PTPPF and error transformation, this paper designs a novel nonsingular sliding mode controller to guarantee the attitudes of RLV with desired tracking performance. Without using piecewise functions, the phenomenon of singularity can be avoided. The Lyapunov method is used to verify the stability of the controller. Lastly, a numerical simulation is presented to validate the efficiency of the proposed controller. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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23 pages, 6602 KiB

Open AccessArticle

Fault Diagnosis Method for Aircraft EHA Based on FCNN and MSPSO Hyperparameter Optimization

by Xudong Li, Yanjun Li, Yuyuan Cao, Shixuan Duan, Xingye Wang and Zejian Zhao

Appl. Sci. 2022, 12(17), 8562; https://doi.org/10.3390/app12178562 - 26 Aug 2022

Cited by 5 | Viewed by 1760

Abstract

Contrapose the highly integrated, multiple types of faults and complex working conditions of aircraft electro hydrostatic actuator (EHA), to effectively identify its typical faults, we propose a fault diagnosis method based on fusion convolutional neural networks (FCNN). First, the aircraft EHA fault data [...] Read more.

Contrapose the highly integrated, multiple types of faults and complex working conditions of aircraft electro hydrostatic actuator (EHA), to effectively identify its typical faults, we propose a fault diagnosis method based on fusion convolutional neural networks (FCNN). First, the aircraft EHA fault data is encoded by gram angle difference field (GADF) to obtain the fault feature images. Then we build a FCNN model that integrates the 1DCNN and 2DCNN, where the original 1D fault data is the input of the 1DCNN model, and the feature images obtained by GADF transformation are used as the input of 2DCNN. Multiple convolution and pooling operations are performed on each of these inputs to extract the features. Next these feature vectors are spliced in the convergence layer, and the fully connected layers and the Softmax layers are finally used to attain the classification of aircraft EHA faults. Furthermore, the multi-strategy hybrid particle swarm optimization (MSPSO) algorithm is applied to optimize the FCNN to obtain a better combination of FCNN hyperparameters; MSPSO incorporates various strategies, including an initialization strategy based on homogenization and randomization, and an adaptive inertia weighting strategy, etc. The experimental result indicates that the FCNN model optimized by MSPSO achieves an accuracy of 96.86% for identifying typical faults of the aircraft EHA, respectively, higher than the 1DCNN and the 2DCNN by about 16.5% and 5.7%. By comparing with LeNet-5, GoogleNet, AlexNet, and GRU, the FCNN model presents the highest diagnostic accuracy, less time in training and testing. The comprehensive performance of the proposed model is demonstrated to be much stronger. Additionally, the FCNN model improved by MSPSO has a higher accuracy rate when compared to PSO. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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17 pages, 4702 KiB

Open AccessArticle

Unsupervised Anomaly Detection for Time Series Data of Spacecraft Using Multi-Task Learning

by Kaifei Yang, Yakun Wang, Xiaodong Han, Yuehua Cheng, Lifang Guo and Jianglei Gong

Appl. Sci. 2022, 12(13), 6296; https://doi.org/10.3390/app12136296 - 21 Jun 2022

Cited by 9 | Viewed by 2698

Abstract

Although in-orbit anomaly detection is extremely important to ensure spacecraft safety, the complex spatial-temporal correlation and sparsity of anomalies in the data pose significant challenges. This study proposes the new multi-task learning-based time series anomaly detection (MTAD) method, which captures the spatial-temporal correlation [...] Read more.

Although in-orbit anomaly detection is extremely important to ensure spacecraft safety, the complex spatial-temporal correlation and sparsity of anomalies in the data pose significant challenges. This study proposes the new multi-task learning-based time series anomaly detection (MTAD) method, which captures the spatial-temporal correlation of the data to learn the generalized normal patterns and hence facilitates anomaly detection. First, four proxy tasks are implemented for feature extraction through joint learning: (1) Long short-term memory-based data prediction; (2) autoencoder-based latent representation learning and data reconstruction; (3) variational autoencoder-based latent representation learning and data reconstruction; and (4) joint latent representation-based data prediction. Proxy Tasks 1 and 4 capture the temporal correlation of the data by fusing the latent space, whereas Tasks 2 and 3 fully capture the spatial correlation of the data. The isolation forest algorithm then detects anomalies from the extracted features. Application to a real spacecraft dataset reveals the superiority of our method over existing techniques, and further ablation testing for each task proves the effectiveness of fusing multiple tasks. The proposed MTAD method demonstrates promising potential for effective in-orbit anomaly detection for spacecraft. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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14 pages, 3538 KiB

Open AccessArticle

Mission-Oriented Real-Time Health Assessments of Microsatellite Swarm Orbits

by Guohua Kang, Xinyu Yuan, Junfeng Wu and Zhenghao Yang

Appl. Sci. 2022, 12(11), 5605; https://doi.org/10.3390/app12115605 - 31 May 2022

Cited by 3 | Viewed by 1475

Abstract

Real-time health assessments are of great importance for the safe and stable operation of in-orbit swarms. To solve the problems of existing real-time health assessments of microsatellite swarms, such as the difficulty of selecting a multisource and assessment calculation normalization, this paper proposes [...] Read more.

Real-time health assessments are of great importance for the safe and stable operation of in-orbit swarms. To solve the problems of existing real-time health assessments of microsatellite swarms, such as the difficulty of selecting a multisource and assessment calculation normalization, this paper proposes a real-time health assessment method applicable to mission-oriented swarms. The method divides the microsatellite swarm into three levels: single satellite, intersatellite communication link and swarm effectiveness, which establish a multilevel index system by adopting the reliability evaluation based on random failure and failure by loss, a health evaluation based on natural connectivity, and a real-time dynamic analysis based on swarm topology. For the swarm effectiveness during the mission, the multilevel index and the entropy weight method are used to construct the effectiveness evaluation model of the whole swarm, and the health state evaluation of the swarm is realized based on the variable weight principle. The simulation results show that this method can quantify the health state of the microsatellite swarm in real-time, and it can predict the health state after the fault without maintenance. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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21 pages, 1163 KiB

Open AccessArticle

Adaptive Fault-Tolerant Control for Flexible Variable Structure Spacecraft with Actuator Saturation and Multiple Faults

by Kai-Yu Hu, Wenjing Sun and Chunxia Yang

Appl. Sci. 2022, 12(11), 5319; https://doi.org/10.3390/app12115319 - 24 May 2022

Cited by 5 | Viewed by 1728

Abstract

This study investigated the adaptive fault-tolerant control (FTC) for a flexible variable structure spacecraft in the presence of external disturbance, multiple actuator faults, and saturation. The attitude system model of a variable structure spacecraft and actuator fault model are first given. A sliding [...] Read more.

This study investigated the adaptive fault-tolerant control (FTC) for a flexible variable structure spacecraft in the presence of external disturbance, multiple actuator faults, and saturation. The attitude system model of a variable structure spacecraft and actuator fault model are first given. A sliding mode-based fault detection observer and a radial basis function-based fault estimation observer were designed to detect the time of actuator fault occurrence and estimate the amplitude of an unknown fault, respectively. Then, the adaptive FTC with variable structure harmonic functions was proposed to automatically repair multiple actuator faults, which first guaranteed that the state trajectory of attitude systems without actuator saturation converges to a neighborhood of the origin. Then, another improved adaptive FTC scheme was further proposed in the actuator saturation constraint case, ensuring that all the closed-loop signals are finite-time convergence. Finally, simulation results are given to illustrate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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19 pages, 2469 KiB

Open AccessArticle

Variable Structure PID Controller for Satellite Attitude Control Considering Actuator Failure

by Yong Qi, Haizhao Jing and Xiwei Wu

Appl. Sci. 2022, 12(10), 5273; https://doi.org/10.3390/app12105273 - 23 May 2022

Cited by 5 | Viewed by 2883

Abstract

In this paper, a variable structure PID controller with a good convergence rate and robustness for satellite attitude is proposed. In order to improve the system convergence rate, the variable structure for the proportional and differential term was designed, and an angular velocity [...] Read more.

In this paper, a variable structure PID controller with a good convergence rate and robustness for satellite attitude is proposed. In order to improve the system convergence rate, the variable structure for the proportional and differential term was designed, and an angular velocity curve with a better convergence rate was achieved by this variable structure. In addition, an integral partitioning algorithm was designed, and the system robustness to disturbance torque was improved; meanwhile, the negative effect of the integral term was avoided during the converging process. The actuator failure condition was also considered, and a fault tolerant control algorithm was designed. System stability was analyzed by the Lyapunov method, and its performance was demonstrated by numerical simulation. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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18 pages, 4340 KiB

Open AccessArticle

Reconfigurable Fault-Tolerant Control for Spacecraft Formation Flying Based on Iterative Learning Algorithms

by Yule Gui, Qingxian Jia, Huayi Li and Yuehua Cheng

Appl. Sci. 2022, 12(5), 2485; https://doi.org/10.3390/app12052485 - 27 Feb 2022

Cited by 12 | Viewed by 2428

Abstract

This paper investigates the issues of iterative learning algorithm-based robust thruster fault reconstruction and reconfigurable fault-tolerant control for spacecraft formation flying systems subject to space perturbations. Motivated by sliding mode methodology, a novel iterative learning observer (ILO) was developed to robustly reconstruct the [...] Read more.

This paper investigates the issues of iterative learning algorithm-based robust thruster fault reconstruction and reconfigurable fault-tolerant control for spacecraft formation flying systems subject to space perturbations. Motivated by sliding mode methodology, a novel iterative learning observer (ILO) was developed to robustly reconstruct the thruster faults. Based on the fault signals obtained from the ILO, a learning output–feedback fault-tolerant control (LOF²TC) approach was explored such that the closed-loop spacecraft formation configuration was accurately maintained in the presence of space perturbations and thruster faults. Numerical simulations were employed to demonstrate the effectiveness and superiority of the proposed ILO-based fault-reconstructing approach and LOF²TC-based configuration maintenance approach for spacecraft formation flying systems. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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24 pages, 20979 KiB

Open AccessArticle

Spacecraft Telemetry Anomaly Detection Based on Parametric Causality and Double-Criteria Drift Streaming Peaks over Threshold

by Zefan Zeng, Guang Jin, Chi Xu, Siya Chen and Lu Zhang

Appl. Sci. 2022, 12(4), 1803; https://doi.org/10.3390/app12041803 - 9 Feb 2022

Cited by 19 | Viewed by 2608

Abstract

Most of the spacecraft telemetry anomaly detection methods based on statistical models suffer from the problems of high false negatives, long time consumption, and poor interpretability. Besides, complex interactions, which may determine the propagation of anomalous mode between telemetry parameters, are often ignored. [...] Read more.

Most of the spacecraft telemetry anomaly detection methods based on statistical models suffer from the problems of high false negatives, long time consumption, and poor interpretability. Besides, complex interactions, which may determine the propagation of anomalous mode between telemetry parameters, are often ignored. To discover the complex interaction between spacecraft telemetry parameters and improve the efficiency and accuracy of anomaly detection, we propose an anomaly detection framework based on parametric causality and Double-Criteria Drift Streaming Peaks Over Threshold (DCDSPOT). We propose Normalized Effective Transfer Entropy (NETE) to reduce the error and noise caused by nonstationarity of the data in the calculation of transfer entropy, and then apply NETE to improve the Multivariate Effective Source Selection (MESS) causal inference algorithm to infer parametric causality. We define the Weighted Source Parameter (WSP) of the target parameter to be detected, then DSPOT is employed to set multi-tier thresholds for target parameter and WSP. At last, two criteria are formulated to determine anomalies. Additionally, to cut the time consumption of the DCDSPOT, we apply Probability Weighted Moments (PWM) for parameter estimation of Generalized Pareto Distribution (GPD). Experiments on real satellite telemetry dataset shows that our method has higher recall and F1-score than other commonly used methods, and the running time is also significantly reduced. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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15 pages, 843 KiB

Open AccessArticle

Robust ADP-Based Sliding-Mode Fault-Tolerant Control for Nonlinear Systems with Application to Spacecraft

by Yanbin Du, Bin Jiang, Yajie Ma and Yuehua Cheng

Appl. Sci. 2022, 12(3), 1673; https://doi.org/10.3390/app12031673 - 6 Feb 2022

Cited by 12 | Viewed by 2133

Abstract

This paper considers a novel fault-tolerant control (FTC) scheme for a category of cascade nonlinear systems with mismatched uncertainties and unknown actuator faults. The robust adaptive dynamic programming (RADP) is used to design a novel optimal sliding surface (SS) off-line, which renders the [...] Read more.

This paper considers a novel fault-tolerant control (FTC) scheme for a category of cascade nonlinear systems with mismatched uncertainties and unknown actuator faults. The robust adaptive dynamic programming (RADP) is used to design a novel optimal sliding surface (SS) off-line, which renders the corresponding sliding-mode dynamics able to obtain robustness of stability to mismatched uncertainties. Subsequently, a simple sliding-mode control (SMC) with the adaptive fault compensation is developed to guarantee reachability of the sliding mode. Then, it is proven that the weight errors of neural networks (NN) of RADP and the closed-loop system are stable based on Lyapunov stability theory. In the simulation section, this proposed scheme is used to deal with the attitude FTC of a spacecraft, and simulation results verify the effectiveness of the proposed novel control scheme. Full article

(This article belongs to the Special Issue Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft)

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