Boundary control for PDE flexible manipulators: Accommodation to both actuator faults and sensor faults

2021 ◽  
Author(s):  
Fangfei Cao ◽  
Jinkun Liu
Keyword(s):  
Boundary Control ◽  
Flexible Manipulators ◽  
Sensor Faults ◽  
Actuator Faults

Robust actuator and sensor fault reconstruction of wind turbine using modified sliding mode observer

2018 ◽  
Vol 41 (6) ◽  
pp. 1504-1518 ◽  
Author(s):  
Mostafa Rahnavard ◽  
Moosa Ayati ◽  
Mohammad Reza Hairi Yazdi
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Rotational Speed ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Fault Reconstruction ◽  
Different Order ◽  
Aerodynamic Torque

This paper proposes a robust fault diagnosis scheme based on modified sliding mode observer, which reconstructs wind turbine hydraulic pitch actuator faults as well as simultaneous sensor faults. The wind turbine under consideration is a 4.8 MW benchmark model developed by Aalborg University and kk-electronic a/s. Rotor rotational speed, generator rotational speed, blade pitch angle and generator torque have different order of magnitudes. Since the dedicated sensors experience faults with quite different values, simultaneous fault reconstruction of these sensors is a challenging task. To address this challenge, some modifications are applied to the classic sliding mode observer to realize simultaneous fault estimation. The modifications are mainly suggested to the discontinuous injection switching term as the nonlinear part of observer. The proposed fault diagnosis scheme does not require know the exact value of nonlinear aerodynamic torque and is robust to disturbance/modelling uncertainties. The aerodynamic torque mapping, represented as a two-dimensional look up table in the benchmark model, is estimated by an analytical expression. The pitch actuator low pressure faults are identified using some fault indicators. By filtering the outputs and defining an augmented state vector, the sensor faults are converted to actuator faults. Several fault scenarios, including the pitch actuator low pressure faults and simultaneous sensor faults, are simulated in the wind turbine benchmark in the presence of measurement noises. Simulation results show that the modified observer immediately and faithfully estimates the actuator faults as well as simultaneous sensor faults with different order of magnitudes.

scholarly journals Observer Design for Simultaneous State and Fault Estimation for a Class of Discrete-time Descriptor Linear Models

2021 ◽  
Vol 229 ◽  
pp. 01020
Author(s):  
Kaoutar Ouarid ◽  
Abdellatif El Assoudi ◽  
Jalal Soulami ◽  
El Hassane El Yaagoubi
Keyword(s):  
Discrete Time ◽  
Linear Models ◽  
Estimation Error ◽  
Equivalent Form ◽  
Observer Design ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Algebraic Equations

This paper investigates the problem of observer design for simultaneous states and faults estimation for a class of discrete-time descriptor linear models in presence of actuator and sensor faults. The idea of the present result is based on the second equivalent form of implicit model [1] which permits to separate the differential and algebraic equations in the considered singular model, and the use of an explicit augmented model structure. At that stage, an observer is built to estimate simultaneously the unknown states, the actuator faults, and the sensor faults. Next, the explicit structure of the augmented model is established. Then, an observer is built to estimate simultaneously the unknown states, the actuator faults, and the sensor faults. By using the Lyapunov approach, the convergence of the state estimation error of the augmented system is analyzed, and the observer’s gain matrix is achieved by solving only one linear matrix inequality (LMI). At long last, an illustrative model is given to show the performance and capability of the proposed strategy.

A Unified Nonlinear Approach to Fault Diagnosis of Aircraft Engines

2013 ◽  
Author(s):  
Xiaodong Zhang ◽  
Remus C. Avram ◽  
Liang Tang ◽  
Michael J. Roemer
Keyword(s):  
Fault Detection ◽  
Adaptive Estimation ◽  
Fault Isolation ◽  
Nonlinear Observer ◽  
Aircraft Engines ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Engine Model ◽  
Fault Type ◽  
Component Faults

Many existing aircraft engine diagnostic methods are based on linearized engine models. However, the dynamics of aircraft engines are highly nonlinear and rapidly changing. Future engine health management designs will benefit from new methods that are directly based on intrinsic nonlinearities of the engine dynamics. In this paper, a fault detection and isolation (FDI) method is developed for aircraft engines by utilizing nonlinear adaptive estimation and nonlinear observer techniques. Engine sensor faults, actuator faults and component faults are considered under one unified nonlinear framework. The fault diagnosis architecture consists of a fault detection estimator and a bank of nonlinear fault isolation estimators. The fault detection estimator is used for detecting the occurrence of a fault, while the bank of fault isolation estimators is employed to determine the particular fault type or location after fault detection. Each isolation estimator is designed based on the functional structure of a particular fault type under consideration. Specifically, adaptive estimation techniques are used for designing the isolation estimators for engine component faults and actuator faults, while nonlinear observer techniques are used for designing the isolation estimators for sensor faults. The FDI architecture has been integrated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) engine model developed by NASA researchers in recent years. The engine model is a realistic representation of the nonlinear aero thermal dynamics of a 90,000-pound thrust class turbofan engine with high-bypass ratio and a two-spool configuration. Representative simulation results and comparative studies are shown to verify the effectiveness of the nonlinear FDI method.

scholarly journals Boundary Control of A Flexible Rotatable Manipulator in Three-Dimensional Space With Input Constraints and Actuator Faults

2021 ◽  
Author(s):  
Jiacheng Wang ◽  
Jinkun Liu ◽  
Fangfei Cao
Keyword(s):  
Boundary Control ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Flexible Manipulator ◽  
Control Input ◽  
Input Constraints ◽  
Actuator Faults ◽  
Flexible System ◽  
Actuator Failures ◽  
Three Dimensional Space

Abstract In this paper, the boundary control problem of a flexible rotatable manipulator in Three-Dimensional space with input constraints and actuator faults is taken into account. The Hamilton principle is introduced to derive the dynamic model represented by partial differential equations (PDEs), which can accurately reflect the characteristics of the distributed parameters of the flexible system. The hyperbolic tangent function is adopted to ensure that the control input is within a bounded range, and the projection-based adaptive laws are designed to estimate the degree of unknown actuator failures. Satisfying the input constraints, the system can still remain stable when the actuator failures ensue. The flexible manipulator can track the required angle, and both the elastic deformation and the deformation rate are effectively suppressed simultaneously. The numerical simulation results further illustrate the effectiveness of the proposed controller.

scholarly journals Advanced Fault Diagnosis for Lithium-Ion Battery Systems

2020 ◽  
Author(s):  
Xiaosong Hu ◽  
Kai Zhang ◽  
Kailong Liu ◽  
Xianke Lin ◽  
Satadru Dey ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Lithium Ion Battery ◽  
Smart Grids ◽  
Lithium Ion ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Safe Operation ◽  
Battery System ◽  
Safety Issues ◽  
Fault Features

Lithium-ion batteries have become the mainstream energy storage solution for many applications, such as electric vehicles and smart grids. However, various faults in a lithium-ion battery system (LIBS) can potentially cause performance degradation and severe safety issues. Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This paper provides a comprehensive review of fault mechanisms, fault features, and fault diagnosis of various faults in LIBS, including internal battery faults, sensor faults, and actuator faults. Future trends in the development of fault diagnosis technologies for a safer battery system are presented and discussed.

scholarly journals A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults

2010 ◽  
Author(s):  
Liang Tang ◽  
Xiaodong Zhang ◽  
Jonathan A. DeCastro ◽  
Luis Farfan-Ramos ◽  
Donald L. Simon
Keyword(s):  
Health Management ◽  
System Development ◽  
Aircraft Engine ◽  
Fault Detection And Isolation ◽  
Specific Response ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Unified Framework ◽  
Adaptive Estimator ◽  
Component Faults

A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.

scholarly journals Advanced Fault Diagnosis for Lithium-Ion Battery Systems

2020 ◽  
Author(s):  
Xiaosong Hu ◽  
Kai Zhang ◽  
Kailong Liu ◽  
Xianke Lin ◽  
Satadru Dey ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Lithium Ion Battery ◽  
Smart Grids ◽  
Lithium Ion ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Safe Operation ◽  
Battery System ◽  
Safety Issues ◽  
Fault Features

Lithium-ion batteries have become the mainstream energy storage solution for many applications, such as electric vehicles and smart grids. However, various faults in a lithium-ion battery system (LIBS) can potentially cause performance degradation and severe safety issues. Developing advanced fault diagnosis technologies is becoming increasingly critical for the safe operation of LIBS. This paper provides a comprehensive review of fault mechanisms, fault features, and fault diagnosis of various faults in LIBS, including internal battery faults, sensor faults, and actuator faults. Future trends in the development of fault diagnosis technologies for a safer battery system are presented and discussed.

Integration of Unknown Input Observers and Classification for Turbofan Engine Diagnosis

2011 ◽  
Author(s):  
Daoliang Tan ◽  
Ai He ◽  
Xiangxing Kong ◽  
Xi Wang
Keyword(s):  
Diagnostic System ◽  
Aircraft Engine ◽  
Integrated Approach ◽  
Support Vector ◽  
Svm Classifier ◽  
Unknown Input ◽  
Sensor Faults ◽  
Actuator Faults ◽  
The Past ◽  
Unknown Input Observers

A great deal of attention has been attracted in the analytical model-based engine diagnostics over the past years. Meanwhile, an increasing number of researchers and practitioners make an attempt to gain an intelligent diagnoser in a pattern recognition way. A question naturally emerges of how to combine the two techniques to improve the robustness of an on-board diagnostic system. In this context, this paper suggests an integrated approach that combines the unknown input observer (UIO) with the support vector machine (SVM) technique to aircraft engine fault diagnosis. Sensor faults and actuator faults are separately considered. To reduce the effect of engine disturbances on diagnostic performance, we first design a bank of UIOs, each of which is sensitive to all sensor and actuator faults but only one signal. Then, the magnitudes of a set of residuals between the UIO-based estimations and the engine measurements are fed into an SVM classifier to detect and isolate engine faults. Experimental results demonstrate an encouraging potential of the suggested method and that the UIO-oriented approach is superior or competitive to the Kalman-based algorithm.

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