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Manufacturing systems are becoming more sophisticated and expensive, particularly with the development of the intelligent industry. The complexity of the architecture and concept of Smart Manufacturing (SM) makes it vulnerable to several faults and failures that impact the entire behavior of the manufacturing system. It is crucial to find and detect any potential anomalies and faults as soon as possible because of the low tolerance for performance deterioration, productivity decline, and safety issues. To overcome these issues, a variety of approaches exist in the literature. However, the multitude of techniques make it difficult to choose the appropriate method in relation to a given context. This paper proposes a new architecture for a conceptual model of intelligent fault diagnosis and self-healing for smart manufacturing systems. Based on this architecture, a review method for the different approaches, sub-approaches and methods used to develop a Fault Detection and Diagnosis (FDD) and Self-Healing-Fault-Tolerant (SH-FT) strategy dedicated to smart manufacturing is defined. Moreover, this paper reviews and analyzes more than 256 scientific articles on fault diagnosis and self-healing approaches and their applications in SM in the last decade. Finally, promising research directions in the field of resilient smart manufacturing are highlighted. [ABSTRACT FROM AUTHOR]

A mathematical model of the main drive system of rolling mill is developed for the motor armature faults in the main drive system of rolling mill, taking into account the effects of nonlinear damping, friction damping between rolls and external perturbations on the system during operation. The unknown input observer is designed to process perturbations and errors as unknown inputs, and the H ∞ performance index is designed to improve the robustness of the unknown input observer to fault reconfiguration. At the same time, in order to ensure the stability of the main drive system of rolling mill after the occurrence of faults, an active fault-tolerant controller is designed for the main drive system of rolling mill after obtaining the accurate fault reconfiguration value, which realizes the active fault-tolerant control of the main drive system of rolling mill. Through the simulation study on the main drive system of 2030 mm cold rolling mill stand F4, it is shown that the system is restored to the normal state after adding the fault-tolerant controller, and the motor angular speed error and roll angular speed error are 2.12% and 2.43%, respectively. Comparing with the fault-tolerant control method based on fault estimation, the root-mean-square errors of the motor angular speed and roll angular speed estimates of the designed fault-tolerant control method are reduced by 4.24% and 3.28%, respectively. Simulation verifies the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a new fault-diagnosis method and fault-tolerance control (FTC) strategy applied to the field-oriented control (FOC) of induction motor drives. The proposed diagnosis method for open-switch faults (OSFs) relies solely on measured current behavior. The diagnostic variables are extracted from the average absolute values of the normalized phase currents. The simulation results show that the diagnosis method can detect the OSFs in less than 36% of the fundamental phase current period without additional sensors. A total of nine types of OSFs can be diagnosed accurately and quickly. In addition, the obtained results demonstrate the method's robustness against load-transient conditions. Compared with existing diagnosis methods, this technique relies on two diagnostic variables and an adaptive detection threshold. To improve the drive's reliability against OSF effects, a fault-tolerant control scheme is developed based on reconfiguring the voltage source inverter (VSI) topology. In this case, the faulty VSI phase is connected to the DC-link midpoint through bidirectional power switches. Most FTC systems reported in the literature require a change in the drive's control algorithm. Hence, this paper presents a low-cost FTC scheme without changing the FOC algorithm. Simulation results are carried out in MATLAB-Simulink to validate the effectiveness of the proposed fault diagnosis method and the FTC strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a fault-tolerant control (FTC) strategy using the current space vectors to diagnose sensor failures and enhance the sustained operation of a field-oriented (FO) controlled induction motor drive (IMD). Three space vectors are established for the sensor fault diagnosis technique, including one converted from the measured currents and the other two calculated from the current estimation technique, respectively, measured and with reference speeds. A mixed mathematical model using three space vectors and their components is proposed to accurately determine the fault condition of each sensor in the motor drive. After determining the operating status of each sensor, if the sensor signal is in good condition, the feedback signal to the controller will be the measured signal; otherwise, the estimated signal will be used instead of the failed signal. Failure states of the various sensors were simulated to check the effectiveness of the proposed technique in the Matlab/Simulink environment. The simulation results are positive: the IMD system applying the proposed FTC technique accurately detected the failed sensor and maintained stability during the operation. [ABSTRACT FROM AUTHOR]

This paper introduces a novel data‐driven approach to develop a fault‐tolerant model predictive controller (MPC) for non‐linear systems. By adopting a Koopman operator‐theoretic perspective, the proposed method leverages historical data from the system to construct a data‐driven model that captures the non‐linear behaviour and fault characteristics. The fault influence is addressed through an online estimation of a time‐varying Koopman predictor, which allows for adjusting the MPC control law to counteract the fault effects. This estimation is performed in a higher dimensional Koopman feature space, where the dynamics behave linearly. As a result, the non‐linear fault‐tolerant MPC optimization problem can be replaced with a more practical and feasible linear time‐varying one using the approximated Koopman predictor. Moreover, by incorporating the online update procedure, the time‐varying Koopman predictor can represent the dynamics of the faulty system. Hence, the controller can adapt and compensate for the faults in real‐time, integrating the fault diagnosis module in the MPC framework and eliminating the need for a separate fault detection unit. Finally, the efficacy of the proposed approach is demonstrated through case study results, which highlight the ability of the controller to mitigate faults and maintain desired system behaviour. [ABSTRACT FROM AUTHOR]

In order to address the problem that the main drive system of rolling mill is easily affected by the impact of biting steel, and considering the nonlinear friction damping and the external perturbations of the main drive system of rolling mill during the rolling process, a fault model of the main drive system of rolling mill is established, and a fault diagnosis and fault tolerance control method of the main drive system of rolling mill based on the nonlinear sliding-mode observer is proposed. In order to suppress the influence of external perturbations on fault diagnosis, a nonlinear sliding-mode observer is constructed for fault diagnosis and fault reconfiguration of the system, and the robustness of the observer to fault reconfiguration is improved by using the sliding-mode control rate v , and the stability of the designed nonlinear sliding-mode observer is proved using Lyapunov's stability theorem. In order to ensure that the system can operate normally even after a fault occurs, a reference model is designed, and a new controller is redesigned for fault-tolerant control of the system by adding a fault compensation term to the original control scheme using fault estimation information. Through the simulation study of the main drive system of stand F4 of 2030 mm cold rolling mill, it is verified that the observer can accurately track the system state with an angular velocity error of 2.45% and detect and estimate the main drive system failure of rolling mill with an estimation error of no more than 0.04% after a fault occurs; the fault-tolerant control of the main drive system of rolling mill is carried out by using the fault information to restore the system to its normal state, and the angular velocity error is 1.89%. [ABSTRACT FROM AUTHOR]

Summary: Due to the long‐term operation of the tower crane, various faults will inevitably occur, such as actuator faults, which further increases the difficulty of controller design. In this paper, a fault‐tolerant control method with adaptive gain is proposed for the double‐pendulum tower crane with distributed payload beam (DTCDPB) system in the existence of external disturbances and actuator failures. First, a nonlinear fault‐tolerant observer is designed for fault diagnosis. Second, an S‐shaped trajectory functions are coupled online and embedded into the system target trajectories for payload swing suppression. Then, feedforward compensation is applied in the controller for the observed faults. Moreover, the adaptive suppression term to be activated is also designed in the controller taking into account the errors existing in the observation. Finally, the effectiveness of the proposed observer and controller is experimentally verified. [ABSTRACT FROM AUTHOR]

In this article, the problems of fault diagnosis (FD) and fault-tolerant control (FTC) are investigated for a class of nonlinear systems with output measurement noise. Due to the influence of measurement noise in the output sensor, the output observation error cannot be accurately obtained, which causes obstacles to the accuracy of FD. To address this issue, an output filter and disturbance estimator are constructed to decrease the negative effects of measurement noise and observer gain disturbances, and a novel non-fragile neural observer is designed to estimate the unknown states. A new evaluation function is also introduced to detect faults. Then, a novel neural FTC controller is proposed in the presence of faults, to ensure that all the closed-loop system signals are semiglobally uniformly ultimately bounded (SGUUB). The effectiveness of the proposed methodology is verified via numerical simulation of a one-link robot system. [ABSTRACT FROM AUTHOR]

The manuscript proposes a data-based integral terminal sliding mode control approach to determine fault-tolerant control (FTC) concerning a class of discrete-time nonlinear systems (DTNS) containing sensor fault. The proposed scheme can be readily implemented because it purely utilizes the input and output data of the system to employ a model called the compact form dynamic linearization (CFDL) data model, while the one-step forward approximator is employed to estimate the fault function term in the system. Moreover, the fault diagnosis mechanism utilizes a time-varying threshold with prescribed performance to judge whether the fault occurs. Hence, the problem of a standard fixed threshold used at the start-up state of the control system is resolved. Then, the discrete-time integral terminal sliding mode fault-tolerant control (DITSM-FTC) method is proposed. Concurrently, the sturdiness of the proposed method is assured by hypothetical investigation. When compared with the literature, the fundamental features of the proposed method are presented as follows: (1) the problem pertinent to fault utilizing a data-driven model is resolved; (2) a fault diagnosis mechanism with prescribed performance is proposed, and (3) one step forward approximator is utilized to devise an estimation approach of fault detection. Finally, the efficacy of the proposed method is presented by running simulations. [ABSTRACT FROM AUTHOR]

T-type three-level inverters (T23LIs) are widely used in the electric drive system of new energy vehicles. However, the open-circuit (OC) faults of their switching devices will cause serious damage to the entire system operation. To mitigate the impact of switching faults, this paper proposes an OC fault diagnosis method based on the variations of common-mode voltage in small sectors of T23LI. Firstly, the normal characteristics of T23LI under SVPWM control algorithm are analyzed, and the correspondence between the space voltage vectors and the values of common-mode voltage is established. Then, the common-mode voltage variations under fault conditions are analyzed, and a fault diagnosis method based on these variations is proposed. The faults of the four switching devices in one phase is divided into two groups through the qualitative analysis of common-mode voltage variations, and the specific location of the faulty switch is located by further quantitative analysis. Finally, by analyzing the changes in the three-phase bridge output voltages after faults, the accurate location of the faults in the 12 switches of the three phases is located. Simulation and experimental results verify that the proposed method can accurately and quickly diagnose the single-switch OC faults of all switches, and it effectively accelerates the diagnosis speed and reduces costs by only requiring the collection of a single voltage signal. [ABSTRACT FROM AUTHOR]

Due to their advantages in ensuring low harmonic distortion and high power factors, single-phase Pulse-Width Modulated (PWM) rectifiers are widely employed in several industrial applications. Generally, the conventional control loop of a single-phase PWM rectifier uses both voltage and current sensors. Hence, in case of sensor fault, the performance and the availability of the converter can be seriously compromised. Therefore, diagnosis approaches and fault-tolerant control (FTC) strategies are mandatory to monitor these systems. Accordingly, this paper introduces a novel multiple-sensor FTC scheme for a single-phase PWM rectifier. The proposed fault diagnosis approach relies on joining several Generalized Proportional Integral (GPI) and Model Reference Adaptive System (MRAS) observers with a residual generation technique to detect and isolate sensor faults in a simple and reliable manner. While conventional sensor FTC methods dedicated to PWM rectifiers can only deal with single faults, the suggested approach guarantees a very good effectiveness level of sensor fault detection, isolation (FDI) and FTC of multiple-sensor fault occurrence scenarios. Consequently, the single-phase PWM rectifier can work with only the survivable single sensor with the guarantee of very good performance as in healthy operation mode. The effectiveness of the proposed sensor FDI approach and its control reconfiguration performance are demonstrated through both extensive simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper investigates the fault-tolerant prescribed performance control problem for a class of multiple-input single-output unknown nonlinear systems subject to process faults and actuator failures. In contrast to the related works, we consider a general class of nonlinear systems with both multiplicative nonlinearities and additive nonlinearities corrupted by the process faults; only the boundedness of the process faults and the continuity of the nonlinear functions are required, without the explicit or fixed structures of the fault functions. To conquer this problem, a less-demanding and low-complexity fault-tolerant prescribed performance control approach is proposed. The controller is independent of the specific information of faults or the system model and does not invoke fault diagnosis or neural/fuzzy approximation to acquire such knowledge. It achieves the reference tracking with the predefined rate and accuracy. A comparative simulation on a single-link robot is conducted to illustrate the effectiveness and superiority of the proposed approach. • Both process faults and actuator failures are considered. • The virtual control coefficients are time-varying nonlinear functions. • We consider a general class of systems with multiplicative and additive nonlinearities. • Both multiplicative and additive nonlinearities are impacted by process faults. • The reference tracking with predefined rate and accuracy is achieved. [ABSTRACT FROM AUTHOR]

Ocean currents, mechanical collisions and electronic damage can cause faults in an autonomous underwater vehicle (AUV), including sensors and thrusters. For such problems, this paper designs a fault-tolerant controller that is independent of the results of the fault diagnosis. An adaptive reaching law is developed based on sliding mode control to shorten convergence times. For the chattering phenomenon, a weighted hyperbolic tangent function is adopted instead of the traditional sign function in sliding mode control. Simulations are carried out when thruster and sensor fail under the condition of ocean current disturbance, model uncertainty and sensor noise. Comparative simulation results show that the proposed method can accelerate the convergence speed of the state point and improve the trajectory tracking effect of the AUV. Consequently, the effectiveness of the proposed method is confirmed. [ABSTRACT FROM AUTHOR]

Summary: The purpose of this Special Issue on "Sliding–mode algorithms for state estimation and fault diagnosis" is to present a collection of articles showing novel developments and results in the theory and practice of sliding–mode algorithms for state estimation and fault diagnosis. This collection also includes some advanced and non–standard methods to deal with the fault–tolerant control problem. [ABSTRACT FROM AUTHOR]

Multistack fuel cell systems (MFCS) are promising developments of fuel cell technology. For MFCS, faults affect durability and stability, and appropriate fault diagnosis methods and control strategies need to be proposed for different multistack structures. Herein, the integrated MFCS thermal management subsystem (TMS), which is based on the optimized split‐stack approach, is first studied, and its possible sensor and actuator faults are analyzed. The sensor fault signal is corrected based on the unscented Kalman filter (UKF), the controller design under the hardware in the loop platform is carried out, and an active fault‐tolerant control (FTC) strategy based on sliding mode control is deployed for the TMS to enable it to recover its performance quickly and effectively in case of faults. The results show that the estimated values are closer to the true values after using the UKF on the sensor signals, avoiding the impact of sensor faults on the system performance. Under New European Driving Cycle dynamic conditions, the FTC controller also exhibits better control compared to the conventional proportional–integral controller, with smaller maximum overshoot and shorter system recovery and stabilization time in the event of a TMS fault, mitigating the impact of system fault on performance. [ABSTRACT FROM AUTHOR]

The concept of Industry 4.0 is flexible monitoring, uninterrupted services, cost-effectiveness, and things connected to networks. Industrial drives with various sensing and controlling units are the key components of every industrial process. In electric drive, the current sensor and speed encoder are used for controlling the system. A fault in the sensing unit could interrupt the process, which causes production losses. In this paper, a fast and smooth switching control strategy is designed and deployed for induction motor drives (IMD) to enhance system reliability and provide uninterrupted services. Based on supervisory decisions, suitable control strategies such as field-oriented control, slip compensation, and scalar control are chosen as alternatives during sensor failure. The adaptive reconfigurable fault-tolerant control technique (ARFTC) is employed for IMD, which can mitigate the transient issues while transitioning between different controls. This ARFTC scheme involves the DC-type feature of the synchronous-frame voltage commands (Vds∗,Vqs∗) and the synchronization of the rotor angle between the different control strategies. Under sensor-fault conditions, ARFTC enables better performance on the drive. Furthermore, cost-effective IoT monitoring services are integrated into the system for analyzing the performance of the drive. The proposed ARFTC is deployed in real-time on the industrial drive VLT-302 using the dSPACE MicroLabBox controller and Alborg interfacing and protection card. The proposed adaptive scheme is experimentally evaluated with a 2.2 kW squirrel cage induction motor under various sensor fault conditions. The obtained results shows that the proposed ARFTC is constructive for enhancing the reliability of induction motor drives, especially in sensor failure situations.

This study presents an adaptive fault estimation and model predictive fault-tolerant control (FTC) for the hypersonic vehicle engine with non-Gaussian uncertain output jet plume. The non-Gaussian probability density function (PDF) describing the plume velocity in a stochastic system is approximated by Type II fuzzy radial basis functions. In the fault observer, the novel prey adaptive estimation method is designed for the valve faults with different amplitudes. Ultimately, this fuzzy-prey fusion adaptive observer shields perturbation and accurately estimates complex faults including incipient and intermittent faults. A predictive tolerant controller compensates for all the faults effects and non-fragile compensation factors of FTC eliminate the perturbation interference, thence the output PDF matches with the expected value. Finally, the more refined internal structure of plume output distribution replaces the local and rough valve position variables, helping this study realizes the hypersonic vehicle engine integrated refine control. Simulation result verifies the effectiveness of the proposed approaches and the superiority compared with the existing method. [ABSTRACT FROM AUTHOR]

Summary: This article contributes with a fault‐tolerant control (FTC) for uncertain systems under the effect of some possible time‐ and state‐dependent actuator faults and/or failures, and component faults, which are zero at the initial time. The proposed scheme is based on a continuous integral sliding‐mode control approach and a fixed control allocation technique. The integral sliding‐mode control strategy allows us to design a robust linear controller and a multivariable Super‐Twisting algorithm, which deals with the faults. The proposed scheme guarantees the fulfilment of an output regulation task, with an arbitrarily small regulation error, and does not require a fault diagnosis stage but full‐state availability. The performance of the proposed FTC is illustrated through some simulations on a benchmark B747 aircraft model. [ABSTRACT FROM AUTHOR]

Summary: In the paper, the problem of fault diagnosis and fault‐tolerant control for the bilinear stochastic distribution system with actuator fault is studied. Firstly, based on a grain processing device, a bilinear stochastic distribution system model is established. Then, a new unknown input observer is designed to diagnose the fault, and a model‐predicted fault‐tolerant controller is designed for the system on the basis of the estimated fault information, in order to keep the system stable or still maintain the control performance after the fault occurs. Finally, the validity of the proposed algorithm is verified by the grain processing process. [ABSTRACT FROM AUTHOR]

• A fault-tolerant model-free predictive approach is developed to control spacecraft coupled 6-DOF relative motion. In this paper, the previous work of the authors on Subspace Predictive Control (SPC) in the context of spacecraft roto-translational relative motion is pursued, and the introduced novel SPC-based approach to fault-tolerant control (FTC) of nonlinear time-variant systems is further investigated. Firstly, the effectiveness of the proposed SPC-based framework for adaptive control allocation is exploited. Subsequently, separating nonlinear control and control allocation blocks yields a new layered SPC-based control scheme. Furthermore, designating a dedicated controller for each of the coupled motions leads to a novel distributed SPC-based architecture. Accordingly, three complete model-free fault-tolerant controllers for coupled nonlinear time-variant plants are developed, which solely need the knowledge of the occurrence time of faults as prerequisite. An internal fault diagnosis capability is also introduced, which makes the framework completely self-sufficient. Finally, the proposed framework is verified by challenging simulated scenarios. [ABSTRACT FROM AUTHOR]

The electro-hydraulic servo system (EHSS) usually faces multiple sensor faults and disturbances, which is difficult to achieve good tracking control, reliability, and stability control. In this article, an advanced fault-tolerant controller is proposed for an EHSS to deal with the above challenge. The three fault observers, called nonlinear unknown input observers (NUIOs), are developed to effectively estimate the position, velocity, pressure sensor faults and the system states. The fault detection, estimation, and isolation are then presented as effective for multiple sensors failure at a time. The first NUIO for position sensor fault is utilized for the tracking control, while the other NUIOs are used for alarm proposal. The adverse effects caused by the matched and unmatched disturbances are eliminated by two extended state observers (ESOs). In addition, to avoid the "explosion of complexity" when computing the derivatives of virtual control laws, the dynamic surface control is applied to design the fault-tolerant control (FTC) scheme. The Lyapunov principle ensures system stability under lumped disturbance and faulty conditions. Finally, simulation studies and evaluation results are performed to demonstrate the validity of the proposed FTC algorithm. [ABSTRACT FROM AUTHOR]

The actuator fault-tolerant control problem for a variable-pitch quadrotor is addressed under uncertain conditions. Following a model-based approach, the plant nonlinear dynamics are faced with a disturbance observer-based control and a sequential quadratic programming control allocation, where only kinematic data of the onboard inertial measurement unit are required for the fault-tolerant control, i.e., it does not require the measurement of the motor speed nor the current drawn by the actuators. In the case of almost horizontal wind, a single observer handles both faults and the external disturbance. The estimation of the wind is fed forward by the controller, while the actuator fault estimation is exploited in the control allocation layer, which copes with the variable-pitch nonlinear dynamics, thrust saturation, and rate limits. Numerical simulations in the presence of measurement noise show the capability of the scheme to handle multiple actuator faults in a windy environment. [ABSTRACT FROM AUTHOR]

This study tackles the fault estimation issue for a continuous-time periodic piecewise time-varying systems (PPTVSs) with delays, fault signal and external disturbances. In particular, the PPTVSs are conjured up by segmenting the fundamental period of the periodic system into a finite number of subintervals. Moreover, fault estimator is designed in line with periodic piecewise observer systems to estimate the immeasurable states of the PPTVSs and the fault signal, simultaneously. Subsequently, in accordance with the estimated values of the fault signal and state dynamics, a fault-tolerant controller is devised. Moreover, by utilising Lyapunov stability theory and matrix polynomial lemma, sufficient criteria are procured in context of linear matrix inequalities to affirm the uniform boundedness of the undertaken system and error system. Further, relying on the acquired constraints, the precise configuration of the fault-tolerant control and observer gain matrices are proffered. Eventually, by offering two illustrative examples including mass-spring-damper system, the utility and potential of presented theoretical insights are validated. [ABSTRACT FROM AUTHOR]

In this paper, we propose a fault tolerant control law for a morphing quadrotor, where the considered morphing ability is that of extendable/telescopic arms. This quite recent class of systems is able to provide a good trade-off between payload capabilities, maneuverability, and space occupancy. However, such degrees of freedom require dedicated servomotors, which in turn implies more possible faults. Thus, the problem of diagnosis for the telescopic servo motors subject to a stuck fault is considered. System symmetries are exploited and used in a residual generator design, which triggers an active fault isolation/identification phase. External disturbances are also taken into account and estimated through a nonlinear disturbance observer. A classical double-loop controller closes the loop, providing an overall control system structure that follows the disturbance observer-based control paradigm. The control scheme is validated through realistic numerical simulations, and the closed-loop performances are analyzed. [ABSTRACT FROM AUTHOR]

The safety of direct torque control (DTC) is strongly reliant on the accuracy and consistency of sensor measurement data. A fault-tolerant control paradigm based on a dual-torque model is proposed in this study. By introducing the vector product and scalar product of the stator flux and stator current vector, a new state variable is selected to derive a new dual-torque model of induction motor; it is combined with a current observer to propose a dual-torque model fault-tolerant control method. This technology calculates torque and reactive torque directly, reducing the system's reliance on sensors, avoiding sensor-noise interference, and improving torque response speed while suppressing torque ripple. In addition, to improve system dependability and safety, a fault-tolerant control method is devised by combining the model with an adaptive virtual current observer. Ultimately, experiments validate the suggested method's effectiveness and feasibility. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of model-based fault diagnosis (FD) and a fault-tolerant control (FTC) scheme for sensor and actuator faults of turbojet engines. For actuator FD, an unbiased estimation scheme with a modified Kalman filter (KF) was developed. For sensor FD, two approaches, the generalized likelihood ratio with robust KF and the pseudo actuator model with modified KF, were investigated in a comparative study. For fault detection and isolation, test statistics are commonly employed to detect fault behavior. For FTC, integral-type sliding mode control using control reconfiguration and the reconstruction of the sensor signal was adopted with the FD schemes. The effectiveness of the employed methods was demonstrated in this study and discussed with numerical simulations. [ABSTRACT FROM AUTHOR]

Mechanical faults, time-varying faults and other disturbances in the role of multiple coupling, the stable operation of the hydroturbine regulation system has caused great obstacles. This study concentrated on the output feedback fault-tolerant (FFT) control technology and T-S state feedback predictive control technology using the actual operating conditions of the numerical simulation test. The results show that the control technique has good identification tracking and control effect, and can make the system stabilize within 2 s in the case of disturbance. This shows that the control system designed by the research institute has good applicability and provides data reference for the intelligent control operation and maintenance of the hydroturbine regulation system. [ABSTRACT FROM AUTHOR]

Three-level T-type inverters have lower total harmonic distortion in output voltage, higher power density and lower voltage stress of power switches compared with conventional two-level inverters and have been widely used in applications with a wide-power range. Reliability improvement is particularly important for the T-type inverters because of the increased number of power switches and high system complexity. This paper proposes a fault-tolerant topology, which is constructed by adding a redundant leg including halfbridge switches and neutral-point switches connected between the DC bus capacitors and the DC-link midpoint of the conventional T-type inverter. In addition, an after-fault control strategy is proposed based on the results of a fault diagnosis method using bridge voltage. The fault-tolerant control of the open-circuit fault of the power switches and the phase-leg fault can both be achieved by the proposed method. Experimental results are given to verify that the proposed fault-tolerant three-level T-type inverter can output the full voltage level and power during the fault-tolerant operation based on the proposed control strategy.

Abstract As More/All Electric Aircraft gradually become a research hotspot, electromechanical actuators (EMAs), which can directly convert electrical energy into mechanical energy, have gained more and more attention. However, since the reliability of EMA cannot meet the requirements of actual aircrafts, the practical application of EMA is severely limited. Therefore, fault diagnosis, prognosis and health management (DPHM), which can realise condition‐based maintenance (CBM), has become the key technology in the application of EMA. The aim is to summarise the research on EMA fault modes, fault diagnosis, prognosis and health management systematically and comprehensively. First, the basic structure and common fault modes of EMAs are introduced, and the failure mechanism of EMA is studied. Then, the algorithms of DPHM for EMAs are reviewed in detail. The perception strategies of data acquisition are analysed, and the EMA fault diagnosis methods, including model‐based and data‐driven methods, are reviewed. The research of remaining useful life (RUL) prediction and fault‐tolerant control are introduced. After that, some problems of the existing research on EMA DPHM and their potential solutions are put forward. Finally, several possible developing directions of research on EMA DPHM are predicted.

Reliable and real-time active diagnosis of system faults with uncertainties is strongly dependent on the input design. This paper establishes a data-driven framework for integrated design of active fault diagnosis and control while ensuring the tracking performance. To be specific, the input design is formulated as a constrained optimization problem that can be solved with the aid of constrained reinforcement learning algorithms. Moreover, based on the maximum mean discrepancy metric, a novel active fault isolation scheme is proposed to implement model discrimination using system outputs. At the end, the effectiveness of the proposed approach is evaluated in two case studies in the presence of probabilistic disturbances and uncertainties. • A data-driven framework for active fault diagnosis with tracking performance guarantees. • Constrained reinforcement learning is applied in the integrated design of active inputs. • A fault isolation strategy to implement model discrimination based on system outputs. [ABSTRACT FROM AUTHOR]

Three-phase grid-connected inverters have been widely used in the distributed generation system, and the current sensor has been applied in closed-loop control in inverters. When the current sensor offset faults occurs, partial fault features of multiple current sensors disappear from the closed-loop control grid-connected system, which leads to difficulties for fault diagnostics and fault-tolerant control. This paper proposes a fault tolerance method based on average current compensation mode to eliminate these adverse effects of fault features. The average current compensation mode compensates the average of the three-phase current to the αβ axis current to realize the fault feature reconstruction of the current sensor. The mode does not affect the normal condition of the system. Then, the data-driven method is used for fault diagnosis, and the corresponding fault tolerant control model is selected according to the diagnosis results. Finally, the experimental results show that the proposed strategy has a good fault tolerance control performance and can improve the fault feature discrimination and diagnostic accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a novel prespecified finite-time and overshoot-restrained fault-tolerant tracking control scheme to compensate the intermittent faults in linear uncertain systems. Starting from the system tracking error dynamics model, we design a speed excitation function to improve the response speed of the control. A finite-time performance index function is established in the zero-sum game framework for the fault-free H ∞ optimal control policy. Based on Lyapunov stability theory, a fault compensation oriented fault estimation and diagnosis method is proposed to ensure the uniformly ultimately bounded stability of tracking errors. It is noteworthy that the proposed speeding fault-tolerant control can accelerate the trajectory tracking, narrow the upper bound of tracking errors and restrain the overshoot. Numerical and practical experiments fully illustrate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

A novel diagnosis method based on the rotor slip is proposed in the paper to correctly detect current and speed sensor failures during the induction motor drive (IMD) operation. In order to enhance reliability and avoid confusion in the diagnosis algorithm due to the influence of measured signal quality, each fault type is determined in a priority order defined by the diagnosis method. Based on the features of the IMD applying the field-oriented control (FOC) technique, an innovative model uses the measured currents and reference speed as the input signals to estimate the rotor slip for the current sensor fault detection. After verifying the quality of the feedback of the current signals, a speed sensor fault function is continued, and performs according to relations among the reference speed, estimated speed based on the sliding mode method, and measured rotor speeds. Finally, the estimated quantities are selected to replace the wrong measured current or speed signals. The feasibility of the proposed approach is verified by simulations using Matlab-Simulink software as well as by practical experiments using an IMD prototype with a rated power of 2.2 kW and a DSC-TMS320F28335-based control system. The obtained simulation and experimental results demonstrated the feasibility, effectiveness, and reliability of the proposed diagnosis technique in detecting sensor failures and maintaining the stable operation of the IMD. [ABSTRACT FROM AUTHOR]

As More/All Electric Aircraft gradually become a research hotspot, electromechanical actuators (EMAs), which can directly convert electrical energy into mechanical energy, have gained more and more attention. However, since the reliability of EMA cannot meet the requirements of actual aircrafts, the practical application of EMA is severely limited. Therefore, fault diagnosis, prognosis and health management (DPHM), which can realise condition‐based maintenance (CBM), has become the key technology in the application of EMA. The aim is to summarise the research on EMA fault modes, fault diagnosis, prognosis and health management systematically and comprehensively. First, the basic structure and common fault modes of EMAs are introduced, and the failure mechanism of EMA is studied. Then, the algorithms of DPHM for EMAs are reviewed in detail. The perception strategies of data acquisition are analysed, and the EMA fault diagnosis methods, including model‐based and data‐driven methods, are reviewed. The research of remaining useful life (RUL) prediction and fault‐tolerant control are introduced. After that, some problems of the existing research on EMA DPHM and their potential solutions are put forward. Finally, several possible developing directions of research on EMA DPHM are predicted. [ABSTRACT FROM AUTHOR]

Wind turbines are playing an increasingly important role in renewable power generation. Their complex and large-scale structure, however, and operation in remote locations with harsh environmental conditions and highly variable stochastic loads make fault occurrence inevitable. Early detection and location of faults are vital for maintaining a high degree of availability and reducing maintenance costs. Hence, the deployment of algorithms capable of continuously monitoring and diagnosing potential faults and mitigating their effects before they evolve into failures is crucial. Fault diagnosis and fault tolerant control designs have been the subject of intensive research in the past decades. Significant progress has been made and several methods and control algorithms have been proposed in the literature. This paper provides an overview of the most recent fault diagnosis and fault tolerant control techniques for wind turbines. Following a brief discussion of the typical faults, the most commonly used model-based, data-driven and signal-based approaches are discussed. Passive and active fault tolerant control approaches are also highlighted and relevant publications are discussed. Future development tendencies in fault diagnosis and fault tolerant control of wind turbines are also briefly stated. The paper is written in a tutorial manner to provide a comprehensive overview of this research topic. [ABSTRACT FROM AUTHOR]

Large-scale heat pumps are a promising technology for the decarbonisation of heat supplied in buildings and industries, provided they operate as expected. However, common faults like fouling and unplanned downtime periods can significantly affect their performance and availability. This could limit the widespread adoption of large-scale heat pumps over other heating technologies such as gas and electric boilers. Approaches described in the literature to optimize the operation of large-scale heat pumps often lack validation under real-world conditions and do not account for performance degradation due to faults. This work demonstrates a step towards utilizing digital twins to improve the energy performance of a commercial large-scale heat pump affected by fouling. A framework was proposed based on the real-time adaptation of digital twins, where a simulation model was calibrated online based on measurements from the heat pump in operation, which was then used for set point optimization. This enabled to determine optimal intermediate pressure set points in the heat pump operating under varying levels of fouling over time. The framework was tested on different periods of heat pump operation spread over ten calendar months. The results showed that the use of online calibration rather than a single calibration decreased performance estimation errors between 3 and 17 percentage points. Moreover, the set points determined by the online-calibrated model, along with a simpler polynomial model derived from it, showed improvements in the heat pump performance by up to 3%, depending on the level of fouling. The findings of this study demonstrated the potential to extend the proposed framework using digital twins to enhance the energy efficiency of large-scale heat pumps. • Use of a model calibrated online to simulate a two-stage ammonia heat pump. • Online calibration enabled to assess fouling growth and mitigation in real-time. • Intermediate pressure set points were optimized through the online calibrated model. • Online calibration improved performance estimations by 3 to 17 percentage points. • Model-based fouling monitoring was beneficial for the set point optimization. [ABSTRACT FROM AUTHOR]

This article solves the fault estimation and fault‐tolerant control problem for discrete‐time hybrid systems containing actuator and sensor faults. A novel extended state observer is shown to estimate states and faults of systems, simultaneously. Based on the utilized estimations, a fault‐tolerant controller is proposed so that stochastic stability of closed‐loop models with H∞$$ {H}_{\infty } $$ level is analyzed and sufficient conditions are obtained. A simulation example is given to prove this proposed strategy's effectiveness. [ABSTRACT FROM AUTHOR]

This article proposes an improved method for the position signal evaluation of a switched reluctance motor (SRM) drives. It can perform accurate position signal reconstruction based on the inductance, and greatly increase the fault tolerance of SRM in complex environments. It includes the position signal fault diagnosis (PSFD), position signal estimation, and fault-tolerant control (FTC). First, the installation and principle of the position sensor is introduced to show the function of the position signal in SRM drive system. Then, to overcome the limitation of application range of the conventional diagnosis method, a new PSFD method based on grey prediction model is proposed. Besides, a position estimation method based on the inflection point of the inductance is proposed. According to the estimated position, FTCs are carried out when position sensors are faulty. Finally, experiments are carried out to validate the effectiveness of the proposed position signal fault-tolerant control method based on a 12/10 six phase SRM. [ABSTRACT FROM AUTHOR]

This paper proposes a fault diagnosis system for inverters based on a cerebellar model articulation controller (CMAC). First, a three-level T-type inverter was implemented and used to create a three-level T-type inverter test environment for measuring the output voltage waveforms of faulty power transistors on the main inverter circuit under different output frequencies. The measured waveforms were processed using a fast Fourier transform (FFT) algorithm to create frequency spectrum diagrams and extract the characteristic spectra of corresponding faulty switches. Then, the associations of the spectra were determined and applied as training data for the CMAC to detect the positions of the faulty power transistors. The test results demonstrated that the proposed induction motor fault diagnosis system is capable of fast algorithm, requires less data to train, and has excellent accuracy of identification, with an error margin of ±5%. The detection results were then processed using a fault-tolerant controller (FTC) to enhance the reliability of the proposed system. Finally, some simulations and experimental results were conducted and analyzed to validate the feasibility of the proposed FTC system. [ABSTRACT FROM AUTHOR]

This paper deals with the development of a novel fault-tolerant control technique aiming at the diagnosis and accommodation of inter-turn short circuit faults in permanent magnet synchronous motors for lightweight UAV propulsion. The reference motor is driven by a four-leg converter, which can be reconfigured in case of a phase fault by enabling the control of the central point of the motor Y-connection. A crucial design point entails the development of fault detection and isolation (FDI) algorithms capable of minimizing the failure transients and avoiding the short circuit extension. The proposed fault-tolerant control is composed of two sections: the first one applies a novel FDI algorithm for short circuit faults based on the trajectory tracking of the motor current phasor in the Clarke plane; the second one implements the fault accommodation, by applying a reference frame transformation technique to the post-fault commands. The control effectiveness is assessed via nonlinear simulations by characterizing the FDI latency and the post-fault performances. The proposed technique demonstrates excellent potentialities: the FDI algorithm simultaneously detects and isolates the considered faults, even with very limited extensions, during both stationary and unsteady operating conditions. In addition, the proposed accommodation technique is very effective in minimizing the post-fault torque ripples. [ABSTRACT FROM AUTHOR]

Background Many faults occur in the modular multi-level converters (MMCs), including unbalancing capacitor voltage, lower and upper arm unbalancing, the line to line voltage unbalancing, sensors and actuators fault, system fault, and sub-modules fault in high as well as medium voltage applications. Introduction Several fault-tolerant approaches are presented to overcome these problems, such as active fault-tolerant control system (AFTCS), passive fault-tolerant control system (PFTCS), hybrid fault-tolerant control system (HFTCS), redundant system technique, special power circuit with the controller, and zero sequence voltage methods, which we will explain extensively in this article. Methodology This review emphasizes the types of faults in the MMCs and discusses the protection methods under failure conditions. The MMC is more popular in high voltage applications because it not only improves the quality of the grid but also has good harmonic performance in high power transmission. There is no need for any isolated dc sources to operate it. When faults are removed, the efficiency and reliability of the system will be increased. Results This extensive explanation of the current literature on MMC fault diagnosis and control techniques will conclude which methods provide a more valuable solution. Finally, this paper discusses the best approach to reduce MMC faults and provides a future research direction to the readers. [ABSTRACT FROM AUTHOR]

Fault diagnosis is studied based on the system type, which facilitates the realization of the engineering configuration and improves the diagnosis efficiency. The fault-tolerant control method is unified based on the concept of fault compensation. According to the dynamic characteristics of the system, the method takes the boundary value of no-fault signal fluctuation as the basis for fault detection, then takes the changing intensity of the solenoid valve control signal after the fault occurs as the fault location basis. Finally, it takes the difference or ratio of the signals before and after the fault occurs as the fault estimation. For the basis of fault separation, the integral value of the fitting equation between the fault signal and time is used as the Eigenvalue of fault type separation to comprehend fault separation. A program is written in C++ and combined with MATLAB/S-Fun function to realize fault tolerance. At the same time, the dynamic model calibration and real-time fault diagnosis, and fault-tolerant control process of sensor fault diagnosis are provided, which makes it suitable for general engineering feedforward-feedback systems and has a certain suppression effect on noise. The simulation results verify that the method is not only viable and it is exact. [ABSTRACT FROM AUTHOR]

The actuator fault-tolerant control problem for a variable-pitch quadrotor is addressed under uncertain conditions. Following a model-based approach, the plant nonlinear dynamics are faced with a disturbance observer-based control and a sequential quadratic programming control allocation, where only kinematic data of the onboard inertial measurement unit are required for the fault-tolerant control, i.e., it does not require the measurement of the motor speed nor the current drawn by the actuators. In the case of almost horizontal wind, a single observer handles both faults and the external disturbance. The estimation of the wind is fed forward by the controller, while the actuator fault estimation is exploited in the control allocation layer, which copes with the variable-pitch nonlinear dynamics, thrust saturation, and rate limits. Numerical simulations in the presence of measurement noise show the capability of the scheme to handle multiple actuator faults in a windy environment.

This paper presents a comprehensive study of model-based fault diagnosis (FD) and a fault-tolerant control (FTC) scheme for sensor and actuator faults of turbojet engines. For actuator FD, an unbiased estimation scheme with a modified Kalman filter (KF) was developed. For sensor FD, two approaches, the generalized likelihood ratio with robust KF and the pseudo actuator model with modified KF, were investigated in a comparative study. For fault detection and isolation, test statistics are commonly employed to detect fault behavior. For FTC, integral-type sliding mode control using control reconfiguration and the reconstruction of the sensor signal was adopted with the FD schemes. The effectiveness of the employed methods was demonstrated in this study and discussed with numerical simulations.

The safety of direct torque control (DTC) is strongly reliant on the accuracy and consistency of sensor measurement data. A fault-tolerant control paradigm based on a dual-torque model is proposed in this study. By introducing the vector product and scalar product of the stator flux and stator current vector, a new state variable is selected to derive a new dual-torque model of induction motor; it is combined with a current observer to propose a dual-torque model fault-tolerant control method. This technology calculates torque and reactive torque directly, reducing the system’s reliance on sensors, avoiding sensor-noise interference, and improving torque response speed while suppressing torque ripple. In addition, to improve system dependability and safety, a fault-tolerant control method is devised by combining the model with an adaptive virtual current observer. Ultimately, experiments validate the suggested method’s effectiveness and feasibility.

A fault diagnosis algorithm using a deep neural network for an octocopter Unmanned Aerial Vehicle (UAV) is proposed. All eight rotors are considered in the multiclass classification fault diagnosis problem. The latest angle time history is fed to the proposed algorithm to determine rotor failure in real time. The normal case and fault case of each rotor are considered with appropriate output pairs to form a dataset. The proposed classifier can distinguish a failed rotor from the others with the help of different patterns of Euler angles during the training process. Two hidden layers are constructed using sigmoid and softmax activation functions. A generalized delta rule is adopted, and a stochastic gradient descent scheme is used to calculate the weight update of the neural network. The proposed fault diagnosis algorithm can be augmented to a fault-tolerant controller to construct an integrated system that involves solving a convex optimization problem. Numerical simulations are conducted to validate the performance of the proposed diagnostic algorithm. It is demonstrated that the performance can be adjusted by controlling the design parameters. [ABSTRACT FROM AUTHOR]