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This paper aims to clarify voltage sourced converter’s (VSC’s) influence rules on the alternating current (AC) short-circuit current and identify the key factors, so as to propose the short-circuit current suppression strategy.

This paper investigates the key factors which impact the short-circuit current supplied by the VSC based on the equivalent current source model. This study shows that the phase of the VSC equivalent current source is mainly affected by the type of fault, whereas the amplitude is mainly decided by the control mode, the amplitude limiter and the electrical distance. Based on the above influence mechanism, the dynamic limiter with short-circuit current limiting function is designed. The theoretical analysis is verified by simulations on PSCAD.

The short-circuit current feeding from VSC is closely related to the control mode and control parameters of the VSC, fault type at AC side and the electrical distance of the fault point. The proposed dynamic limiter can make VSC absorb more reactive power to suppress the short-circuit current.

The dynamic limiter proposed in this paper is limited to suppress three-phase short-circuit fault current. The future work will focus more on improving and extending the dynamic limiter to the fault current suppression application in other fault scenarios.

The research results provide a reference for the design of protection system.

The key influence factors are conducive to put forward the measures to suppress the fault current, eliminate the risk of short-circuit current exceeding the standard and reduce the difficulty of protection design.

This paper aims to address the spacecraft attitude regulation problem in the presence of extrinsic disturbances and actuator faults.

Based on adaptive backstepping design technique, a new concise adaptive dual-mode control scheme is proposed, which can either use the fault information detected by fault diagnosis mechanisms or switch to the fault-unknown mode when the fault diagnosis information is non-existent for control signal generation. These two modes share an adaptive mechanism that reduces the complexity of the algorithm.

The new fault-tolerant attitude control algorithm can accommodate both modes with and without fault diagnosis mechanisms.

The proposed algorithm in this paper can be applied to both cases when the attitude control system is equipped with or without fault diagnosis capability. This also enhances the robustness of attitude control algorithm. This study performs numerical simulations and verifies that the algorithm could effectively adapt to both modes.

The purpose of this paper is to propose an adaptive neural-sliding mode-based observer for the estimation and reconstruction of unknown faults and disturbances for time-varying nonlinear systems such as aircraft, to ensure preciseness in the diagnosis of fault magnitude as well as the shape without enhancement of system complexity and cost. Fault-tolerant control (FTC) strategy based on adaptive neural-sliding mode is also proposed in the existence of faults for ensuring the stability of the faulty system.

In this paper, three strategies are presented: adaptive radial basis functions neural network (ARBFNN), conventional radial basis functions neural network (CRBFNN) and integral-chain differentiator. For the purpose of enhancement of fault diagnosis and isolation, a new sliding mode-based concept is introduced for the weight updating parameters of radial basis functions neural network (RBFNN).The main objective of updating the weight parameters adaptively is to enhance the effectiveness of fault diagnosis and isolation without increasing the computational complexities of the system. Results depict the effectiveness of the proposed ARBFNN approach in fault detection (FD) and approximation compared to CRBFNN, integral-chain differentiator and schemes existing in literature. In the second step, the FTC strategy is presented separately for each observer in the presence of unknown faults and failures for ensuring the stability of the system, which is validated on Boeing 747 100/200 aircraft.

The proposed adaptive neural-sliding mode approach is investigated, which depicts more effectiveness in numerous situations such as faults, disturbances and uncertainties compared to algorithms used in literature. In this paper, both the fault approximation and isolation and the fault tolerance approaches are studied.

For the enhancement of safety level as well as for avoiding any kind of damage, timely FD and fault tolerance have always had a significant role; therefore, the algorithms proposed in this research ensure the tolerance of faults and failures, which plays a vital role in practical life for avoiding any kind of damage.

In this study, a new neural-sliding mode concept is adopted for the adaptive faults approximation and reconstruction, and then the FTC algorithms are studied for each observer separately, whereas in previous studies, only the fault detection and isolation (FDI) or the fault tolerance problems were studied. Results demonstrate the effectiveness of the proposed strategy compared to the approaches given in the literature.

To solve the above problems and ensure the stability of the ad hoc network node topology in the process of wireless signal transmission, this paper aims to design a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.

This paper designs a robust adaptive sliding film fault-tolerant controller under the nonlinear distortion of signal transmission in an amorphous flat air-to-ground wireless ad hoc network system.

The simulation results show that the amorphous flat wireless self-organizing network system has good nonlinear distortion fault-tolerant correction ability under the feedback control of the designed controller, and the system has the asymptotically stable convergence ability; the test results show: the node topology of the self-organizing network structural stability is significantly improved, which provides a foundation for the subsequent realization of long-distance transmission of ad hoc network nodes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further.

The controller can extract the fault information caused by nonlinear distortion in the wireless signal transmission process, and at the same time, its feedback matrix K can gradually converge the generated wireless signal error to zero, to realize the stable transmission of the wireless signal.

The paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, this paper aims to propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the system to distribute to solve the problem of control and communication failure at the same time.

In the paper, the authors propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network-integrated system.

The results show that the integrated system has good robustness and fault tolerance performance indicators for flight control and wireless signal transmission when confronted with external disturbances, internal actuator failures and wireless network associated failures and the flight control curve of the quadrotor unmanned aerial vehicle (UAV) is generally smooth and stable, even if it encounters external disturbances and actuator failures, its fault tolerance performance is very good. Then in the range of 400–800 m wireless communication distance, the success rate of wireless signal loop transmission is stable at 80%–100% and the performance is at least relatively improved by 158.823%.

This paper takes the air-ground integrated wireless ad hoc network-integrated system as the research object, based on the robust fault-tolerant control algorithm, the authors propose a distributed robust H_∞ adaptive fault-tolerant control algorithm suitable for the system and through the Riccati equation and linear matrix inequation method, the designed distributed robust H_∞ adaptive fault-tolerant controller further optimizes the fault suppression factor γ, so as to break through the limitation of only one Lyapunov matrix for different fault modes to distribute to solve the problem of control and communication failure at the same time.

The purpose of this paper, is to solve the problem of finite-time fault-tolerant attitude synchronization and tracking control of multiple rigid bodies in presence of model uncertainty, external disturbances, actuator faults and saturation. It is assumed that the rigid bodies in the formation may encounter loss of effectiveness and/or bias actuator faults.

For the purpose, adaptive terminal sliding mode control and neural network structure are used, and a new sliding surface is proposed to guarantee known finite-time convergence not only at the reaching phase but also on the sliding surface. The sliding surface is then modified using a proposed auxiliary system to maintain stability under actuator saturation.

Assuming that the communication topology between the rigid bodies is governed by an undirected connected graph and the upper bounds on the actuators’ faults, estimation error of model uncertainty and external disturbance are unknown, not only the attitudes of the rigid bodies in the formation are synchronized but also they track the time-varying attitude of a virtual leader. Using Lyapunov stability approach, finite-time stability of the proposed control algorithms demonstrated on the sliding phase as well as the reaching phase. The effectiveness of the proposed algorithm is also validated by simulation.

The proposed controller has the advantage that the need for any fault detection and diagnosis mechanism and the upper bounds information on estimation error and external disturbance is eliminated.

In this paper, the authors take an amorphous flattened air-ground wireless self-assembling network system as the research object and focus on solving the wireless self-assembling network topology instability problem caused by unknown control communication faults during the operation of this system.

In the paper, the authors propose a neural network-based direct robust adaptive non-fragile fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network integrated system.

The simulation results show that the system eventually tends to be asymptotically stable, and the estimation error asymptotically tends to zero with the feedback adjustment of the designed controller. The system as a whole has good fault tolerance performance and autonomous learning approximation performance. The experimental results show that the wireless self-assembled network topology has good stability performance and can change flexibly and adaptively with scene changes. The stability performance of the wireless self-assembled network topology is improved by 66.7% at maximum.

The research results may lack generalisability because of the chosen research approach. Therefore, researchers are encouraged to test the proposed propositions further.

This paper designs a direct, robust, non-fragile adaptive neural network fault-tolerant controller based on the Lyapunov stability principle and neural network learning capability. By directly optimizing the feedback matrix K to approximate the robust fault-tolerant correction factor, the neural network adaptive adjustment factor enables the system as a whole to resist unknown control and communication failures during operation, thus achieving the goal of stable wireless self-assembled network topology.

The purpose of the paper is to design a nonlinear dynamic inversion (NDI) based robust fault-tolerant control (FTC) for aircraft longitudinal dynamics subject to system nonlinearities, aerodynamic parametric variations, external wind disturbances and fault/failure in actuator.

An uncertainty and disturbance estimator (UDE) technique is used to provide estimate of total disturbance enabling its rejection and thereby achieving robustness to the proposed NDI controller. As needed in the NDI design, the successive derivatives of the output are obtained through an UDE robustified observer making the design implementable. Further, a control allocation scheme consigns control command from primary actuator to the secondary one in the event of fault/failure in the primary actuator.

The robustness is achieved against the perturbations mentioned above in the presence of actuator fault/failure.

Lyapunov analysis proves practical stability of the controller–observer structure. The efficacy and superiority of the proposed design has been demonstrated through Monte-Carlo simulation.

Unlike in many FTC designs, robustness is provided against system nonlinearities, aerodynamic parametric variations, external wind disturbances and sinusoidal input disturbance using a single control law which caters for fault-free, as well as faulty actuator scenario.

This paper aims to study the reliability of the high-speed train operation control system in the Chinese Train Control System Level 3 (CTCS-3) operating mode.

Dynamic fault tree and Bayesian network method are adopted to analyze the reliability and weakness of the CTCS-3 system.

First, a physical architecture and data flow diagram of the CTCS-3 system are established according to the typical structure and functions of the CTCS-3 system. Second, the dynamic fault tree of the CTCS-3 system is constructed. Considering the prior probability of the bottom event and the existence of dynamic redundancy, the dynamic fault tree is transformed into a Bayesian net. The reliability of the CTCS-3 system is carried out based on the prior probability and the weakness that affects the reliability of the system based on the posterior probability is also analyzed by the Bayesian network. Finally, it is disclosed that the impact of the on-board subsystem on the reliability of the CTCS-3 system is generally greater than that of the ground subsystem. The two weakest modules in the onboard subsystem are the driver-machine interface (DMI) and balise transmission module (BTM) and the weakest one in the ground subsystem is Balise. The analysis results are generally consistent with the malfunctions in the field operation of China’s high-speed railway.

(1) By reasoning, the reliability of the train operation control system in the CTCS-3 operating mode meets the standard requirements.

(2) Through backward reasoning, it is found that the failure of the onboard subsystem leads to a greater probability of failure of the train control system.

(3) The DMI, BTM and automatic train protection computer unit modules are weak components in the onboard subsystem. Vital digit input&output, train interface unit and train security gateway are rarely involved in previous research, the result in this paper shows that these three modules are also weak components in the subsystem, which requires attention.

Quantitative reliability analysis can effectively identify the time the driving system needs to be maintained. Then, the potential safety problems can be found, and some catastrophic failures can be effectively prevented. Therefore, this paper aims to evaluate the reliability of the switched reluctance generator (SRG) driving system.

In this paper, a method considering different thermal stresses and fault tolerance capacity is proposed to analyze the reliability of an SRG. A full-bridge power converter (FBPC) instead of the asymmetric half-bridge power converter (AHBPC) is adopted to drive the SRG system. First, the primary fault modes of the SRG system are introduced, and a fault criterion is proposed to determine whether the system fails. Second, the thermal circuit model of the converter is established to quickly and accurately obtain the junction temperature of the devices. At last, the Markov models of different levels are established to evaluate the reliability of the system.

The results show that the two-level Markov model is the most suitable when compared to the static model and the one-level Markov model.

The driving system of SRG will be more reliable after the reliability of the system is evaluated by the Markov model. At the same time, an FBPC is adopted to drive the SRG. The FBPCs have the advantages of fewer switching devices, higher integration and lower cost. The proposed driving strategy of the FBPC avoids the current reversal and the generation of dead zone time, which has the advantage of reliable operation. In addition, a precise thermal circuit model of the FBPC is proposed, and the junction temperature of each device can be obtained, respectively.