Active Fault Tolerant Nonsingular Terminal Sliding Mode Control for Electromechanical System Based on Support Vector Machine

Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this paper.By borrowing the advantages of model-driven and data-driven methods,a fault tolerant nonsingular terminal sliding mode control method based on support vector machine(SVM)is proposed.A SVM is designed to estimate the fault by off-line learning from small sample data with solving convex quadratic programming method and is introduced into a high-gain observer,so as to improve the state estimation and fault detection accuracy when the fault occurs.The state estimation value of the observer is used for state reconfiguration.A novel nonsingular terminal sliding mode surface is designed,and Lyapunov theorem is used to derive a parameter adaptation law and a control law.It is guaranteed that the proposed controller can achieve asymptotical stability which is superior to many advanced fault-tolerant controllers.In addition,the parameter estimation also can help to diagnose the system faults because the faults can be reflected by the parameters variation.Extensive comparative simulation and experimental results illustrate the effectiveness and advancement of the proposed controller compared with several other main-stream controllers.

FAULT-TOLERANT INTEGRATED NAVIGATION SYSTEM BASED ON NEURONS

In this paper, the multisensor data fusion technique of a fault tolerant integrated navigation system is discussed. A neural approach for data fusion is proposed for multisensor integrated systems. The simulation results show that this neural approach for data fusion is feasible.

Fault tolerant control of electric pitch control system based on single current detection

In view of the current sensors failure in electric pitch system,a variable universe fuzzy fault tolerant control method of electric pitch control system based on single current detection is proposed.When there is single or two-current sensor fault occurs,based on the proposed method the missing current information can be reconstructed by using direct current（DC）bus current sensor and the three-phase current can be updated in time within any two adjacent sampling periods,so as to ensure stability of the closed-loop system.And then the switchover and fault tolerant control of fault current sensor would be accomplished by fault diagnosis method based on adaptive threshold judgment.For the reconstructed signal error caused by the modulation method and the main control target of electric pitch system,a variable universe fuzzy control method is used in the speed loop,which can improve the anti-disturbance ability to load variation,and the robustness of fault tolerance system.The results show that the fault tolerant control method makes the variable pitch control system still has ideal control characteristics in case of sensor failure although part of the system performance is lost,thus the correctness of the proposed method is verified.

T-PBFT: An EigenTrust-Based Practical Byzantine Fault Tolerance Consensus Algorithm

Blockchain with these characteristics of decentralized structure, transparent and credible, time-series and immutability, has been considering as a promising technology. Consensus algorithm as one of the core techniques of blockchain directly affects the scalability of blockchain systems. Existing probabilistic finality blockchain consensus algorithms such as PoW, PoS, suffer from power consumptions and low efficiency;while absolute finality blockchain consensus algorithms such as PBFT, HoneyBadgerBFT, could not meet the scalability requirement in a largescale network. In this paper, we propose a novel optimized practical Byzantine fault tolerance consensus algorithm based on EigenTrust model, namely T-PBFT, which is a multi-stage consensus algorithm. It evaluates node trust by the transactions between nodes so that the high quality of nodes in the network will be selected to construct a consensus group. To reduce the probability of view change, we propose to replace a single primary node with a primary group. By group signature and mutual supervision, we can enhance the robustness of the primary group further. Finally, we analyze T-PBFT and compare it with the other Byzantine fault tolerant consensus algorithms. Theoretical analysis shows that our T-PBFT can optimize the Byzantine fault-tolerant rate,reduce the probability of view change and communication complexity.

Data-based Fault Tolerant Control for Affine Nonlinear Systems Through Particle Swarm Optimized Neural Networks

In this paper, a data-based fault tolerant control(FTC) scheme is investigated for unknown continuous-time(CT)affine nonlinear systems with actuator faults. First, a neural network(NN) identifier based on particle swarm optimization(PSO) is constructed to model the unknown system dynamics. By utilizing the estimated system states, the particle swarm optimized critic neural network(PSOCNN) is employed to solve the Hamilton-Jacobi-Bellman equation(HJBE) more efficiently.Then, a data-based FTC scheme, which consists of the NN identifier and the fault compensator, is proposed to achieve actuator fault tolerance. The stability of the closed-loop system under actuator faults is guaranteed by the Lyapunov stability theorem. Finally, simulations are provided to demonstrate the effectiveness of the developed method.

Fault Tolerant Control for Networked Control Systems with Packet Loss and Time Delay

In this paper,a fault tolerant control with the consideration of actuator fault for a networked control system （NCS） with packet loss is addressed.The NCS with data packet loss can be described as a switched system model.Packet loss dependent Lyapunov function is used and a fault tolerant controller is proposed respectively for arbitrary packet loss process and Markovian packet loss process.Considering a controlled plant with external energy-bounded disturbance,a robust H ∞ fault tolerant controller is designed for the NCS.These results are also expanded to the NCS with packet loss and networked-induced delay.Numerical examples are given to illustrate the effectiveness of the proposed design method.

Deep Learning Based Data Fusion for Sensor Fault Diagnosis and Tolerance in Autonomous Vehicles

Environmental perception is one of the key technologies to realize autonomous vehicles.Autonomous vehicles are often equipped with multiple sensors to form a multi-source environmental perception system.Those sensors are very sensitive to light or background conditions,which will introduce a variety of global and local fault signals that bring great safety risks to autonomous driving system during long-term running.In this paper,a real-time data fusion network with fault diagnosis and fault tolerance mechanism is designed.By introducing prior features to realize the lightweight network,the features of the input data can be extracted in real time.A new sensor reliability evaluation method is proposed by calculating the global and local confidence of sensors.Through the temporal and spatial correlation between sensor data,the sensor redundancy is utilized to diagnose the local and global confidence level of sensor data in real time,eliminate the fault data,and ensure the accuracy and reliability of data fusion.Experiments show that the network achieves state-of-the-art results in speed and accuracy,and can accurately detect the location of the target when some sensors are out of focus or out of order.The fusion framework proposed in this paper is proved to be effective for intelligent vehicles in terms of real-time performance and reliability.

Driving Circuit for AMOLED with Fault Tolerance

The defects of an OLED-based display,mainly electrical shorts,cause pixels to stay dark,decrease the brightness of a panel,severely influence the display uniformity,and also consume a considerable amount of power. In this paper, for AM-OLEDs, a novel circuit employing p-type low-temperature poly-Si thin-film transistors is introduced to offer fault-tolerant capabilities for such defects. The results show that this circuit can save significant power and maintain the luminance of the pixel without changing the driving current.

Model-Based Fault Tolerant Control for Hybrid Dynamic Systems with Sensor Faults

A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults. Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.

Open-circuit Fault-tolerant Control Strategy Based on Five-level Power Converter for SRM System

Switched reluctance motor power converters are prone to open-circuit faults because it need to withstand large voltages and currents.Due to the small number of traditional asymmetrical half bridge topology switches,it is difficult to carry out fault tolerant control when power converters has an open-circuit fault,resulting in larger output torque ripple.This paper presents a five-level power converter based on the traditional asymmetric half-bridge power converter.The five-level topology has more switching states and can work in multi-level mode.Based on the topology,different excitation and demagnetization voltages can be choose at different speeds.A fault-tolerance strategy is developed to decrease the influence of the open-circuit fault.The five-level power converter has four switches per phase,and two of them will be used in one of the operating mode.So the remaining two of the switches can be used for safe backup,enabling fault-tolerant control when an open-circuit occur.Since each phase of the five-level power converter proposed in this paper is independent of each other,a reasonable control strategy can be used to avoid the unbalance of the midpoint potential.Finally,the topology and fault-tolerant strategy proposed in this paper are verified by simulation and experiment.

MICROTHREAD BASED (MTB) COARSE GRAINED FAULT TOLERANCE SUPERSCALAR PROCESSOR ARCHITECTURE

Fault tolerance in microprocessor systems has become a popular topic of architecture research. Much work has been done at different levels to accomplish reliability against soft errors, and some fault tolerance architectures have been proposed. But little attention is paid to the thread level superscalar fault tolerance. This letter introduces microthread concept into superscalar processor fault tolerance domain, and puts forward a novel fault tolerance architecture, namely, MicroThread Based (MTB) coarse grained transient fault tolerance superscalar processor architecture, then discusses some detailed implementations.

Guaranteeing the Fault Transient Performance of Aerospace Multiphase Permanent Magnet Motor System: an Adaptive Robust Speed Control Approach

To enhance the fault transient performance of aerospace multiphase permanent magnet synchronous motor(PMSM)system,an adaptive robust speed control is proposed regardless of the phase open-circuit(OC)and short-circuit(SC)fault in this paper,which can be applied for both the redundant motor system and fault tolerant motor system.For aerospace multiphase PMSM system,besides external load disturbance and system parameter perturbation,there inevitably exists the electromagnetic torque ripple in fault transient process,which can degrade the system performance and even cause the system instability.To cope with this issue,the electromagnet torque ripple of the multiphase PMSM system in fault transient process is first analyzed.Then,by considering the electromagnet torque fluctuation caused by fault transient as a system uncertainty,a novel adaptive robust speed control scheme is proposed,while the adaptive law is constructed to emulate the total system uncertainty bound,which include the load disturbance,the parameter variation,and the electromagnetic torque fluctuation due to fault transient.The resulting control can ensure the speed control performance even in fault transient process regardless of the uncertainty,in which no prior estimation of the uncertainty bound is required.In addition,the proposed adaptive robust speed control is demonstrated by a six-phase PMSM experimental platform.The novelty of this research is to explore a novel adaptive robust speed control to strengthen the fault tolerance performance of multiphase PMSM system even in fault transient process,which requires no prior estimation of the uncertainty bound.

Policy driven and multi-agent based fault tolerance for Web services

This paper proposes a policy driven and multi-agent based model to enhance the fault tolerance and recovery capabilities of Web services in distributed environment. The evaluation function of fault specifications and the corresponding handling mechanisms of the services are both defined in policies, which are expressed in XML. During the implementation of the services,the occurrences of faults are monitored by the service monitor agent through the local knowledge on the faults. Such local knowledge is dynamically generated by the service policy agent through querying and parsing the service policies from the service policies repository. When the fault occurs, the service process agent will focus on the process of fault handling and service recovery, which will be directed with the actions defined in the policies upon the specific conditions. Such a policy driven and multi-agent based fault handling approach can address the issues of flexibility, automation and availability.

Twin model-based fault detection and tolerance approach for in-core self-powered neutron detectors

The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SPNDs are indispensable for reliable reactor management.To completely extract the correlated state information of SPNDs,we constructed a twin model based on a generalized regression neural network(GRNN)that represents the common relationships among overall signals.Faulty SPNDs were determined because of the functional concordance of the twin model and real monitoring sys-tems,which calculated the error probability distribution between the model outputs and real values.Fault detection follows a tolerance phase to reinforce the stability of the twin model in the case of massive failures.A weighted K-nearest neighbor model was employed to reasonably reconstruct the values of the faulty signals and guarantee data purity.The experimental evaluation of the proposed method showed promising results,with excellent output consistency and high detection accuracy for both single-and multiple-point faulty SPNDs.For unexpected excessive failures,the proposed tolerance approach can efficiently repair fault behaviors and enhance the prediction performance of the twin model.

Fault tolerant control for a robot collaborative system

A new fault-tolerant control scheme is proposed for a nonlinear collaborative system that contains two robot subsystems. When fault occurs in one subsystem, the fault-free subsystem is used to compensate the fault influence of the faulty one on the whole collaborative system. When the faulty subsystem could not repair itself or the repair process needs a long time, the controller of the fault-free subsystem is reconfigured using the fault diagnosis information and other measured infor- mation, leading to the fault tolerant control of the robot collaborative system. Simulations of fault tolerant control for the robot collaborative system show the effectiveness of the proposed method.

Fault tolerant synchronization of chaotic systems based on T-S fuzzy model with fuzzy sampled-data controller

In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi Sugeno （T-S） fuzzy model is employed to represent the chaotic system dynamics. To acquire good performance and produce a less conservative analysis result, a new parameter-dependent Lyapunov-Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.

DECENTRALIZED OUTPUT FEEDBACK FAULT一TOLERANT CONTROL FOR UNCERTAIN LARGE一SCALE SYSTEMS

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Achieving privacy-preserving big data aggregation with fault tolerance in smart grid

In a smart grid, a huge amount of data is collected for various applications, such as load monitoring and demand response. These data are used for analyzing the power state and formulating the optimal dispatching strategy. However, these big energy data in terms of volume, velocity and variety raise concern over consumers＇ privacy. For instance, in order to optimize energy utilization and support demand response, numerous smart meters are installed at a consumer＇s home to collect energy consumption data at a fine granularity, but these fine-grained data may contain information on the appliances and thus the consumer＇s behaviors at home. In this paper, we propose a privacy-preserving data aggregation scheme based on secret sharing with fault tolerance in a smart grid, which ensures that the control center obtains the integrated data without compromising privacy. Meanwhile, we also consider fault tolerance and resistance to differential attack during the data aggregation. Finally, we perform a security analysis and performance evaluation of our scheme in comparison with the other similar schemes. The analysis shows that our scheme can meet the security requirement, and it also shows better performance than other popular methods.

Excellent Practical Byzantine Fault Tolerance

With the rapid development of blockchain technology,more and more people are paying attention to the consensus mechanism of blockchain.Practical Byzantine Fault Tolerance(PBFT),as the first efficient consensus algorithm solving the Byzantine Generals Problem,plays an important role.But PBFT also has its problems.First,it runs in a completely closed environment,and any node can't join or exit without rebooting the system.Second,the communication complexity in the network is as high as O(n2),which makes the algorithm only applicable to small-scale networks.For these problems,this paper proposes an Optimized consensus algorithm,Excellent Practical Byzantine Fault Tolerance(EPBFT),in which nodes can dynamically participate in the network by combining a view change protocol with a node's add or quit request.Besides,in each round of consensus,the algorithm will randomly select a coordination node.Through the cooperation of the primary and the coordination node,we reduce the network communication complexity to O(n).Besides,we have added a reputation credit mechanism and a wrong node removal protocol to the algorithm for clearing the faulty nodes in time and improving the robustness of the system.Finally,we design experiments to compare the performance of the PBFT and EPBFT algorithms.Through experimental,we found that compared with the PBFT algorithm,the EPBFT algorithm has a lower delay,communication complexity,better scalability,and more practical.

Analysis and modeling of resistive switching mechanism oriented to fault tolerance of resistive memory based on memristor

With the progress of the semiconductor industry, resistive memories, especially the memristor, have drawn increasing attention. The resistive memory based on memrsitor has not been commercialized mainly because of data error. Currently, there are more studies focused on fault tolerance of resistive memory. This paper studies the resistive switching mechanism which may have time-varying characteristics. Resistive switching mechanism is analyzed and its respective circuit model is established based on the memristor Spice model.