Fault-tolerant Method Research Articles

Redundancy-based intrusion tolerance approaches moving from classical fault tolerance methods

Redundancy-based intrusion tolerance approaches moving from classical fault tolerance methods

The Hall Sensors Fault-Tolerant for PMSM Based on Switching Sensorless Control With PI Parameters Optimization

The failure of Hall sensors can give rise to loss of rotor position and speed information, which can result in loss of control of the speed loop, spatial decoupling errors, and affecting system stability in three-phase PMSM control system. To solve this problem, a Hall fault-tolerant control system based on sensorless state switching is proposed in this paper. Firstly, a three-phase PMSM control system based on FOC is established to analyze and clarify the importance of rotor position and speed signals. Secondly, a detection scheme based on Hall change edge signal is designed to detect the health status of Hall sensors and implement fault-tolerant state switching. For the stability of the system, a sliding mode observer is built to obtain the back electromotive force(back-EMF). In addition, the phase-locked loop is designed to extract the rotor position and speed information from the back-EMF. When the system enters a fault-tolerant state, changes in the speed feedback loop can affect the control performance of the system. Therefore, the speed loop PI parameter optimization scheme based PSO algorithm is proposed to optimize the performance of the fault tolerant control system. Finally, the effectiveness of the fault-tolerant method based on the sensorless state switching after particle swarm optimization is verified on a semi-physical platform (RCP-HIL). The experimental results show that the Hall fault-tolerant control system proposed in this paper can effectively detect Hall sensor faults and cut into the fault-tolerant control state, and can maintain the control system stable during fault-tolerant state switching. Furthermore, the control system can maintain an observation error of ±30 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rpm</i> under variable load or variable speed conditions at medium and high speeds when the system enters fault-tolerant control state.

Multi Open-/Short-Circuit Fault-Tolerance Using Modified SVM Technique for Three-Level HANPC Converters

Open- and short-circuit faults are the most severe issues that affect the stability and reliability of power conversion systems. The space vector modulation (SVM) technique is widely used to control power converters. However, conventional SVM is incapable of controlling the system effectively when such faults occur. Considering these, this article proposes a modified SVM that is capable of tolerating the extreme cases of faults (including multi open-/short-circuit faults) simultaneously. An innovative fault tolerance method is proposed to tolerate multifaults in hybrid active neutral point converters (HANPCs). Furthermore, new voltage reference signals are created in addition to calculating voltage offset and inserting modified switching sequences. A descriptive performance analysis of the modified SVM technique is applied under healthy and faulty conditions. Correspondingly, the effects of the total harmonic distortion of the system performance are also highlighted and explained. The results reveal that the proposed control strategy can effectively maintain healthy and safe operation under faulty conditions without the need for additional parts or alteration of the topology configuration. In addition, the proposed method can be applied to HANPCs without special requirements to withstand high voltage levels. The effectiveness of the proposed method is verified by simulation and experimental results.

The AAPF fault-tolerant method for small and complex product assembly

Fault-tolerant control should be considered during assembly to ensure stability and efficiency of the assembly process. The paper proposes a fault-tolerant method to improve stability and efficiency during the assembly of small and complex products. The fault-tolerant method model was initially constructed, then an adaptive artificial potential field control algorithm (AAPF) was introduced to control related assembly tasks based on changes in assembly information. Next, active and passive fault tolerance methods were integrated using a least squares support vector machine (LS-SVM). Finally, the assembly of a 2P circuit breaker controller assembly with leakage protection was used as an example to verify the proposed assembly method. The experimental results demonstrated that the AAPF fault-tolerant method showed promising fault-tolerance capabilities for the assembly of small and complex products. Not only could it coordinate the number of tasks for each assembly robot, but it also effectively reduced the number of tasks that accumulated due to faults. The method proposed in this paper could effectively guarantee assembly stability and efficiency during small and complex product assembly.

A proactive failure tolerance method for LEO mega-constellation based on traffic engineering

The LEO mega-constellation has attracted increasing attention due to its potential for wide coverage,high throughput and low latency communication. However, given the complex space environment and its own characteristics,LEO mega-constellation needs to study the fault tolerance problem. Therefore, this paper focuses onhow to ensure that the network traffic is still forwarding without congestion after the failure of satellites.Specifically, a proactive fault-tolerant method called SN-FFC based on traffic engineering is proposed.The main idea is to make the network uncongested if the concurrent failures is up to $k$ ($k$ is a parameter) through reasonable link redundancy.SN-FFC first designs a fault-tolerant model based on traffic engineering, then proposes an algorithm based on dual theoryto solve the high computational complexity problem of the model, which reduces the complexity from $O(C_n^k)$ to $O(n)$.The simulation experiments based on the Starlink constellation model (first stage) show that SN-FFC can realize uncongested forwarding under failurescompared with the existing method, and can achieve low computing time and throughput cost.

DESIGN OF ON – LINE FAULT TOLERANT CONTROLLER

A new control strategy is implemented on a heat exchanger model using fault tolerant control (FTC) based on fault detection and isolation (FDI) techniques. The approach is used in implementing this strategy, namely on-line fault tolerant control. This approach is based on using state feedback technique in the design of the gain matrix. A heat exchanger, which represents a subsystem of many industrial systems is used to verify the ability of the proposed fault tolerant methods to compensate for all faults that may take place. The proposed FTC indicates that once FDI is applied, then effect of the fault on the system is reduced, thus preventing the need for any sudden stoppage of the system. The FDI unit is usually contained within the Fault tolerant control, hence enabling the continuous operation of the system close to nominal operating conditions.

Fault-tolerant strategy without redundant switches for PV systems based on differential power processing converters

Considering the failure risk and cost-effectiveness of photovoltaic (PV) systems with high granularity maximum power point tracking (MPPT), a fault-tolerant strategy without redundant switches is proposed for the PV system based on differential power processing (DPP) converters. This fault-tolerant strategy optimizes the output power of the PV system under different converter fault conditions by adjusting the coordinated operation of the DPP converter and the centralized converter. Compared to previous methods, in the case of hardware cost advantage, the proposed fault-tolerant strategy achieves the stable operation of the PV system after the converter failure and completes the targeted power optimization of all PV modules. The PV system with the proposed fault-tolerant strategy operates in three modes: distributed MPPT (DMPPT) mode, the coexistence of DMPPT and centralized MPPT (CMPPT) mode, and CMPPT mode. The PV system operates in the DMPPT mode when no switch failure occurs in the DPP converter. In the latter two post-fault operating modes, this paper proposes a simple fault-tolerant method to remove the faulty DPP converter and adjust the MPPT coverage of the centralized converter to recover the power loss caused by the fault. The experimental results validate the proposed fault-tolerant strategy.

A Novel Trade Transaction Agreement Algorithm Using Blockchain Consensus Mechanism

Blockchain, the underlying technology of Bitcoin, has been deeply studied in various fields after its development in recent years. As a typical decentralized distributed data storage system, consensus reached among all participants in a blockchain system requires a consensus mechanism to be realized. In order to make blockchain applicable to different application scenarios, different consensus mechanisms have been proposed. With the further development of blockchain applications, more and more studies have been conducted on the consensus mechanism. However, some existing consensus mechanisms still have some problems in various aspects. Therefore, this paper proposes a trade deal algorithm based on the blockchain mechanism of consensus. First of all, according to PBFT, the lack of a dynamic problem in the VPBFT voting mechanism was introduced. The node system is divided into four types with different responsibilities and gives the number of relations between nodes. When the number of nodes is changed, it can be calculated according to the quantity relation, ensuring dynamic. Second, a data anonymous transaction and authentication protocol is designed. In the protocol, when the seller sells data, the mapping relationship between the real identity and the false identity of the data owner is blinded and sent to the buyer. When the buyer wants to verify their identity, the seller’s identity can only be verified with the authentication of the blockchain. The proposed algorithm is superior to the current consensus in terms of time and energy consumption, throughput, and fault tolerance methods, which is proven through experimental tests and simulation analysis.

IMPROVEMENT OF SOFTWARE SYSTEMS FAULT TOLERANCE ENSURING ALGORITHMS

The study investigates the concepts of fault tolerance and methods of system responses to failures. The study is based on the research of modern resiliency patterns and common approaches of reaction to failures. During the research, the common unresolved issues with modern resiliency and fault tolerance approaches were defined. The study improved the method of the system response to failures by designing a comprehensive solution that includes refinement and expansion of classical patterns of fault tolerance as a proposal to resolve common problems. The new solution of fault tolerance is based on the combination of basic monitoring approaches, load balancing approaches, circuit breaker pattern, and re-designing of the sharding pattern to be applicable not only for databases but also for modern applications. The new solution is based on an automatic decision-making expert system, which based on anonymous data saved by the monitoring layer decides the root cause of the issue and validates which scenario is applicable for the current situation. Based on the decision system can either enable a user and load balancing approaches by isolating harmful users using improved sharding and load-balancing solutions or enable a circuit breaker to temporarily disable the faulty features. The new method of resiliency is supposed to prevent and reduce more errors compared to the existing solutions in the domain of fault tolerance and resiliency, thus the efficiency of the new approach is higher. The expediency and urgency of designing a new method of fault tolerance are substantiated by expressing the importance of resolving existing problems. Improved methods of automatic response and failure prevention, which allowed to reduce the number of errors that occur in the system compared to existing solutions in resiliency and fault tolerance.

Adaptive decentralized Kalman filters with non-common states for nonlinear systems

This paper presents two fault tolerance methods for decentralized Kalman filter with non-common states (DKF-NCS) for nonlinear systems. The DKF-NCS is used in a sensor network, where states are not uniform across all nodes. To detect and isolate faulty measurements, the χ2 test has been quite useful, where faulty measurements are detected based on the innovation error and innovation error covariance matrix. However, the innovation error and innovation error covariance matrix are dependent on the predicted state vector and its error covariance along with measurement model. The χ2 distribution test fails, if the predicted state vector is not consistent with its predicted error covariance matrix. Also, due to processing of set of measurements independently, fault detection happens more often in decentralized estimation compared to centralized estimation. Therefore, discarding the valid measurements based on χ2 detector may impact the performance of decentralized estimators significantly. To overcome this problem, we propose two adaptive fault tolerance methods. The first method handles faulty measurements at the assimilation step by applying weighted correction of the information and information matrix. The second method modifies the measurement noise matrix based on a closed-form solution, if fault is detected. These methods are validated using 100 simulation runs for a tracking problem. Overall, the proposed methods are demonstrated to be superior compared to the χ2 test and an existing adaptive extended Kalman filter.

SNR: S queezing N umerical R ange Defuses Bit Error Vulnerability Surface in Deep Neural Networks

As deep learning algorithms are widely adopted, an increasing number of them are positioned in embedded application domains with strict reliability constraints. The expenditure of significant resources to satisfy performance requirements in deep neural network accelerators has thinned out the margins for delivering safety in embedded deep learning applications, thus precluding the adoption of conventional fault tolerance methods. The potential of exploiting the inherent resilience characteristics of deep neural networks remains though unexplored, offering a promising low-cost path towards safety in embedded deep learning applications. This work demonstrates the possibility of such exploitation by juxtaposing the reduction of the vulnerability surface through the proper design of the quantization schemes with shaping the parameter distributions at each layer through the guidance offered by appropriate training methods, thus delivering deep neural networks of high resilience merely through algorithmic modifications. Unequaled error resilience characteristics can be thus injected into safety-critical deep learning applications to tolerate bit error rates of up to at absolutely zero hardware, energy, and performance costs while improving the error-free model accuracy even further.

A Complete Fault Tolerant Method for Extra Fault Diagnosability of Alternating Group Graphs

A network's diagnosability is the maximum number of faulty vertices that the network can discriminate solely by performing mutual tests among vertices. The original diagnosability without any condition is often rather low because it is bounded by the network's minimum degree. The h-extra fault diagnosability is an important and widely accepted diagnostic strategy as a new measure of diagnosability, which guarantees that the scale of every component is at least h+1 in the remaining system. Moreover, it increases the allowed faulty vertices, hence enhancing the diagnosability of the network. There have been lots of state-of-the-art literatures concerning the h-extra fault diagnosability. Although there are some methods to theoretically prove the extra fault diagnosability of some other well-known networks under MM* model, these methods have some serious flaws when there exists a 4-cycle in these networks. In this article, we investigate the reason that caused the flawed results in some references, and we derive a different, broadly applicable, and complete fault tolerant method to establish the extra fault diagnosability in an n-dimensional alternating group graph AG <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> under MM* model. The complete fault tolerant method adopts combinatorial properties and linearly many fault analysis to conquer the core of our proofs. Moreover, we compare the extra fault diagnosability of AG <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> with various types of fault diagnosability, including the diagnosability, strong diagnosability, conditional diagnosability, t/k-diagnosability, and pessimistic diagnosability. It can be seen that the extra fault diagnosability is greater than all the other types of fault diagnosability.

Cogsworth: Byzantine View Synchronization

Most methods for Byzantine fault tolerance (BFT) in the partial synchrony setting divide the local state of the nodes into views, and the transition from one view to the next dictates a leader change. In order to provide liveness, all honest nodes need to stay in the same view for a sufficiently long time. This requires \emph{view synchronization}, a requisite of BFT that we extract and formally define here. Existing approaches for Byzantine view synchronization incur quadratic communication (in $n$, the number of parties). A cascade of $O(n)$ view changes may thus result in $O(n^3)$ communication complexity. This paper presents a new Byzantine view synchronization algorithm named Cogsworth, that has optimistically linear communication complexity and constant latency. Faced with benign failures, Cogsworth has expected linear communication and constant latency. The result here serves as an important step towards reaching solutions that have overall quadratic communication, the known lower bound on Byzantine fault tolerant consensus. Cogsworth is particularly useful for a family of BFT protocols that already exhibit linear communication under various circumstances, but suffer quadratic overhead due to view synchronization.

Fault-tolerant scheme for robotic manipulator-Nonlinear robust back-stepping control with friction compensation.

Emerging applications of autonomous robots requiring stability and reliability cannot afford component failure to achieve operational objectives. Hence, identification and countermeasure of a fault is of utmost importance in mechatronics community. This research proposes a Fault-tolerant control (FTC) for a robot manipulator, which is based on a hybrid control scheme that uses an observer as well as a hardware redundancy strategy to improve the performance and efficiency in the presence of actuator and sensor faults. Considering a five Degree of Freedom (DoF) robotic manipulator, a dynamic LuGre friction model is derived which forms the basis for design of control law. For actuator’s and sensor’s FTC, an adaptive back-stepping methodology is used for fault estimation and the nominal control law is used for the controller reconfiguration and observer is designed. Fault detection is accomplished by comparing the actual and observed states, pursued by fault tolerant method using redundant sensors. The results affirm the effectiveness of the proposed FTC strategy with model-based friction compensation. Improved tracking performance as well robustness in the presence of friction and fault demonstrate the efficiency of the proposed control approach.

Nonlinear Gaussian Mixture Filtering with Intrinsic Fault Resistance

Because of limitations in onboard computing, spaceflight navigation has long been relegated to estimation processes that promote computational efficiency over increased model accuracy. Such is the case with fault tolerance methods, where residual editing is the most common practice to screen out erroneous sensor data. This work investigates an alternative approach, where sensor returns classified as faulty are not simply rejected, but are accounted for within the measurement model of the sensor, ultimately leading to a filter with intrinsic fault resistance in lieu of supplementary extensions like residual editing. Several different faulty measurement models are examined by comparing the proposed filter to a baseline filter outfitted with residual editing, where analysis is performed to test relative performance, robustness, and approximation ability of the proposed filter. The proposed approach not only outperforms residual editing, but is also found to be exceptionally robust to both unknown and approximated faulty measurement distributions.

A Novel Submodule Level Fault-Tolerant Approach for MMC With Integrated Scale-Up Architecture

A submodule (SM) level fault-tolerant method for modular multilevel converters (MMCs) with a scalable control design for medium- and high-voltage applications is proposed in this article. A large number of SMs, which is typically required in high-power applications, is divided into sets with a smaller number of SMs. A local controller is assigned to each set for the capacitor voltage balancing (CVB) and switching signal generations, and the SM level protection. A CVB control method is proposed to maintain SM voltages among sets within a prespecified band under SM failures, in which an MMC arm can operate with unequal numbers of SMs among sets. The computational and communication burdens are reduced in each local controller. Most importantly, changing the number of SMs is achieved without significant modifications in the control system, which improves the expandability and flexibility of the MMC system to easily scale-up to higher voltage levels. A ±320 kV/1000 MW MMC system has been studied in a real-time digital simulator (RTDS) and field-programmable gate arrays boards to validate the proposed fault-tolerant control method under SM failures.

Adaptive fault-tolerant flutter control considering related failure

This article proposes a novel adaptive fault-tolerant control method for suppressing flutter and compensating for related failure in a flutter system. Considering cubic nonlinearity, external disturbances, and related failure, the flutter dynamic model was established firstly. Then, an adaptive fault-tolerant control law was proposed on basis of this model to compensate for related failure and suppress flutter. By Lyapunov stability analysis, the stability of proposed control law was proved in detail. On the last, simulation results further proved the effectiveness of the control law which can not only suppress flutter and compensate for related failure successfully but also has good robustness for external disturbances and system perturbation.

Distributed Cooperative Sliding Mode Fault-Tolerant Control for Multiple High-Speed Trains Based on Actor-Critic Neural Network

This article investigates the cooperative fault-tolerant control problem for multiple high-speed trains (MHSTs) with actuator faults and communication delays. Based on the actor-critic neural network, a distributed sliding mode fault-tolerant controller is designed for MHSTs to solve the problem of actuator faults. To eliminate the negative effects of unknown disturbances and time delay on train control system, a distributed radial basis function neural network (RBFNN) with adaptive compensation term of the error is designed to approximate the nonlinear disturbances and predict the time delay, respectively. By calculating the tracking error online, an actor-critic structure with RBFNN is used to estimate the switching gain of the distributed controller, which reduces the chattering phenomenon caused by sliding mode control. The global stability and ultimate bounded of all signals of the closed-loop system are proposed with strict mathematic proof. Simulations show that the proposed method has superior effectiveness and robustness compared with other fault-tolerant control methods, which ensures the safe operation of MHSTs under moving block conditions.

Development of a hardware-in-the-loop demonstrator for the validation of fault-tolerant control methods for a hybrid UAV

Many aircraft are inherently over-actuated with regard to their input variables. This can be particularly advantageous in the context of unmanned aerial vehicles (UAV), where actuator functions can fail in critical situations. In such cases, the redundant actuators can be used to further fulfil the control strategies used and thus increase the operational safety. Within such an active fault-tolerant control system, a fault detection and isolation (FDI) module is required. To evaluate such safety–critical systems, hardware-in-the-loop simulations (HIL) are a necessary step prior to real flight tests. These simulations can verify the correct implementation of the flight controller on the target hardware as well as the real-time capability of the algorithms used. Particularly in the context of active fault-tolerant control, investigations concerning the robustness of the used FDI module with regard to real, noisy sensor signals, which can be generated by a HIL demonstrator, are of utter importance. This paper presents the development of a HIL demonstrator for the validation of fault-tolerant control methods for a hybrid UAV. This includes a detailed description of the demonstrator’s design, control and interfacing between the integrated subsystems. As an application example, a hybrid UAV model will be shortly presented, which, in addition to the primary aerodynamic control surfaces, can also use four lift rotors to control the aircraft during cruise and is therefore inherently over-actuated. Finally, a closed-loop real-time simulation of the UAV model on the HIL demonstrator is presented on the basis of the exemplary simulation of an actuator failure and subsequent reconfiguration by the fault-tolerant flight control law.

Fault Tolerant Lanczos Eigensolver via an Invariant Checking Method

An extensive survey of the literature shows that the Lanczos eigensolver is a popular iterative method for approximating a few maximal eigenvalues of a real symmetric matrix, particularly if the matrix is large and sparse. In recent years, graphics processing units (GPUs) have become a popular platform for scientific computing applications, many of which are based on linear algebra, and are increasingly being used as the main computational units in supercomputers. This trend is expected to continue as the number of computations required by scientific applications reach petascale and exascale range. In this paper, building on our earlier work [22], we investigate in detail the error checking mechanism for the Lanczos eigensolver. We identify a low cost invariant for efficient error checking, and through mathematical analysis determine the efficiency of our mechanism when used by the Lanczos eigensolver. We evaluate the proposed fault tolerant scheme using an open-source sparse eigensolver on a GPU platform, with and without the injection of faults. We use a large number of sparse matrices from real applications, to determine the efficiency and efficacy of our method and our implementation shows that the proposed fault tolerant method has good error coverage and low overhead. To the best of our knowledge, we are the first to introduce such a scheme for the Lanczos method.