Fault Tolerance Properties Research Articles

Intelligent sliding mode fault-tolerant control for aircraft engines with actuator dynamics and faults based on adaptive dynamic programming

Abstract The fault-tolerant control issue of aircraft engines with actuator dynamics and faults is investigated in this paper. By proposing a novel intelligent sliding mode fault-tolerant control (ISMFTC) method, which combines an adaptive dynamic programming (ADP) sliding surface with Grey Wolf Optimizer (GWO) for controller parameter optimisation, the goal is to achieve quality steady-state and dynamic performance in aircraft engines while maintaining strong fault-tolerance properties. Firstly, by considering not only actuator dynamics but also actuator faults, an uncertain nonlinear cascaded model of aircraft engines is developed according to characteristic of aircraft engines and their actuators. Secondly, an ADP-based sliding surface is proposed for considered aircraft engine uncertain nonlinear cascaded system. It can obtain a certain sense of optimised performance, and could be solved by ADP strategy off-line as well. Thirdly, fault-tolerant controller is obtained on the basis of sliding mode theory and adaptive fault estimation law, namely, ADP-based ISMFTC controller. Meanwhile, GWO is integrated into the investigation of ADP-based ISMFTC controller, optimised designable control parameters are obtained subsequently. Besides, robustness analysis is elaborated according to Lyapunov theory, fault estimation error is bounded and states of closed-loop system are uniformly ultimately bounded. Simulation on a twin-shaft turbofan aircraft engine, indicates the effect of proposed ADP-based ISMFTC method.

A Fault Tolerance Method for Control Systems with Full or Partial Fault Decoupling

This paper considers technical systems described by nonlinear dynamic models. The fault tolerance property of such systems is ensured by introducing feedback with full or partial fault decoupling. The solution is based on separating a subsystem insensitive or minimally sensitive to faults and its subsequent analysis. For this purpose, a logical-dynamic approach is used, which operates only linear algebra methods. An illustrative practical example is provided.

Unifying flavors of fault tolerance with the ZX calculus

There are several models of quantum computation which exhibit shared fundamental fault-tolerance properties. This article makes commonalities explicit by presenting these different models in a unifying framework based on the ZX calculus. We focus on models of topological fault tolerance – specifically surface codes – including circuit-based, measurement-based and fusion-based quantum computation, as well as the recently introduced model of Floquet codes. We find that all of these models can be viewed as different flavors of the same underlying stabilizer fault-tolerance structure, and sustain this through a set of local equivalence transformations which allow mapping between flavors. We anticipate that this unifying perspective will pave the way to transferring progress among the different views of stabilizer fault-tolerance and help researchers familiar with one model easily understand others.

CG-PBFT: an efficient PBFT algorithm based on credit grouping

Because of its excellent properties of fault tolerance, efficiency and availability, the practical Byzantine fault tolerance (PBFT) algorithm has become the mainstream consensus algorithm in blockchain. However, current PBFT algorithms have problems such as inadequate security of primary node selection, high communication overhead and network delay in the process of consensus. To address these problems, we design a novel efficient Byzantine fault tolerance algorithm based on credit grouping, called CG-PBFT. First, we propose a new credit evaluation model to obtain nodes’ credit values and introduce an optimized three-way quick sorting algorithm to divide nodes into the master-node group, the consensus-node group and the observation-node group, which have different privileges. The nodes in the observation-node group are restricted from participating in consensus, which reduces the communication overhead and improves consensus efficiency. Second, we propose an optimized selection method for the primary node based on a voting mechanism whereby the consensus-node group and observation-node group vote to produce the primary node, which reduces the probability of malicious nodes acting as the primary node and improves the security of primary node selection. Finally, the identity conversion mechanism between node groups is designed, and the actual behavior of nodes within different groups is given credit rewards or punishment, so as to keep an incentive for nodes to participate in appropriate system behavior and improve the working enthusiasm of nodes. The experimental simulation results show that compared with existing PBFT algorithms, the CG-PBFT algorithm improves the average throughput by 51.3% and reduces the average delay by 64.5%; it greatly improves the operating efficiency of the system and can be more suitable for application in the consortium blockchain scenarios.

Implementation of Highly Reliable Convolutional Neural Network with Low Overhead on Field-Programmable Gate Array

Due to the advantages of parallel architecture and low power consumption, a field-programmable gate array (FPGA) is typically utilized as the hardware for convolutional neural network (CNN) accelerators. However, SRAM-based FPGA devices are extremely susceptible to single-event upsets (SEUs) induced by space radiation. In this paper, a fault tolerance analysis and fault injection experiments are applied to a CNN accelerator, and the overall results show that SEUs occurring in a control unit (CTRL) lead to the highest system error rate, which is over 70%. After that, a hybrid hardening strategy consisting of a finite state machine error-correcting circuit (FSM-ECC) and a triple modular redundancy automatic hardening technique (TMR-AHT) is proposed in this paper to achieve a tradeoff between radiation reliability and design overhead. Moreover, the proposed methodology has very small workload and good migration ability. Finally, by full exploiting the fault tolerance property of CNNs, a highly reliable CNN accelerator with the proposed hybrid hardening strategy is implemented with Xilinx Zynq-7035. When BER is 2 × 10−6, the proposed hybrid hardening strategy reduces the whole system error rate by 78.95% with the overhead of an extra 20.7% of look-up tables (LUTs) and 20.9% of flip-flops (FFs).

Artificial Optoelectronic Synapses Based on Light‐Controllable Ferroelectric Semiconductor Memristor

AbstractNumerous synaptic devices have been explored for the next generation of energy‐efficient computing techniques. Among them, optoelectronic synaptic devices based on semiconductor/ferroelectric heterostructures have received a lot of attention lately due to their amazing parallelism, efficiency, and fault tolerance properties. However, polarizing the ferroelectric layer or gating the dielectric layer is necessary to achieve tunable synaptic functions, which generally causes an increase in energy consumption and complex manufacturing processes. Here, a simple and efficient method is demonstrated to develop a tunable optoelectronic synaptic device based on a single ferroelectric semiconductor, BiFeO3‐BaTiO3 (BF‐BT). Multi‐essential synaptic functions including short‐term plasticity, paired‐pulse facilitation, and long‐term plasticity are all satisfactorily replicated by the memristor device. More significantly, light‐controllable synaptic behaviors are realized by altering the ferroelectric polarization state of BF‐BT. Synaptic devices’ relaxation characteristics enable simulation of the effects of positive/negative emotions on learning and forgetting processes. This study highlights the potential of the ferroelectric semiconductor memristor in constructing the efficient optoelectronic synapses for future neuromorphic electronics with the ability to learn and sense optical information.

Fault Tolerance and Node Mapping Algorithm Hierarchical Graph HCN

Embedding in an interconnection network maps the interconnection network G to H and analyzes the relationship between G and H. Hypercubes and toruses are widely known as interconnection networks, and various algorithms have been developed. The HCN graph is a network with a hierarchical structure to improve the network cost of hypercube. In this study, we analyze the fault tolerance and embedding properties of HCN graphs. As a result of the research, the HCN graph has the same node connectivity and degree, so it has the maximum fault tolerance property. In addition, an algorithm that can one-to-one node map the HCN structure to the torus structure was proposed. The embedding results showed that it was possible to embed the torus structure in the HCN graph at an extension rate of 3 and dilation of 1. The results of the embedding study mean that various algorithms developed in Torus can be efficiently used in the HCN structure.

A robustly stabilizing fault‐tolerantMPC: A performance improvement‐based approach

AbstractIn terms of model predictive control (MPC) performance degradation caused by operational faults, in this article, a robust MPC strategy with active fault tolerance properties is proposed. The proposed strategy incorporates a fault supervision layer into the structure of conventional cost‐contracting formulation‐based robust MPC for the online update of the nominal controller model in the event of faults. The robust MPC is based on multiplant uncertainty, while the supervisory layer consists of a bank of unknown input observers and a decision‐making algorithm. Simulation results in a nonlinear polymerization reactor subject to process faults demonstrate that the proposed approach offers superior performance compared to the conventional strategy.

Structure Fault Tolerance of Bubble-Sort Star Graphs

As two significant performance indicators, structure connectivity and substructure connectivity have been widely studied, and they are used to judge a network’s fault tolerance properties from the perspective of the structure becoming faulty. An n-dimensional bubble-sort star graph BSn is a popular interconnection network with many good properties. We find the upper bounds of κ(BSn;K1,3) and κs(BSn;K1,3) in this paper. Furthermore, we establish κ(BSn;H) and κs(BSn;H) of BSn, where H∈{K1,K1,1,K1,2}.

Securing Big Data Integrity for Industrial IoT in Smart Manufacturing Based on the Trusted Consortium Blockchain (TCB)

The smart manufacturing ecosystem enhances the end-to-end efficiency of the mine-to-market lifecycle to create the value chain using the big data generated rapidly by edge computing devices, third-party technologies, and various stakeholders connected via the industrial Internet of things. In this context, smart manufacturing faces two serious challenges to its industrial IoT big data integrity: real-time transaction monitoring and peer validation due to the volume and velocity dimensions of big data in industrial IoT infrastructures. Modern blockchain technologies as an embedded layer substantially address these challenges to empower the capabilities of the IIoT layer to meet the integrity requirements of the big data layer. This paper presents the trusted consortium blockchain (TCB) framework to provide an optimal solution for big data integrity through a secure and verifiable hyperledger fabric modular (HFM). The TCB leverages trustworthiness in heterogeneous IIoT networks of governing end-point peers to achieve strong integrity for big data and support high transaction throughput and low latency of HFM contents. Our proposed framework drives the fault-tolerant properties and consensus protocols to monitor malicious activities of tunable peers if compromised and validates the signed evidence of big data recorded in real-time HFM operated over different smart manufacturing environments. Experimentally, the TCB has been evaluated and reached tradeoff results of throughput and latency better than the comparative consortium blockchain frameworks.

Optimization of Rotor Arrangement for a Multirotor UAV with Robustness against a Single Rotor-Failure

This paper proposes the optimization scheme for designing rotor arrangements for a multirotor unmanned aerial vehicle (UAV), which achieves high manipulability with satisfying fault-tolerant properties against an arbitrary single rotor fault. The proposed optimization problem is formulated to yield UAVs in which rotors are all directed upward and arranged on the same plane without overlapping. We then apply this optimization problem to design a hexarotor. The obtained structure shows a similar structure to the 2Y hexarotor, which was presented in the previous work without guaranteeing its optimality. We then build a prototype of the 2Y hexarotor. The experimental demonstration verifies the robustness of the 2Y hexarotor against any single rotor malfunction.

Parallel Fault-Tolerant and Robust Boost Converter for Vehicle-to-Aid Services

The operation of electric vehicles is currently segmented in a scenario of smart grids as Vehicle to Grid (V2G), Vehicle to Home (V2H), Vehicle to Building (V2B), Vehicle to Load (V2L), among others. However, the migration of a type of vehicular applications toward its electrification that is of vital relevance is the medical/health assistance (human, animal, agronomist, environmental, etc.) or emergency services, called in this article vehicle-to-aid (V2A). Applications for V2A, for instance the electronic power converters that supply energy from the vehicle to the medical equipment, require offering very robust solutions against failures, including short circuits and component damages. In this paper, is proposed a new configuration of serial input and parallel output, not isolated, DC-DC converter with important properties of fault tolerance to component failures, robustness against variations in the parameters and tolerance to design errors. Analytical, numerical and experimental results, that validate the operation of the proposed configuration against failures and parameter variation, are presented.

Guest editorial: Decision making and control for connected and automated vehicles

Guest editorial: Decision making and control for connected and automated vehicles

Extra Edge Connectivity and Extremal Problems in Education Networks

Extra edge connectivity and diagnosability have been employed to investigate the fault tolerance properties of network structures. The p-extra edge connectivity λp(Γ) of a graph Γ was introduced by Fàbrega and Fiol in 1996. In this paper, we find the exact values of p-extra edge connectivity of some special graphs. Moreover, we give some upper and lower bounds for λp(Γ), and graphs with λp(Γ)=1,2,n2n2−1,n2n2 are characterized. Finally, we obtain the three extremal results for the p-extra edge connectivity.

Development of A Novel Block Design Based Key Agreement Protocol for Cloud Environment to Improve Efficient Performance and Security

Cloud computing is one of the recent emerging technologies. Heavy data sharing among multiple users is an open issue. Data sharing in cloud computing enables multiple participants to freely share the group data, which improves the efficiency of work in cooperative environments and has widespread potential applications. However, how to ensure the security of data sharing within a group and how to efficiently share the outsourced data in a group manner are formidable challenges. In this paper we focused on security issues with the help of key agreement protocols to perform efficient data sharing in cloud environment. We proposed a novel block design based key agreement method in support of symmetric balanced incomplete block design (SBIBD). The main objective of this method is to supports multiple participants, which can flexibly extend the number of participants in a cloud environment according to the structure of the block design. Based on the proposed group data sharing model, we present general formulas for generating the common conference key K for multiple participants. In addition, the fault tolerance property of our protocol enables the group data sharing in cloud computing to withstand different key attacks, which is similar to Yi’s protocol.

Decoding Merged Color-Surface Codes and Finding Fault-Tolerant Clifford Circuits Using Solvers for Satisfiability Modulo Theories

Universal fault-tolerant quantum computers will require the use of efficient protocols to implement encoded operations necessary in the execution of algorithms. In this work, we show how solvers for satisfiability modulo theories (SMT solvers) can be used to automate the construction of Clifford circuits with certain fault-tolerance properties and we apply our techniques to a fault-tolerant magic-state-preparation protocol. Part of the protocol requires converting magic states encoded in the color code to magic states encoded in the surface code. Since the teleportation step involves decoding a color code merged with a surface code, we develop a decoding algorithm that is applicable to such codes.

Advanced post‐impact safety and stability control for electric vehicles

In terms of the possible secondary or multiple events accidents (MEA) after an initial vehicle to vehicle (V2V) impact, this research proposes an active safety & stability controller for independent-driven electric vehicles towards recovering the vehicle to safety states after an impact. The controller aims to regulate the course angle and lateral deviation that enforce the vehicle back to its original driving path. The upper-level controller is derived based on sliding mode technique. And the low-level controller aims to solve a convex quadratic allocation problem, which inherently incorporates fault-tolerance property. The independent in-wheel-motor (IWM) fault is very likely to happen under a real V2V impact and it contributes much to the driving safety & stability. Two typical real-end-collision scenarios under low- and high longitudinal velocities are designed to verify the proposed controller performance. The low- and high velocities collisions aim to simulate the urban and highway accidents, respectively. Compared to other control methods, i.e. pure braking and static allocation, the RMSEs of safety (lateral deviation, course angle) and stability indexes (yaw rate, sideslip angle) under proposed controller reduce significantly both in urban and highway accidents. Moreover, the controller performs robust enough against the impact-induced IWM fault. It further supports the effectiveness at dealing with the safety and stability of the ego vehicle after an initial impact and prevent possible MEA.

On the g-extra diagnosability of enhanced hypercubes

Several fault tolerant models have been investigated in order to study the fault-tolerance properties of self-diagnosable interconnection networks, which are often represented with a connected graph G. In particular, a g-extra cut of a non-complete graph G,g≥0, is a set of vertices in G whose removal disconnects the graph, but every component in the survival graph contains at least g+1 vertices. The g-extra diagnosability of G then refers to the maximum number of faulty vertices in G that can be identified when considering these g-extra faulty sets only.Enhanced hypercubes, denoted by Qn,k,n≥3,k∈[1,n], is another variant of the hypercube structure. In this paper, we make use of its super connectivity property to derive its g-extra diagnosability of (g+1)n−(g2)+1 in terms of the PMC diagnostic model for g∈[1,min⁡{(n−3)/2,k−3}],n≥2g+3, and k∈[max⁡{4,g+3},n−1]; as well as g∈[1,(n−5)/2], and n=k; and that in terms of MM* model, when g∈[2,min⁡{(n−3)/2,k−3}], n≥2g+3, and k∈[max⁡{4,g+3},n−1]; as well as g∈[2,(n−5)/2], and n=k.

Fault Tolerant Control System for a Mini Hydropower Plant

In this paper, a solution for the fault tolerant control of a mini hydropower plant is proposed. The mathematical model which describes the dynamics of the electrical energy production process is identified based on processing the experimental data measured during the plant operation. The main real power and frequency control strategy is based on implementing the cascade control structure. In order to obtain the fault tolerance property, the initial form of the cascade structure is augmented by introducing additional elements which identify the faults and reject their effects. In order to implement the faults identifier and the correction mechanism, artificial intelligence methods, based on neural networks, are used.

PV-Powered Grid-Tied Fault Tolerant Double-Stage DC-AC Conversion Chain Based on a Cascaded H-Bridge Multilevel Inverter

This paper is dedicated to a comprehensive study of a complete DC/AC conversion chain. Motivated by the high power demand of a variety of industrial applications, this work puts an emphasis on a double stage conversion system composed of N photovoltaic energy supplies, N DC-DC boost converters, a DC-link containing N capacitors, N H-bridge inverters connected in cascade forming the core of the structure, an LCL filter and an electrical grid. With the use of an appropriate regulator, the following control objectives are aimed to be achieved: i. the extraction of the maximum available power via the regulation of the voltage across the PV panels, ii. the fulfillment of a unitary power factor, iii. the regulation of the DC-link voltage to a desired reference. Reaching the pre-mentioned objectives requires the design of a multi-loop regulator that upgrades the features of the system under investigation to work under matching and mismatching irradiations efficiently thanks to the individual control of each PV module. As for the power factor correction (PFC) requirement and the DC link regulation, two cascaded loops are developed. The designed regulator in this study is based on the sliding mode control strategy combined with Lyapunov theory. The controlled system's performances are examined by means of simulation on Matlab/SimPowerSystems environment. The obtained results prove the effectiveness of the designed controlled system and demonstrate the fault tolerance property of the conversion chain.