Fault-tolerant Scheme Research Articles

Deterministic fault-tolerant connectivity labeling scheme

AbstractThe f-fault-tolerant connectivity labeling (f-FTC labeling) is a scheme of assigning each vertex and edge with a small-size label such that one can determine the connectivity of two vertices s and t under the presence of at most f faulty edges only from the labels of s, t, and the faulty edges. This paper presents a new deterministic f-FTC labeling scheme attaining $$O(f^2 \textrm{polylog}(n))$$ O ( f 2 polylog ( n ) ) -bit label size and a polynomial construction time, which settles the open problem left by Dory and Parter (in: Proceedings of the 2021 ACM symposium on principles of distributed computing (PODC), pp 445–455, 2021). The key ingredient of our construction is to develop a deterministic counterpart of the graph sketch technique by Ahn et al. (in: Proceedings of the 31st ACM SIGMOD-SIGACT-SIGAI symposium on principles of database systems (PODS), pp 5–14, 2012), via some natural connection with the theory of error-correcting codes. This technique removes one major obstacle in de-randomizing the Dory–Parter scheme. The whole scheme is obtained by combining this technique with a new deterministic graph sparsification algorithm derived from the seminal $$\epsilon $$ ϵ -net theory, which is also of independent interest. As byproducts, our result deduces the first deterministic fault-tolerant approximate distance labeling scheme with a non-trivial performance guarantee and an improved deterministic fault-tolerant compact routing. The authors believe that our new technique is potentially useful in the future exploration of more efficient FTC labeling schemes and other related applications based on graph sketches.

Dynamic event-triggered prescribed performance disturbance rejection fault-tolerant trajectory tracking for surface vehicles

In this article, a dynamic event-triggered prescribed performance disturbance rejection fault-tolerant scheme is designed for the trajectory tracking of surface vehicles. The external time-varying disturbances and loss-of-effectiveness thruster faults are addressed separately. By constructing the separate observers, the external time-varying disturbances and the loss-of-effectiveness thruster faults are on-line estimated, respectively. The prescribed performance and error transformation functions enable the transient and steady-state performance to settle within pre-specified function values. The dynamic event-triggering is introduced so that commanded control signals are temporarily kept under predefined conditions to reduce wear and tear on the thrusters especially in harsh environmental condition. With the aid of the vectorial backstepping technique, the finial control law is derived such that the position and heading of vehicles can be forced to track the reference trajectories in disturbance and fault conditions. Application example on a 1:70 scaled model vessel in the different cases clarify the scheme.

Comprehensive Analysis and Reconstruction of Sensor Faults in Interleaved Buck Converters Using Sliding Mode Observers

This paper presents a fault signal reconstruction method for current sensors in an interleaved buck DC–DC converter, utilizing a sliding mode observer (SMO). A filter bank is used to design the observer within an extended-order system, effectively treating sensor faults as actuator faults, which enables precise estimation of the fault signal. Thus, the proposed approach allows for the identification of the faulty sensor and supports the implementation of fault-tolerant strategies. The paper provides an in-depth analysis of current sensor faults, verifies their impact on current balancing control, and demonstrates the challenge of achieving error-free current estimation in one phase using observers. A comprehensive set of simulation results is carried out, validating the method’s effectiveness and showing a strong correlation with theoretical principles.

Fixed-time active fault-tolerant control for a class of nonlinear systems with intermittent faults and input saturation

In this paper, the problem of fixed-time active fault-tolerant control is studied for systems with sector-bounded nonlinearities, intermittent faults, and input saturation. Since intermittent faults appear and disappear randomly, a fixed-time scheme is considered in the active fault-tolerant control algorithm, composed of detection, isolation, estimation, and the control unit. Utilizing homogeneity-based observers, the fixed-time state estimation is available in the presence of unknown but bounded disturbances, and a fault diagnosis unit is proposed. An input saturation compensator is introduced to analyze the effect of input saturation, and its auxiliary variables are used in the reconfigurable control law. The fault-tolerant controller, which is constructed via the information provided by the fault diagnosis unit and saturation compensator, has two switching modes. As a consequence, intermittent faults are compensated via the designed active fault-tolerant control method and the system reaches practical stability with the entire convergence time bounded in a fixed time. Finally, the example of a heat control system is exploited to demonstrate the effectiveness of the developed active fault-tolerant control scheme.

Robust flexible spacecraft attitude tracking under measurement errors, actuator nonlinearities, and faults

Reliable spacecraft attitude maneuver is one of the core research areas of the space industry due to the need for sustainable space exploration and advancements in the space technology. The paper presents an observer-based adaptive backstepping (OB-ABST) fault-tolerant control scheme for a flexible spacecraft attitude tracking under the effect of state measurement errors, inertial uncertainties, external disturbances, multiple actuator faults, and input nonlinear saturation (INS) while suppressing vibrations due to flexible modes. Initially, we design an adaptive backstepping controller to mitigate the system’s unwanted nonlinearities and observers to get estimates of the attitude dynamics in a recursive design framework. Later, the control structure incorporates a simple actuator saturation compensator to tackle input torque saturation in the system. The critical feature of the proposed OB-ABST control structure is to ensure precise attitude-tracking maneuvers and vibration suppression without intelligent materials such as shape memory alloys (SMA) and piezoelectric material (PZT). Lyapunov stability analysis proves practical finite-time convergence of the system state errors, observation errors, and actuator saturation compensators. Moreover, we provide specific conditions to tune design parameters. Finally, comparative simulation experiments validate the control performance of the proposed controller in the presence of multiple challenges.

Two-dimensional reinforcement learning model-free fault-tolerant control for batch processes against multi- faults

Aiming at the characteristics of batch process changing along with time and batch directions, the existence of unmodeled dynamics, and the partial failure of actuators or/and sensors, we propose a novel 2D reinforcement learning (RL) fault tolerant control strategy without considering model parameters. Firstly, a two-Dimensional (2D) augmented state space model and 2D Q function-based fault tolerant control (FTC) framework is established. The 2D Bellman equation can be acquired by analyzing the relationship between the 2D value function and the 2D Q function. Based on the extended model and Q-learning concept of RL, a data-driven FTTC independent of model parameters is designed, and a 2D data-driven Q-learning algorithm is proposed. Finally, taking the pressure holding phase in the injection process as the experimental object, the control effect is compared with that of the traditional model-based FTC, and better tracking performance and unbiasedness to the probing noise can be proved.

Adaptive dynamic programming–based fault-tolerant control of multi-UAV formation system

With the increasing utilization of unmanned aerial vehicle (UAV) swarms in civilian and military field applications, it is crucial to eliminate the potential impacts of UAV faults on task completion and efficiency. To address this issue, the present paper investigates a fault-tolerant control scheme based on the adaptive dynamic programming (ADP) method and fault observer. The whole closed-loop system is composed of a position loop and an attitude loop. An ADP-based position-tracking controller is established with an improved cost function that can simultaneously represent actuator faults, control inputs, and tracking errors. In addition, a single-layer critic neural network is constructed to estimate the cost function and approximate control inputs. In the process of adjusting the weights of the neural network, a unique adjustment method combining policy gradient and prioritized experience replay is adopted to improve the data usage efficiency and speed up the weight convergence. Furthermore, a sliding mode–based attitude controller is utilized for the inner-loop attitude subsystem. The significant feature of this scheme is that it has the ability to self-learn and self-adapt. A Lyapunov stability analysis is performed to verify whether the signals are uniformly ultimately bounded. Finally, simulation experiments are conducted to demonstrate the effectiveness of the proposed scheme.

Multicast-based fault-tolerant multiparty state preparation of four-qubit cluster states

The primary aim of this study is to utilize multicast in the preparation of multi-party four-qubit cluster states. In the presence of environment noises, errors may influence the procedure of the particle distribution. To address this challenge, we propose a fault-tolerant scheme to manage the errors within the detectable channel particles. Based on the Bell chain channel, our approach could prepare arbitrary four-particle cluster state by introducing auxiliary particles, where the receiver performs the unitary operation for recovering the target states. Compared to previous multicast protocols, our scheme reduces resource consumption and operational complexity during cluster state preparation. Additionally, we analyze the system’s fidelity in incoherent environments, providing a more comprehensive understanding of the impact of noise on quantum communication systems.

Fixed-Time Fault-Tolerant Adaptive Neural Network Control for a Twin-Rotor UAV System with Sensor Faults and Disturbances

This paper presents a fixed-time fault-tolerant adaptive neural network control scheme for the Twin-Rotor Multi-Input Multi-Output System (TRMS), which is challenging due to its complex, unstable dynamics and helicopter-like behavior with two degrees of freedom (DOFs). The control objective is to stabilize the TRMS in trajectory tracking in the presence of unknown nonlinear dynamics, external disturbances, and sensor faults. The proposed approach employs the backstepping technique combined with adaptive neural network estimators to achieve fixed-time convergence. The unknown nonlinear functions and disturbances of the system are processed via an adaptive radial basis function neural network (RBFNN), while the sensor faults are actively estimated using robust terms. The developed controller is applied to the TRMS using a decentralized structure where each DOF is controlled independently to simplify the control scheme. Moreover, the parameters of the proposed controller are optimized by the gray-wolf optimization algorithm to ensure high flight performance. The system’s stability analysis is proven using a Lyapunov approach, and simulation results demonstrate the effectiveness of the proposed controller.

An expandable and cost-effective data center network

With the rapid growth of data volume, the escalating complexity of data businesses, and the increasing reliance on the Internet for daily life and production, the scale of data centers is constantly expanding. The data center network (DCN) is a bridge connecting large-scale servers in data centers for large-scale distributed computing. How to build a DCN structure that is flexible and cost-effective, while maintaining its topological properties unchanged during network expansion has become a challenging issue. In this paper, we propose an expandable and cost-effective DCN, namely HHCube, which is based on the half hypercube structure. Further, we analyze some characteristics of HHCube, including connectivity, diameter, and bisection bandwidth of the HHCube. We also design an efficient algorithm to find the shortest path between any two distinct nodes and present a fault-tolerant routing scheme to obtain a fault-tolerant path between any two distinct fault-free nodes in HHCube. Meanwhile, we present two local diagnosis algorithms to determine the status of nodes in HHCube under the PMC model and MM* model, respectively. Our results demonstrate that despite the presence of up to 25% faulty nodes in HHCube, both algorithms achieve a correct diagnosis rate exceeding 90%. Finally, we compare HHCube with state-of-the-art DCNs including Fat-Tree, DCell, BCube, Ficonn, and HSDC, and the experimental results indicate that the HHCube is an excellent candidate for constructing expandable and cost-effective DCNs.

Fault-tolerant security-efficiency combined authentication scheme for manned-unmanned teaming

Manned-unmanned teaming (MUM-T) is an emerging network system which interconnects manned aerial vehicles (MAVs) with unmanned aerial vehicles (UAVs) to enhance mission effectiveness and reduce workloads. Like other wireless systems, MUM-T is prone to attacks from the open communication channel. Therefore, an authentication scheme is required to establish secure and trusted communication between the MAV and the UAV. However, existing schemes fail to provide adequate security features and necessary efficiency, mostly due to their incomprehensive threat modeling and improper use of authentication techniques. Moreover, traditional centralized architecture of the authentication server leads to the single point of failure (SPOF) problem, which jeopardizes the robustness and scalability of MUM-T. In this paper, we propose a fault-tolerant authentication scheme for MUM-T that will solve these problems. To enhance its security, we construct a new threat model consisting of adversary's capabilities, security features, and security challenges to ensure the security of a scheme under combination attacks. To preserve the highest possible efficiency, we propose the design principle of using lightweight primitives for authentication and applying public key operations in key establishment. To address the SPOF problem, we employ a distributed fault-tolerant mechanism to share registration information within authentication servers and defend against faulty nodes. As is demonstrated by the security proof and performance comparison, our scheme succeeds in improving security and reducing overall costs, which provides a better solution than existing schemes.

Encoded-Fusion-Based Quantum Computation for High Thresholds with Linear Optics.

We propose a fault-tolerant quantum computation scheme in a measurement-based manner with finite-sized entangled resource states and encoded-fusion scheme with linear optics. The encoded fusion is an entangled measurement devised to enhance the fusion success probability in the presence of losses and errors based on a quantum error-correcting code. We apply an encoded-fusion scheme, which can be performed with linear optics and active feedforwards to implement the generalized Shor code, to construct a fault-tolerant network configuration in a three-dimensional Raussendorf-Harrington-Goyal lattice based on the surface code. Numerical simulations show that our scheme allows us to achieve up to 10 times higher loss thresholds than nonencoded fusion approaches with limited numbers of photons used in fusion. Our scheme paves an efficient route toward fault-tolerant quantum computing with finite-sized entangled resource states and linear optics.

Prescribed-time active fault-tolerant control of dynamic positioning vessels based on improved iterative learning observer

Considering the dynamic positioning (DP) vessel control system with actuator faults and unknown environment disturbances, a fault-tolerant control scheme based on improved iterative learning observer (ILO) is proposed in this article. Firstly, the kinematics and dynamics models of DP vessels are established containing the actuator faults and environmental disturbances. Secondly, an improved ILO is designed to handle the unknown faults and disturbances concurrently with higher estimation precision by introducing the state information of the previous moment. Further, a prescribed-time active fault-tolerant control scheme is presented on the basis of the improved ILO and prescribed-time stability. And the stability of proposed ILO and DP fault-tolerant control system are analyzed based on Lyapunov theory. Finally, the effectiveness and advantages of the presented ILO and active fault-tolerant control scheme are illustrated by numerical simulations and comparisons.

Fault-Tolerant Operation of Bosonic Qubits with Discrete-Variable Ancillae

Fault-tolerant quantum computation with bosonic qubits often necessitates the use of noisy discrete-variable ancillae. In this work, we establish a comprehensive and practical fault-tolerance framework for such a hybrid system and synthesize it with fault-tolerant protocols by combining bosonic quantum error correction (QEC) and advanced quantum control techniques. We introduce essential building blocks of error-corrected gadgets by leveraging ancilla-assisted bosonic operations using a generalized variant of path-independent quantum control. Using these building blocks, we construct a universal set of error-corrected gadgets that tolerate a single-photon loss and an arbitrary ancilla fault for four-legged cat qubits. Notably, our construction requires only dispersive coupling between bosonic modes and ancillae, as well as beam-splitter coupling between bosonic modes, both of which have been experimentally demonstrated with strong strengths and high accuracy. Moreover, each error-corrected bosonic qubit is comprised of only a single bosonic mode and a three-level ancilla, featuring the hardware efficiency of bosonic QEC in the full fault-tolerant setting. We numerically demonstrate the feasibility of our schemes using current experimental parameters in the circuit-QED platform. Finally, we present a hardware-efficient architecture for fault-tolerant quantum computing by concatenating the four-legged cat qubits with an outer qubit code utilizing only beam-splitter couplings. Our estimates suggest that the overall noise threshold can be reached using existing hardware. These developed fault-tolerant schemes extend beyond their applicability to four-legged cat qubits and can be adapted for other rotation-symmetrical codes, offering a promising avenue toward scalable and robust quantum computation with bosonic qubits. Published by the American Physical Society 2024

Fault-Tolerant Control for Multi-Quadcopter with Suspended Payload under Wind Disturbance

Delivering payload with multiple quadcopters necessitates a reliable backup system. This research introduces a fault-tolerant design specifically for multi-drone payload transportation. The system employs formation control, ensuring the weight is evenly distributed among all functioning drones. This research tackles the challenge of reliable payload delivery with multi-drone systems. It proposes a new fault-tolerant control system specifically designed for this purpose. The system addresses a limitation in existing solutions by incorporating a simple PD controller alongside a fault-tolerant strategy. This approach allows the system to maintain operation even if a drone malfunctions. The paper further demonstrates the system's effectiveness through simulations. Results show the system's ability to maintain stability with minimal altitude loss (only 6.3cm) and rapid position reconfiguration (within 3.96 seconds) even under windy conditions. These findings highlight the potential of this fault-tolerant design to significantly improve multi-drone payload delivery, especially for missions requiring high levels of stability and redundancy.

Exponentially tighter bounds on limitations of quantum error mitigation

Quantum error mitigation has been proposed as a means to combat unwanted and unavoidable errors in near-term quantum computing without the heavy resource overheads required by fault-tolerant schemes. Recently, error mitigation has been successfully applied to reduce noise in near-term applications. In this work, however, we identify strong limitations to the degree to which quantum noise can be effectively ‘undone’ for larger system sizes. Our framework rigorously captures large classes of error-mitigation schemes in use today. By relating error mitigation to a statistical inference problem, we show that even at shallow circuit depths comparable to those of current experiments, a superpolynomial number of samples is needed in the worst case to estimate the expectation values of noiseless observables, the principal task of error mitigation. Notably, our construction implies that scrambling due to noise can kick in at exponentially smaller depths than previously thought. Noise also impacts other near-term applications by constraining kernel estimation in quantum machine learning, causing an earlier emergence of noise-induced barren plateaus in variational quantum algorithms and ruling out exponential quantum speed-ups in estimating expectation values in the presence of noise or preparing the ground state of a Hamiltonian.

Adaptive neural network fault-tolerant control of hypersonic vehicle with immeasurable state and multiple actuator faults

This paper proposes a fault-tolerant control scheme for tracking and controlling hypersonic vehicles with unknown dynamics, actuator failures, and unmeasurable states. The approach involves using a radial-based neural network to approximate the unknown dynamics and reconstruct the entire system model. Additionally, a neural network state observer is proposed to estimate the unmeasurable state of the system. To address the impact of actuator faults, a nonlinear observer is designed to estimate and compensate for the approximation error of the neural network system and fault values. Furthermore, a prescribed performance function is introduced to ensure both transient and steady-state performance of the system. The bounded stability of the closed-loop system is demonstrated through Lyapunov stability analysis.

Multi-hop fault-tolerant teleportation of arbitrary two-qubit states with cluster channel

In this paper, we propose one multi-hop fault-tolerant teleportation scheme leveraging non-maximally entangled cluster states as the quantum channel, which is crucial for efficient transmission over extended distances. During quantum communication, environmental noise may introduce operational errors between adjacent nodes. In order to uphold the maximum transmission efficiency, error correction operations are exclusively conducted by the ultimate receiver rather than intermediate nodes. Error outcomes from each node can be synchronously relayed to the receiver via the classical channel, effectively diminishing the delays and operational intricacies, thereby significantly bolstering the transmission efficiency. Moreover, we utilize the Quirk simulation software to simulate the teleportation process.

L1 Adaptive Fault-Tolerant Control for Nonlinear Systems Subject to Input Constraint and Multiple Faults

This paper investigates an L1 adaptive fault-tolerant control scheme for nonlinear systems with input constraint, external disturbances, and multiple faults, which include actuator faults and sensor faults. Faults and input constraint are important factors that affect the stability and performance of a control system. Actuators and sensors are the most vulnerable components, with the former receiving more attention in comparison. In this paper, sensor faults are first transformed into pseudo-actuator faults through the augmented matrix approach, which facilitates their handling together with actuator faults. Saturation constraints on the control signal are not conducive to the design of the controller. The conversion of an input-saturated function to a time-varying linear system is completed based on function approximation and Lagrange’s mean value theorem. Moreover, a nonlinear system with unknown input gain and uncertainties is constructed using these methods. Next, an L1 adaptive fault-tolerant controller is designed to cope with uncertainties, including system uncertainties, external disturbances, faults, and approximation errors. In the L1 adaptive controller, the online estimation of the time-varying parameters allows for updating of the system state, while the combination of the two is transmitted to the control law such that it can compensate for the effects of the uncertainties. The stability and performance boundaries are further derived using the Lyapunov theory and the L1 reference system. Finally, simulations are carried out to demonstrate the effectiveness of the proposed controller.

Robust Fixed-Time Adaptive Fault-Tolerant Control for Dynamic Positioning of Ships with Thruster Faults

The ship dynamic positioning system has long been a subject of great interest due to the intricate and unpredictable nature of the maritime environment, which affects its dependability and timeliness. This study focuses on the issue of developing a robust, efficient, and adaptable fault-tolerant control system for ship dynamic positioning systems that experience thruster malfunctions. Firstly, we build the motion model of the ship’s dynamic positioning system with three degrees of freedom, as well as the model for faults in the thruster. A second-order fast fixed-time nonsingular sliding mode surface is formulated, and a robust adaptive control technique is introduced to counteract external environmental disturbances and model errors. The objective is to ensure rapid convergence of the system within a predetermined time frame. Simultaneously, combined with the fault-tolerant control technique, it is ensured that the dynamic positioning ship can still achieve system stability when thruster faults occur. In addition, the analysis of the Lyapunov stability criterion proves that the proposed fixed-time adaptive fault-tolerant control scheme can make the system tracking error converge within a fixed time. Finally, the effectiveness of the proposed control scheme is verified by numerical simulation results.