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The cooperative output regulation problem with actuator faults and unknown nonlinear disturbances is a challenging research area in multi‐agent systems. This paper proposes an adaptive fuzzy fault‐tolerant controller to address this problem by employing a fuzzy logic system for approximating the unknown nonlinear disturbances. The internal model principle is utilized to transform the cooperative output regulation problem into a stability problem of an auxiliary system, with the aim of compensating for actuator failures in the system. By incorporating fuzzy logic system, the adaptive controller is able to approximate and compensate for the unknown nonlinear disturbances. Extensive simulations are conducted to validate the robustness and performance of the proposed method. The adaptive controller effectively handles actuator faults and achieves output regulation with unknown nonlinear disturbances. [ABSTRACT FROM AUTHOR]

To improve the fault-tolerant ability of switched reluctance motor (SRM) drive systems and ensure the braking performance of the electric vehicle driven by in-wheel SRMs, a novel fault-tolerant control method that includes the open circuit and the short circuit is presented in this study. First, a novel modular fault-tolerant power converter, which includes traditional driving topology and modular fault-tolerant construction, is built in accordance with the traditional half-bridge power converter. This novel converter provides an advanced fault-tolerant solution for the faults of SRM drive systems. Then, combined with the corresponding detection signals, a new fault detection method is presented for accurately detecting the faults of the system. Furthermore, a new fault-tolerant control method is proposed to improve the fault-tolerant ability of the system. Notably, the fault-tolerant process is completed by employing the circuit of the traditional power converter to replace the fault circuit of the modular construct when faults are detected. Moreover, simulation results are obtained and compared. The results indicate that the proposed method can ensure vehicle braking performance, including braking comfort, braking safety, endurance mileage, and braking stability. Finally, hardware-in-the-loop is conducted, and the results demonstrate the real-time performance and validity of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the distributed fault-tolerant leader-following synchronisation problem for linear multi-agent systems (MASs) with the event triggering strategy. Firstly, in order to compensate effectively for the actuator faults and bounded inputs from the leader, a distributed event-triggered algorithm with adaptive techniques is proposed. Secondly, the trigger function with adaptive parameters is designed to enhance the self-regulation of the trigger mechanism, which is relevant to the state of the agents and time, but not to the number of agents. Then, it is demonstrated that the developed consensus protocol can achieve not only the synchronisation of agents without continuous communication, but also the exclusion of Zeno behavior. Finally, example of numerical simulation illustrates the effectiveness of the presented control protocol. [ABSTRACT FROM AUTHOR]

This paper investigates the containment control problem for heterogeneous multi-agent systems with unknown leaders and actuator failures. The dynamics of the leaders are unavailable to all followers and the measurable information of leaders is available to some followers. A model-free adaptive observer for each follower is proposed to estimate the convex hull of the leaders states and the dynamic knowledge of the unknown leaders. The followers may be affected by the actuator failures. Based on the adaptive observer and the adaptive solution of the output regulation equation, an adaptive fault-tolerant control protocol is designed to mitigate the impact of actuator failure on containment performance such that the output containment errors are ultimately uniformly bounded. Two simulation examples are provided to demonstrate the feasibility of the presented control scheme. [ABSTRACT FROM AUTHOR]

This study investigates fault-tolerant consensus tracking for discrete-time multi-agent systems (MASs) subject to external eavesdropping threats and additive actuator faults. First, actuator faults are modeled by difference equations, and decentralized observers are constructed to estimate actuator faults as well as system states. To offset fault-induced effects, ensure secure communication, and alleviate communication congestion, neighboring encrypted state information based on the encryption–decryption strategy (EDS) and estimated fault are integrated into a distributed active fault-tolerant consensus tracking control (FCTC) protocol. Through the properties of compatible norms, criteria for the controller, observer, and dynamic encryption key in EDS are derived to achieve leader-following consensus (LFC) of MASs with bias and drift actuator faults. Simulation results confirm the validity of the encryption–decryption-based distributed FCTC strategy. • The design of consensus tracking control protocols combine privacy preservation and fault-tolerant control technologies when multi-agent systems suffer from cyber and physical security problems. • A sufficient condition guarantees the performance of leader-following consensus tracking and serves as a criterion for designing the controller, observer, and symmetric encryption key. • A new modified Riccati-based controller design method separates the graph properties from the feedback design problem. [ABSTRACT FROM AUTHOR]

Introduction. Recently, three-phase induction motor drives have been widely used in industrial applications; however, the feedback signal failures of current sensors can seriously degrade the operation performance of the entire drive system. Therefore, the motor drives require a proper solution to prevent current sensor faults and improve the reliability of the motor drive systems. The novelty of the proposed research includes integrating the current sensor fault-tolerant control (FTC) function according to enhanced technique into the field-oriented control loop for speed control of the motor drive system. Purpose. This research proposes a hybrid method involving a third difference operator and signal comparison algorithm to diagnose various types of current sensor faults as a positive solution to enhance the stability of the induction motor drive system. Methods. A hybrid method involving a third difference operator for the measured speed signals and a comparison algorithm between measured and estimated current signals are proposed to diagnose the current sensors’ health status in the fault-tolerant process. After determining the faulty sensor, the estimated current signals based on the Luenberger observer are used immediately to replace the defective sensor signal. Results. The current sensor is simulated with various failure types, from standard to rare failures, to evaluate the performance of the FTC method implemented in the MATLAB/Simulink environment. Simultaneously, a fault flag corresponding to a defective sensor should be presented as an indicator to execute the repair process for faulty sensors at the proper time. Practical value. Positive results have proven the feasibility and effectiveness of the proposed FTC integrated into the speed controller to improve reliability and ensure the stable operation of the induction motor drive system even under current sensor fault conditions. [ABSTRACT FROM AUTHOR]

To address the issues of decreased electromagnetic torque, poor robustness, and failure of demagnetization fault detection caused by permanent magnet demagnetization and inductance mismatch in interior permanent magnet synchronous motor (IPMSM), a robust deadbeat fault-tolerant predictive current control (RDFTPCC) strategy based on cascade flux linkage observer (CFO) is proposed. The proposed CFO is constructed by combining a discrete model reference adaptive system (MRAS) with an improved non-singular fast terminal sliding mode observer (INFTSMO). MRAS and INFTSMO perform d-q axis inductance estimation and demagnetization fault detection, respectively. A better current prediction can be obtained via the parameter state information from CFO. Moreover, the RDFTPCC is constructed by the state information obtained from CFO, which can compensate for the torque deficit due to permanent magnet demagnetization and the control performance degradation due to parameter mismatch, hence realizing fault-tolerant control. The experimental results indicate that the proposed method exhibits stronger fault-tolerance and robustness than the conventional method when the IPMSM suffers from demagnetization fault and inductance mismatch. [ABSTRACT FROM AUTHOR]

In this article, an optimized fault-tolerant control (FTC) method without current judgement is proposed for open-switch faults (OSFs) in dual three-phase permanent magnet synchronous motor (DTPMSM) drives. The reason for the torque ripple under OSFs has been investigated. The theoretical analysis reveals a significant increase in torque ripple under OSFs. Then, an optimized FTC method is proposed for a DTPMSM with two isolated neutral points. The proposed method maintains the original control scheme, enabling the smooth transitions of current and torque between faulty operation and FTC without introducing noticeable torque ripples. In addition, the universality and robustness are enhanced by eliminating the need for current judgement, thereby avoiding misjudgments due to sinusoidal current zero crossings, sudden load, or speed changes. The experimental results are presented to validate the effectiveness of the proposed FTC strategy under OSFs on a laboratory DTPMSM. [ABSTRACT FROM AUTHOR]

The ability and rapid access to execution data and information in manufacturing workshops have been greatly improved with the wide spread of the Internet of Things and artificial intelligence technologies, enabling real-time unmanned integrated control of facilities and production. However, the widespread issue of data quality in the field raises concerns among users about the robustness of automatic decision-making models before their application. This paper addresses three main challenges relative to field data quality issues during automated real-time decision-making: parameter identification under measurement uncertainty, sensor accuracy selection, and sensor fault-tolerant control. To address these problems, this paper proposes a risk assessment framework in the case of continuous production workshops. The framework aims to determine a method for systematically assessing data quality issues in specific scenarios. It specifies the preparation requirements, as well as assumptions such as the preparation of datasets on typical working conditions, and the risk assessment model. Within the framework, the data quality issues in real-time decision-making are transformed into data deviation problems. By employing the Monte Carlo simulation method to measure the impact of these issues on the decision risk, a direct link between sensor quality and risks is established. This framework defines specific steps to address the three challenges. A case study in the steel industry confirms the effectiveness of the framework. This proposed method offers a new approach to assessing safety and reducing the risk of real-time unmanned automatic decision-making in industrial settings. [ABSTRACT FROM AUTHOR]

This paper focuses on a robotic system with actuator fault and presents a sliding mode active fault-tolerant control method based on coupled position error. The actuator fault is first detected by a fault alerter with a predetermined threshold. After the fault is successfully detected, the fault is estimated by a fault observer. Coupling the position error with the weighted position error of different joints, a non-singular fast terminal sliding mode surface is constructed, and a super-twisted algorithm is introduced to design a coupled error super-twisted sliding mode controller (CESSMC). Furthermore, the fault estimation is incorporated with the CESSMC to accomplish the coupled error super-twisted sliding mode active fault-tolerant control. The stability and the finite-time convergence of the system are theoretically proved. Simulations and experiments are conducted to verify the effectiveness of the proposed method. The proposed method can achieve the position error convergence in finite time and reduce chattering in the control input. With the tight coupling between position error and weighted position error, the fault compensation effect and trajectory tracking accuracy can be improved. [ABSTRACT FROM AUTHOR]

Industrial mobile robots easily experience actuator loss of some effectiveness and additive bias faults due to the working scenarios, resulting in unexpected performance degradation. This article proposes a novel adaptive fault-tolerant control (FTC) strategy for nonholonomic mobile robot systems subject to simultaneous actuator lock-in-place (LIP) and partial loss-of-effectiveness (LOE) faults. First, a nominal fractional-order sliding mode controller based on the designed exponential super-twisting reaching law is investigated to reduce the reaching phase time and eliminate the chattering. To address the time-varying LIP faults and uncertainties, a novel barrier function (BF)-based gain is explored to assist the super-twisting law. An estimator is designed to estimate the lower bound of the time-varying partial LOE fault coefficients, thus without requiring the boundary information of faults that is commonly requested in traditional FTC schemes. Combined with the nominal controller clubbed with BF and estimator-based LOE fault compensation term, the fault-tolerant controller is finally constructed. The proposed FTC scheme achieves fast convergence and the sliding variables can be confined in a predetermined neighborhood of the sliding manifold under actuator faults. The results show that the proposed controller has superior tracking performance under faulty conditions compared with other state-of-the-art adaptive FTC approaches. [ABSTRACT FROM AUTHOR]

Robotic manipulators are widely used in various industries for complex and repetitive tasks. However, they remain vulnerable to unexpected hardware failures. In this study, we address the challenge of enabling a robotic manipulator to complete tasks despite joint malfunctions. Specifically, we develop a reinforcement learning (RL) framework to adaptively compensate for a nonfunctional joint during task execution. Our experimental platform is the Franka robot with seven degrees of freedom (DOFs). We formulate the problem as a partially observable Markov decision process (POMDP), where the robot is trained under various joint failure conditions and tested in both seen and unseen scenarios. We consider scenarios where a joint is permanently broken and where it functions intermittently. Additionally, we demonstrate the effectiveness of our approach by comparing it with traditional inverse kinematics-based control methods. The results show that the RL algorithm enables the robot to successfully complete tasks even with joint failures, achieving a high success rate with an average rate of 93.6%. This showcases its robustness and adaptability. Our findings highlight the potential of RL to enhance the resilience and reliability of robotic systems, making them better suited for unpredictable environments. [ABSTRACT FROM AUTHOR]

This article explores a distributed optimal coordination control problem for multiple Euler–Lagrange systems with actuator faults. To address this problem, an event-triggered fault-tolerant optimisation algorithm is first proposed to eliminate unexpected faults and reduce the consumption of control resources. In order to further enhance the system's reliability, another algorithm based on the Nussbaum function is proposed to handle faulted systems with uncertain control directions. Note that an auxiliary system with adaptive gains is introduced to eliminate the need for agents to interact with their actual state information, and thus has the effect of protecting privacy. Moreover, the stochastic semi-Markov jumping networks are considered in the algorithms to describe the switching process of uncertain communication graphs. Additionally, the algorithms are fully distributed since it does not require global information of topologies. Finally, numerical simulations are conducted in the article to verify the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

In the fault-tolerant control tasks of nonlinear systems, unmeasurable states, time delay and actuator faults are considered to be the main factors hindering effective controller design and tracking performance improvement. To solve these problems, firstly, a state observer is established to estimate the unmeasurable of the system and the prescribed performance control based on error transformation is presented to maintain system efficiency and reliability. Secondly, the problem of controller design caused by input delay is effectively solved by constructing an auxiliary tracking error and auxiliary system and combining with the well-designed Lyapunov-Krasovskii functionals. Thirdly, the newly employed damping term in the intermediate control law is utilized to compensate for the possibly unlimited number of faults. Then, it is proved that all signals are semi-global practical finite-time stable based on the backstepping technique. Meanwhile, the tracking error can converge to a specified range within finite time. Finally, comparative simulations are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In the paper, a dynamic surface-based adaptive fuzzy fixed-time fault-tolerant control scheme is developed for nonstrict feedback nonlinear systems with non-affine faults. Firstly, the computational complexity is reduced by adopting dynamic surface control technique, and unknown nonlinear functions are approximated with the help of fuzzy logic systems. Secondly, non-affine faults involving system states and controller output are taken into account and treated by transforming it into nonlinear in the unknown parameters. Then, under the framework of fixed-time stability, a novel adaptive fuzzy fault-tolerant control strategy is designed so that the closed-loop system is semi-globally practically fixed-time stable. Finally, a numerical simulation and a model simulation are given to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Four-wheel independent drive and four-wheel independent steering (4WID-4WIS) vehicles provide increased redundancy in fault-tolerant control (FTC) schemes, enhancing heterogeneous fault-tolerant capabilities. This paper addresses the challenge of maintaining vehicle safety and maneuverability in the presence of actuator faults in autonomous vehicles, focusing on 4WID-4WIS systems. A novel unified hierarchical active FTC strategy is proposed to handle various actuator failures. The strategy includes an upper-layer motion controller that determines resultant force requirements based on trajectory tracking errors and a middle-layer allocation system that redistributes tire forces to fault-free actuators using fault information. This study, for the first time, considers multi-fault scenarios involving longitudinal and lateral coupling, calculating FTC boundaries for each fault type. Additionally, a fault tolerance index is introduced for 256 fault scenarios, using singular value decomposition to linearly represent the vehicle attainable force domain. Based on this, an adaptive velocity planning strategy is developed to balance safety and maneuverability under fault conditions. Matlab 2021a/Simulink and Carsim 2019 co-simulation results validate the proposed strategies, demonstrating significant improvements in fault-tolerant performance, particularly in complex and emergency scenarios. [ABSTRACT FROM AUTHOR]

The present investigation aims to address the leader‐following consensus issue for variable‐order fractional multi‐agent systems (VOFMASs) under actuator faults and unknown external disturbances. The Caputo definition for the variable‐order fractional (VOF) derivative is used to model the non‐linear dynamics of the leader and follower agents. Consequently, two lemmas are developed for the Caputo VOF derivative of the Lyapunov function. In the first case, it is assumed that the multi‐agent system (MAS) operates without actuator faults and an adaptive controller is proposed. With the aid of the developed lemmas, assurance is provided for the finite‐time bounded cooperative tracking of the VOFMAS despite the presence of unknown external disturbances. In the second case, a novel fault‐tolerant controller is designed for the finite‐time consensus of the MAS under two common kinds of actuator faults: loss of effectiveness fault and bias fault. Finally, the efficacy of the proposed controller is demonstrated through the presentation of results from three simulation examples. [ABSTRACT FROM AUTHOR]

This work focuses on the three-dimensional integrated guidance and control (IGC) problem for a flight vehicle with a body-aligned strapdown seeker. The strapdown seeker cannot provide the line-of-sight (LOS) angular rate information and causes difficulties in the controller design. Additionally, external disturbance and gain–loss actuator faults also lead to the loss of control performance. To solve these problems, an extended state observer (ESO) is firstly developed to estimate the LOS angular rate by applying the observed body-line-of-sight angles provided by the body-aligned strapdown seeker. Based on backstepping and dynamic surface control techniques, the fault-tolerant IGC is then designed to deal with the gain–loss actuator fault, and adaptive approaches are applied to improve the robustness of the system. Finally, the uniformly ultimately bounded stability of the flight control system is guaranteed via Lyapunov synthesis, and numerical simulations are conducted to verify the effectiveness of the system. [ABSTRACT FROM AUTHOR]

This paper investigates a finite-time adaptive fuzzy prescribed performance fault-tolerant control (FTC) issue for the steer-by-wire vehicle (SBWV) systems with intermittent actuator faults. Different from the steer-by-wire (SBW) system studied by the previous literatures, the SBWV system involved in this study consists of a vehicle dynamics model and an SBW system, including unmeasurable states and unknown nonlinear dynamics. Fuzzy logic systems (FLSs) are first used to identify the unknown model dynamics, and a fuzzy state observer is constructed to estimate the unmeasured states. Then, to compensate for the influence of intermittent actuator faults, a novel finite-time output-feedback prescribed performance adaptive FTC scheme is developed by using the adaptive backstepping control methodology and co-designing the last virtual controller. The presented control scheme not only guarantees that all signals of the closed-loop system are bounded in the presence of actuator faults, but also ensures that the tracking error converges to a small neighborhood of the zero within the prescribed performance bounded. The computer simulation and comparison results demonstrate the effectiveness of the proposed fuzzy control algorithm. [ABSTRACT FROM AUTHOR]

In this article, we introduced a novel definition for a class of extended Nussbaum functions that have looser requirements than the traditional Nussbaum function. The extended Nussbaum function achieves comparable performance to the traditional Nussbaum function while addressing the challenges of unknown control directions and time‐varying actuator faults. We then provide a specific example function based on the extended Nussbaum function definition. Unlike the traditional Nussbaum function, which oscillates with fixed frequency and constantly increasing amplitude, this example function constrains the amplitude and oscillates with decreasing frequency. Consequently, its amplitude and derivative remain bounded. The oscillation of the system caused by the too large amplitude of the traditional Nussbaum function can be avoided. Furthermore, this example function is constructed using portions of elliptic curve. As a result, it is continuous and differentiable, in contrast to the normal decreasing‐frequency Nussbaum function using trigonometric function, which is only continuous. The overall closed‐loop system's global stability and asymptotic convergence of system states are successfully achieved. Simulation results demonstrate the effectiveness of the proposed function. [ABSTRACT FROM AUTHOR]

Vector-controlled drives require stator current information for use in current feedback and/or state variable estimators. That is why the detection and compensation of possible current sensor (CS) damage is so important. This article focuses on CS fault-tolerant control (FTC) in induction motor (IM) drive systems. In contrast to solutions known from the literature, two modified Luenberger observers (MLO) were applied, allowing for high-quality estimation of currents used in the detector and fault compensator. In a simple implementation of a detection algorithm based on residuals, an adaptive threshold coefficient was employed, enabling effective detection of various types of faults, regardless of whether the second CS was faulty or intact. The presented solution was evaluated during both motor and regenerative operation, with faults occurring in transient states, unlike solutions known in the literature. [ABSTRACT FROM AUTHOR]

In this paper, a robust fault-tolerant control with a dynamic event-triggered mechanism based on the observer is proposed for a nonlinear switched system with faults, external disturbances, and uncertainties. A first-order filter is utilized to equate sensor faults to actuator faults, and the augmented system is constructed. An adaptive observer with H∞ performance is designed based on the augmented system. The condition that the state error and fault error of the adaptive observer are uniformly bounded is given. To save communication resources and reduce the transmission of unnecessary information, an improved dynamic event-triggered mechanism is designed by introducing a fixed threshold and defining a sampling error function based on the observed state and the actual state. This mechanism can further expand the triggering time interval and effectively avoid the Zeno behavior. According to the observed state and real-time fault estimation information at the triggering moment, a fault-tolerant controller for the switched system based on the dynamic event-triggered mechanism is proposed, and the conditions for asymptotic stability of the closed-loop system are provided. Finally, the validity of the proposed method is verified by application simulation for the variant aircraft switched system. [ABSTRACT FROM AUTHOR]

This paper investigates adaptive fuzzy finite-time output feedback fault-tolerant tracking control problem for multiple-input multiple-output (MIMO) stochastic non-strict feedback nonlinear systems with non-affine nonlinear faults and states unmeasured. Firstly, high-gain fuzzy state observers are constructed to overcome the state unmeasured problem in the system. Secondly, the mean-value theorem and input compensation techniques are employed to decouple non-affine nonlinear faults, and the resulting unknown control coefficients problem is handled using Nussbaum functions. In addition, dynamic surface control techniques and error compensation mechanisms are considered in the controller design, which effectively decreases the computational complexity of the control scheme. By combining the adaptive backstepping technique with finite-time control, a novel adaptive fuzzy dynamic surface finite-time output feedback fault-tolerant tracking control algorithm is proposed. The designed controller guarantees that all signals in the stochastic systems are semi-global finite-time stable in probability (SGFSP) as well as the tracking errors can converge to a small neighborhood within the origin in finite-time. Finally, two simulation examples are introduced to verify the effectiveness of the suggested control strategy. [ABSTRACT FROM AUTHOR]

This paper presents an actuator fault-tolerant control (FTC) strategy for a hexacopter unmanned aerial vehicle (UAV) designed specifically for precision agriculture applications. The proposed approach integrates advanced sensing techniques, including the estimation of Near-Infrared (NIR) reflectance from RGB imagery using the Pix2Pix deep learning network based on conditional Generative Adversarial Networks (cGANs), to enable the calculation of the Normalized Difference Vegetation Index (NDVI) for health assessment. Additionally, trajectory flight planning is developed to ensure the efficient coverage of the targeted agricultural area while considering the vehicle's dynamics and fault-tolerant capabilities, even in the case of total actuator failures. The effectiveness of the proposed system is validated through simulations and real-world experiments, demonstrating its potential for reliable and accurate data collection in precision agriculture. An NDVI test was conducted on a sugarcane crop using the estimated NIR to assess the crop's condition during its tillering stage. Therefore, the main contributions this paper include (i) the development of an actuator FTC strategy for a hexacopter UAV in precision agriculture applications, integrating advanced sensing techniques such as NIR reflectance estimation using deep learning network; (ii) the design of a flight trajectory planning method ensuring the efficient coverage of the targeted agricultural area, considering the vehicle's dynamics and fault-tolerant capabilities; (iii) the validation of the proposed system through simulations and real-world experiments; and (iv) the successful integration of FTC scheme, advanced sensing, and flight trajectory planning for reliable and accurate data collection in precision agriculture. [ABSTRACT FROM AUTHOR]

This paper presents a concomitant observer-based multi-level fault-tolerant control (FTC) for near-space vehicles (NSVs) with a new type dissimilar redundant actuation system (NT-DRAS). When NSV flight control system faults occur in NT-DRAS and attitude-corresponding sensors, the NSV hybrid output states, including the concomitant observer usable states and the real system states, are applied to solve the FTC gain by using the linear quadratic regulator (LQR) technique. Furthermore, since NT-DRAS is used in NSVs, a multi-level (actuation system level and flight control level) FTC strategy integrating NT-DRAS channel switching and flight control LQR is proposed for complex and worsening fault cases. The most important finding is that though the proposed strategy is applicable for worsening fault cases in NSVs, systematic and accurate criteria for the process being performed are necessary and can improve the FTC efficiency with minimal FTC resources. Additionally, such criteria can improve the NSV's responsiveness to comprehensive faults, provided that the real-time performance of the fault detection and diagnosis (FDD) scheme can be further optimized. The concomitant observer convergence and the multi-level FTC strategy have been verified by numerical simulations based on the Matlab/Simulink platform. [ABSTRACT FROM AUTHOR]

This paper proposes a decentralized adaptive event-triggered fault-tolerant cooperative control (ET-FTCC) scheme for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and external disturbances under denial-of-service (DoS) attacks. The multiple UAVs and UGVs have a larger search radius, which is important in both the civilian and military domains. The different dynamics between UAVs and UGVs result in unbalanced interactions in the communication topologies, which increases the complexity of cooperative control. DoS attacks are conducted in both sensor and control channels. The dynamic models of UAVs and UGVs are introduced firstly, and the unified heterogeneous multiagent system model with actuator faults is established. The composite observer is designed to obtain the information of state and lumped disturbance, which is used to design the controller. In order to save the limited communication network resources, the event-triggered mechanism is introduced. The transformed error is presented by using the prescribed performance function (PPF). Then, the sliding-mode manifold is presented by combining the event-triggered control scheme to achieve the tracking purpose with actuator faults, external disturbances, and DoS attacks. Based on the Lyapunov function approach, the tracking errors are bounded within the prescribed boundary. Finally, the effectiveness of the proposed method is verified by qualitative analysis and quantitative analysis of the simulation results. This study can enhance the security and reliability of heterogeneous multiagent systems, providing technical support for the safe operation of unmanned systems. This paper mainly solves the FTCC problem of second-order nonlinear heterogeneous multiagent systems, and further research is needed for the FTCC problem of higher-order nonlinear heterogeneous multi-agent systems. In addition, the system may encounter multiple cyber attacks. As one of the future research works, we can extend the results of this paper to high-order nonlinear systems under multiple cyber attacks, which contain DoS attacks and deception attacks, and achieve fault-tolerant cooperative control of heterogeneous multiagent systems. [ABSTRACT FROM AUTHOR]

This paper reviews the application of Hall position sensors in control and position estimation of permanent magnet synchronous motors (PMSMs). Accurate rotor position and motor speed data are essential for the high-efficiency control of PMSMs in modern industry. Rotor position and motor speed can be measured by mechanical position sensors, which are costly and less reliable, or by rotor position observers, which are sensitive to system models and changes in motor parameters. This paper examines the benefits, limitations, challenges, and uses of low-resolution Hall position sensors in PMSM drives, presenting them as a cost-effective solution for achieving a balance between performance and expense. In addition, the paper discusses recent solutions to issues related to misplaced Hall position sensors and fault-tolerant control algorithms, and gives an outlook to future developments in this area. [ABSTRACT FROM AUTHOR]

In this article, a fault-tolerant tracking control technique is developed for the ascent of hypersonic vehicles (HSV) experiencing wing damage and time-varying state constraints. The difficulty of control problem lies in handling state constraints associated with both state and time, while determining the unknown control directions of the multi-input multi-output (MIMO) nonlinear system. The presence of constraints in both state and time complicates the design of the control algorithm. This paper proposes the construction of a novel state transition function to establish a new unconstrained system, thereby eliminating the conservative feasibility conditions of Barrier Lyapunov Function (BLF) and integral BLF methods when dealing with time-varying constraints. The fusion of time-varying scaling functions and Nussbaum-type functions not only resolves the issue of unknown control directions in the MIMO nonlinear system but also enhances the transient and steady-state performance of the closed-loop system. Neural Networks are employed to approximate the unknown nonlinear functions. Using Lyapunov stability theory, it is proven that state constraints are not violated, and all signals in the closed-loop system are bounded. Simulation results demonstrate the merits of the designed fault-tolerant control (FTC) algorithm. • A unified fault-tolerant control scheme for the ascent hypersonic vehicle is designed. • Wing damage and function constraints on states are considered. • Nonlinear mapping eliminates the feasibility conditions in barrier Lyapunov functions. • The unknown control direction issue in multivariable nonlinear systems is resolved. [ABSTRACT FROM AUTHOR]

The study targets uncertain coupling faults in robotic arm actuators and proposes a new fault-tolerant visual servo control strategy. Specifically, it considers both multiplicative and additive actuator faults within the dynamic of the robotic arm, treating the coupling faults and time-varying disturbances as an aggregate of concentrated uncertainties. A radial basis function neural network-based state observer is introduced to online approximate these concentrated uncertainties, which include fault information, eliminating the need for prior knowledge of faults. Furthermore, a fault-tolerant controller based on a non-singular fast terminal sliding mode is proposed, which separately decouples the nominal quantities and concentrated uncertainties and develops individual adaptive control laws for each. This effectively reduces the detrimental impact of coupled faults and disturbances on the system's performance, facilitating image feature trajectory tracking control with minimal jitter, high precision, and strong transient response capabilities. The stability of the state observer and the fault-tolerant controller has been substantiated through Lyapunov's theory. Lastly, numerical simulations validate the efficacy and robustness of the proposed fault-tolerant visual servo control approach. [ABSTRACT FROM AUTHOR]

For batch processes with small time delays and actuator partial fault, the existing methods based on iterative learning control still have some limitations, including the conservative and computationally burdensome of stability conditions and the limited fault-tolerant control capabilities. For this background, an iterative learning robust predictive fault-tolerant control method is developed, which integrates the Lyapunov–Razumikhin function method and derives stability conditions based on robust positive definite invariant set and terminal constraint set. With small time delays, the stability conditions of the system deduced using the Lyapunov–Razumikhin function are solved at a lower computational cost, which is due to the fact that the dimensionality of the stabilization condition is directly related to the size of the time delay, and thus the small time delay implies a lower dimensionality. Especially, the computational effort for solving the stability conditions online is reduced, allowing real-time control law gains to be obtained and combined with historical batches of control inputs, reducing the learning cycles of the system, and realizing stable tracking of the setpoints within shorter operating batches. Moreover, the robust positive invariant set and the set of terminal constraints are able to constrain the state of the system within a safe range for all possible uncertainties, bounded disturbances, and faults. This makes the proposed methods based on them more robust and fault tolerant. Finally, a nonlinear batch reactor is used as an example to demonstrate the effectiveness and feasibility of the developed method. [ABSTRACT FROM AUTHOR]

The problem of retargeting rigid body attitude with attitude constraints has been extensively investigated, whereas the challenge persists in maneuvering rigid-body attitude with multiple concurrent attitude constraints and finite sequential actuator faults. Finite sequential actuator faults, which can reduce controllability or destabilize the system, necessitate the implementation of fault-tolerant control strategies. Therefore, this paper aims to address the issue of redirecting spacecraft attitude subject to multiple attitude constraints and finite sequential actuator faults comprehensively. Firstly, we represent spacecraft attitude using unit quaternions and employ an artificial potential function to effectively handle multi-attitude constraints. The negative gradient direction guides the rigid-body spacecraft towards seamless convergence with the desired attitude. Our proposed unwinding strategy effectively avoids unwinding phenomena during large-angle spacecraft reorientation as well. Additionally, we design an adaptive compensation strategy for finite sequential actuator faults that enables real-time calculation of the fault compensation matrix under such actuator faults. Importantly, we propose an improved adaptive fault-tolerant back-stepping controller integrated with a potential function that effectively addresses both attitude constraints and finite sequential actuator faults simultaneously. Subsequently, stability analysis is conducted on the proposed controller to ensure its stability in practical applications rigorously. Finally, numerical simulations are performed meticulously to demonstrate the effectiveness and robustness of our proposed controller. [ABSTRACT FROM AUTHOR]

This research focuses on the issue of adaptive fuzzy fault-tolerant position tracking for permanent magnet synchronous motors (PMSMs) subject to finite-time prescribed performance. An improved finite-time prescribed performance control strategy, in which unknown nonlinear functions can be tackled via fuzzy logic systems (FLSs), is presented via incorporating the approach of prescribed performance control with the technique of command filter. In addition, the command filtered method is utilized to conquer the 'explosion of complexity' emerged in the classic backstepping method and the error compensation mechanism is adopted to diminish the error generated by filtering process. Further, the impact of actuator failures is dealt with based on fault-tolerant control. It is proven that the designed controllers not only assure the semi-global boundedness of all the controlled system signals, but also make the output tracking error is preserved in a specified prescribed performance within a finite-time interval. Finally, simulation results are supplied to display the significance and potential of the proposed control technique. [ABSTRACT FROM AUTHOR]

This paper proposes a novel fault-tolerant control (FTC) scheme for real-time uncertainty estimation in nonlinear systems. It addresses the challenges arising from nonlinear dynamics in system inputs, states, and outputs, along with measurement uncertainties, within an output feedback framework. Our approach leverages two key components: 1) A neural network NN descriptor-based observer: this novel observer concurrently estimates both system states and sensor uncertainties. It is particularly capable of handling unbounded sensor uncertainties in specific situations. It utilizes NNs as universal approximators to capture the system's complex nonlinearities. 2) A robust model reference tracking controller: this controller employs the estimated states from the NN descriptor-based observer to achieve the desired system performance despite the existence of uncertainties. It exhibits robustness, guaranteeing system stability and asymptotic state tracking to a given reference model. The efficacy of the proposed FTC scheme is validated through theoretical analysis and its application to two real-world case studies. • Addressing systems with nonlinear inputs, states, and output dynamics, and modeling them using NN approximators. • Handling unknown and maybe potentially unbounded additive uncertainties. • Introducing a new model for all nonlinearities and sensor uncertainties and augments the system as a descriptor system. • Designing an observer to concurrently estimate the state of the original system and measurement uncertainties. • Using the MRC technique to handle stable and unstable systems with unknown parameters, ensuring the desired performance. [ABSTRACT FROM AUTHOR]

Currently, key factors hindering application of steer-by-wire systems are their inadequate safety and reliability, which are significant criteria for evaluating automotive active safety. Based on the steer-by-wire platform, a dual-redundant steering motor control system is proposed, featuring dual three-phase permanent magnet synchronous motors as execution motors, achieving redundancy from hardware. A torque vector-space-decoupling control method is introduced for these motors to ensure balanced and stable torque output. Upon a fault, fault-tolerant measures are taken by disconnecting power supply to the affected motor, which, despite reducing system functionality, allows for normal steering control. This research starts with modeling the dual three-phase motors to construct a simulation model. It then proceeds with hardware-in-the-loop testing integrated with the dual-redundancy steer-by-wire control system, conducting tests under dual-lane-change trajectory conditions. Finally, a steering system fault is simulated to assess fault handling and functional degradation. These experiments confirmed that the proposed method enabled balanced torque output from the dual three-phase motors in the redundant steering control and facilitated fault-tolerant processing post fault, ensuring the vehicle's steering functions were maintained. [ABSTRACT FROM AUTHOR]

Electro-mechanical brake (EMB) systems have garnered significant attention due to their distributed architecture. However, their signals from the brake pedal to the wheel-end actuators (WEAs) are transmitted electrically, meaning that any fault in EMB systems can severely impair the braking performance of vehicles. Consequently, the functional safety issues of EMB systems are the primary limitation of their widespread adoption. In response, this study first introduced the typical architectures of EMB and evaluated the automotive safety integrity level (ASIL) that must be achieved. Based on this, an EMB system architecture that satisfies functional safety standards was proposed. To accurately analyze the main factors affecting the probabilistic metric for hardware failures (PMHF) of the architecture, the failure rate of WEAs is further discussed. Specifically, a Markov chain was employed to define the operating states of the WEA matrix. The availability of each operating state was assessed based on the fault-tolerant control strategy. Finally, the failure rates of critical EMB parts, particularly the WEA matrix, were calculated. The results indicate that the unavailability of the WEA matrix is 9.244 × 10−3 FIT. Furthermore, the PMHFs of the EMB system for each safety goal are 6.14 FIT, 5.89 FIT, and 6.03 FIT, respectively, satisfying the ASIL-D requirements. [ABSTRACT FROM AUTHOR]

This study presents a comparative analysis of control strategies designed to enhance the performance of Anti-Lock Braking Systems (ABS) and improve vehicle safety. The research explores three key approaches: First, it evaluates Fuzzy Logic-Controlled ABS, comparing five defuzzification algorithms using MATLAB's Fuzzy Logic Toolbox. Second, it investigates a Neural Network-Based Fault-Tolerant Control strategy, emphasizing improved fault tolerance during braking. Third, it assesses the performance of three ABS controllers--fuzzy logic, bangbang, and PID controllers. The findings reveal that Fuzzy Logic-Controlled ABS significantly enhances braking performance and directional stability, while Neural Networks demonstrate rapid response and accuracy in generating real-time substitute signals, thereby boosting system reliability. Among the controllers, the PID controller excels in reducing stopping distance and time, though the Fuzzy Logic Controller shows superior control over relative slip, enhancing steerability despite longer stopping distances and times. This comparative analysis provides valuable insights into ABS control strategies and their implications for vehicle safety. Future research should focus on refining ABS algorithms, developing robust fault detection mechanisms, and optimizing controller designs to further advance automotive safety and ABS efficiency. [ABSTRACT FROM AUTHOR]

In practice, the time-varying communication delays and actuator failures are the main inevitable issues in nonlinear multilateral teleoperation systems, which can reduce the performance and stability of the considered systems. This article proposed a novel failure-distribution-dependent H ∞ fuzzy fault-tolerant control scheme to realize position synchronization and force tracking simultaneously for multilateral teleoperation systems. Firstly, the nonlinear multilateral systems were modeled as a kind of T-S fuzzy systems with multiple time-varying delays. Then, based on the distribution characteristic of failures, by introducing a series of tradeoff coefficients, a novel failure-distribution-dependent fault-tolerant control algorithm was provided to ensure force tracking in spite of failures, and the purpose of position synchronization was achieved (not only the master and slave robot position synchronization but also the position synchronization between each slave robot). Finally, a numerical simulation example was given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, the adaptive event-triggered fault-tolerant control (FTC) issue of uncertain nonlinear systems suffering from sensor and actuator faults as well as external disturbances is studied. A disturbance observer (DO) is constructed to compensate for external disturbances and approximation errors generated by neural networks (NNs). Then, switching event-triggered control and command filtering techniques are introduced to balance the communication frequency and tracking performance of the controlled systems while avoiding “explosion of complexity” issue caused by iterative derivations of virtual controllers. Furthermore, compensation signals are designed to eliminate filtered errors. Finally, it is proven that the developed FTC scheme can esure that all signals are bounded and free from Zeno phenomenon. Simulation results of a spring damping mechanical system verifies the merits of the designed control algorithm. [ABSTRACT FROM AUTHOR]

Effective fault identification and management are critical for efficient wind turbine operation. This research presents a novel L 1 adaptive- SMC system designed to enhance fault tolerance in wind turbines, specifically addressing common issues such as pump wear, hydraulic leakage, and excessive air content in the oil. By combining SMC with L 1 adaptive control, the proposed technique effectively controls rotor speed and power, ensuring reliable performance under various conditions. The controller employs an adjustable gain and an integrated sliding surface to maintain robustness. We validate the controller's performance in the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) simulation environment using a 5-megawatt wind turbine under high wind speeds. Simulation results demonstrate that the proposed L 1 adaptive- SMC outperforms traditional adaptive- SMC and adaptive control schemes, particularly in the presence of faults, unknown disturbances, and turbulent wind fields. This research highlights the controller's potential to significantly improve the reliability and efficiency of wind turbine operations. [ABSTRACT FROM AUTHOR]

This paper is concerned with nonlinear disturbance observer (DO)-based geometric attitude fault-tolerant control (FTC) problem of quadrotor unmanned aerial vehicles (UAVs) subject to system uncertainties, exogenous disturbances, and actuator faults. A disturbance observer-based control (DOBC) framework is devised to tackle the difficulties caused by system uncertainties and external disturbances. The FTC is proposed to cope with the occurrence of actuator faults which can be modelled as a constant loss of effectiveness. The proposed design scheme can provide an effective way to analyse the stability of the closed-loop system, which can ensure the asymptotical convergence of the error. The other method considers actuator failures as part of the lumped disturbance, and the attitude tracking problem of quadrotors concerning the lumped disturbance is solved by the DO-based control method, which can ensure the exponential convergence of the error. The numerical simulations are performed to illustrate the effectiveness of the design techniques. [ABSTRACT FROM AUTHOR]

This paper investigates the fault-tolerant control problem for vehicular platoons with time-varying actuator fault directions and distance constraints. A bias constraint function is introduced to convert the asymmetric constraints into symmetric ones, based on which a unified barrier Lyapunov function (BLF) method is proposed to ensure distance constraints. Further, an adaptive fixed-time fault-tolerant controller in the context of a sliding mode control technique is proposed, wherein a new Nussbaum function is adopted to address the effects of unknown time-varying actuator fault directions. It is proved that both individual vehicle stability and string stability can all be guaranteed, and the effectiveness of the proposed algorithm is verified through numerical simulations. [ABSTRACT FROM AUTHOR]

Road vehicles and maglev trains have garnered significant attention, with their suspension systems being crucial for safe and stable performance. However, these systems can be compromised by faults such as sensor and actuator failures, posing risks to stability and safety. This review explores fault-tolerant controls for suspension systems, driven by the need to enhance fault tolerance in such scenarios. We examine the dynamic similarities between the semi-active/active suspension systems in road vehicles and the suspension systems in maglev trains, offering a comprehensive summary of fault-tolerant control strategies for both. Our analysis covers the histories, technical characteristics, fundamentals, modeling, mathematical derivations, and control objectives of both systems. The review categorizes fault-tolerant control methods into hardware redundancy, passive fault-tolerant control, and active fault-tolerant control. We evaluate the advantages and disadvantages of these strategies and propose future directions for the development of fault-tolerant control in suspension systems. [ABSTRACT FROM AUTHOR]

• We propose a novel adaptive sliding mode based spacecraft attitude controller. • The boundary of the model uncertainty and external disturbance is not required. • Actuator failure and saturation problem is considered by using an RBF network. • A control gains reduction technique is applied to weaken chattering phenomenon. Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method. [ABSTRACT FROM AUTHOR]

A low-complexity global fault-tolerant control method is proposed to solve the tracking problem of uncertain pure-feedback systems in the presence of sensor faults. First, a novel modeling approach is introduced to reconstruct the non-affine term, which removes the restriction that the non-affine function must be differentiable. Second, a novel nonlinear mapping based on inverse-tangent function is utilized in the controller design such that the control parameters are free from initial values of states compared to the traditional prescribed performance control methods, resulting in global fault-tolerant control of pure-feedback systems under sensor and actuator faults. Furthermore, the designed global controller is low-complexity in the sense that no time derivatives of system signals are involved in the controller, and no neural networks or fuzzy logic systems are used, though unknown nonlinearities are present in the considered systems, and the control parameters are allowed to be arbitrary positive constants. Finally, the proposed method is applied to numerical and tailless fly-wing UAV examples, which fully demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study explores fault-tolerant consensus in leader–following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler–Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Purpose: The multi-objective optimization configuration strategy is proposed due to the configuration of EMAs in fault-tolerant control of active magnetic bearing with redundant electromagnetic actuators involving high-dimensional, nonlinear, conflicting goals. Design/methodology/approach: A multi-objective optimization model for bias current coefficients is established based on the nonlinear model of active magnetic bearings with redundant electromagnetic actuators. Based on the non-dominated sorting genetic algorithm III, a numerical method is used to obtain feasible and non-inferior sets for the bias current coefficient. Findings: (1) The conflicting relationship among the three optimization objectives was analyzed for various failure modes of EAMs. (2) For different EMAs' failure modes, the multi-objective optimization configuration strategy can simultaneously achieve the optimal or sub-optimal effective EMF, flux margins, and stability of EMF. Moreover, the characteristics of the optimal Pareto front are consistent with the physical properties of the AMB. (3) Compared with the feasible configuration of C0, the non-inferior configurations can significantly improve the performance of AMB, and the advantages of the multi-objective optimization configuration strategy become more prominent as the asymmetry of the residual supporting structure intensifies. Originality/value: i) Considering the variation of the rotor displacement during the support reconstruction, a decision-making model that can accurately characterize the dynamic performance of AMB is presented. (ii) The interaction law between AMB and rotor under different failure modes of EMAs is analyzed, and the configuration principles for redundant EMAs are proposed. (iii) Based on the dynamic characteristics of AMB during the support reconstruction, effective EMF, energy consumption, and the Pearson correlation coefficient between the desired EMFs and the decoupled control currents are used as objective functions. iv. The NSGA-III is combined with the decision-making model to address the multi-objective optimization configuration problem of C0. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes open‐phase fault detection (FD) and tolerant control strategies for wye‐connected three‐phase induction machines (WCTPIMs). The FD mechanism is based on the comparison between predicted and actual values of stator currents, and the control approach is derived from the field‐oriented control (FOC). In the proposed fault‐tolerant control (FTC) method, an asymmetrical current transformation is used for stator current components, and the conventional symmetrical voltage transformation is employed for stator voltage components. It is shown that using these transformations, a modified FOC can be employed for the faulty WCTPIM. The suggested scheme is able to control WCTPIM drives under normal and single open‐phase fault (SOPF) modes with minor adjustments. Experimental results achieved from a laboratory prototype confirm the possibility and good performance of the proposed open‐phase FD and tolerant control for the WCTPIM under different operating conditions. [ABSTRACT FROM AUTHOR]