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To ensure the three-level neutral point clamped (NPC) grid-connected inverter in a grid-connected system continuous operation after a single-phase bridge arm short circuit or open circuit failure, an optimal compensation fault-tolerant control strategy with low common-mode voltage is proposed in this paper, which is based on space vector pulse width modulation (SVPWM). Firstly, the reference voltage vector synthesis rule is determined by analyzing the common mode voltage corresponding to the switch state of the eight-switch three-phase inverters (ESTPI), which is the topology of the three-level NPC inverter with one phase failure. Then, the mechanism of neutral point potential fluctuation is analyzed by the neutral point current change in a fundamental wave period. Further, the space vector synthesis is compensated based on this mechanism. Finally, the low-pass filter and hysteresis controller are designed to optimize vector synthesis compensation, so as to ensure the quality of grid-connected current and effectively restrain the neutral point potential offset of the DC bus. The simulation results show that the proposed fault-tolerant control strategy can realize the stable and reliable operation of the grid-connected system after single-phase bridge arm failure, and the common-mode voltage can be reduced for one-third of the period time. The quality of grid-connected current is improved significantly. The proposed controller has good control characteristics when the grid-connected current changes.

The main drive system of the rolling mill often experiences torsional vibrations, which severely affect product quality, precision, and the service life of the transmission equipment. This paper investigates the torsional vibration suppression problem in the main drive system of the rolling mill, considering actuator faults, nonlinear friction, nonlinear damping, and model uncertainties. Based on the high-order fully actuated (HOFA) system approach, the main drive system of the rolling mill is transformed into a rolling mill main drive fully actuated system (RMMDFAS). Adaptive neural networks are introduced to address unknown uncertainties, and a continuous differentiable Gaussian error function is used to handle actuator faults. An adaptive neural network fault-tolerant control law for motor torque is proposed. The stability of the designed main drive torsional vibration system is rigorously proven, while maintaining the performance of the transformed states. Finally, the effectiveness and superiority of the proposed algorithm are verified through simulations.

Because of their attractive features, switched reluctance motors (SRMs) are strong candidates with real chances on the market for several industrial applications including vehicle propulsion. However, the SRMs suffer from torque ripple and associated acoustic noise. A proper control algorithm can handle torque ripples to an accepted limit. However, the internal faults in stator windings of SRMs deteriorate not only the performance of control algorithm but also the output power, efficiency, and noise (torque ripple). They cause fast degradation of motor lifetime. Therefore, this paper introduces a novel method to counteract the internal faults in winding of SRMs. A new simulation method for SRMs including the capability of interturn faults is introduced. The proposed novel interturn fault tolerant control (FTC) is achieved based on average torque control (ATC) algorithm. The switching angles are optimized smartly providing a less complicated control algorithm to fit properly with the industrial platforms. The simplicity of overall control algorithm is still functional. The performance of proposed FTC is evaluated compared to healthy motor conditions as well as faulty conditions. The results show the superior performance of the proposed control.

This study focuses on fault-tolerant finite-time flight-path angle control for an aircraft in the presence of external disturbances, unknown deadzone and actuator fault. To begin with, the longitudinal model of aircraft is introduced for the subsequent controller design. Then, a new smooth deadzone inverse model is presented to compensate for the deadzone nonlinearity in aircraft system. A robust adaptive fault-tolerant finite-time control law is derived by using backstepping adaptive control approach, where a finite-time stability criterion is adopted for developing practical finite-time control. In order to reduce the difficulty of control system design, two finite-time differentiators are used to estimate the derivatives of virtual control signals. The coupling errors of the deadzone and faults are properly dealt with by estimating the unknown bounds. Finally, comparative numerical simulation results are provided to demonstrate the efficiency of the proposed fault-tolerant finite-time flight-path angle control scheme.

This paper proposes a robust sampled-observer-based fault-tolerant min-type switching law for a class of continuous-time uncertain switched affine systems (SAS) subject to persistent bounded sensor faults using Luenberger observers to estimate the system state. The switching law is designed to make the trajectories of the system be attracted to an open ball containing a given equilibrium point, even in the presence of faults and norm-bounded uncertainties. First, nonlinear matrix conditions are given to obtain the switching law that guarantee the practical stability of a class of uncertain SAS whenever persistent bounded sensor faults are present. To reduce the complexity of the nonlinear matrix conditions, we thus provide LMI-based conditions to obtain the observer gains at the cost of increasing the estimation of the ball for which the trajectories of the system are attracted. Next, we estimate the radius of the open ball by solving a minimization problem using the gains obtained by satisfying the LMI conditions. We then propose an algorithm to search for a set of equilibrium points for a class of uncertain SAS with two system modes, which can be applied to DC-DC converters such as boost, buck, buck-boost, and Cuk converters. Finally, experiments using hardware in the loop of a bidirectional buck-boost DC-DC converter illustrate the efficiency of the fault-tolerant strategy.

Given the continuous development of society and the escalating demand for clean energy, there is an imperative focus on wind farm control to overcome the primary obstacle hindering wind farm development: high operation and maintenance costs. This paper presents innovative solutions for intelligent fault-tolerant active power control design based on reinforcement learning, aiming to optimize the balance between grid load and wind farm active power. The proposed solutions effectively handle a range of fault scenarios, addressing both active power control and frequency regulation while safeguarding faulty wind turbines against further deterioration. Through comprehensive simulations conducted on a wind farm benchmark model, the efficacy of these solutions and strategies is demonstrated, showcasing their ability to achieve both passive and active fault-tolerant control across diverse load and fault scenarios.

Motivated by the demand for formation security, this paper studies the fault-tolerant control problem for fixed-wing UAV formation with switching topologies. Based on the application of fixed-wing UAV formation in scenarios involving various severities of faults, this article employs a leader-follower formation control method, focusing on addressing actuator faults, saturation, failures and the consequent communication faults. These challenges are approached as a problem of fault-tolerant control with switching topologies. To tackle these problems, the article delves into the impact of UAV network connections on nodes through neighboring interactions and proposes a novel fault-tolerant formation control method based on graph theory, observer theory, output regulation, and $\mathrm {H}_{\infty} $ robust control theory, which is concluded as an algorithm. The method aims to effectively manage the complexities arising from fault occurrences and ensure the formation cooperative performance. Finally, the proposed control method’s effectiveness is demonstrated in a formation with one leader and four followers through numerical simulations, with a comparative analysis against an alternative method. A formation security schema is developed to provide an application scenario of the proposed method for different kinds of fixed-wing UAV formations.

In this study, a robust $H_\infty$ observer-based PID path tracking control strategy is proposed for Autonomous Ground Vehicle (AGV) to efficiently attenuate the effect of external disturbance, actuator/sensor fault signals, and control saturation to achieve the robust path tracking design. To simplify the design procedure, a novel path reference-based feedforward linearization scheme is proposed to transform nonlinear dynamic AGV system to an equivalent linear tracking error system with nonlinear actuator signal. To protect the AGV system from the corruption of actuator/sensor fault signals, two smoothed signal models are introduced to precisely estimate these fault signals to compensate their corruption. Further, the proposed $H_\infty$ fault-tolerant observer-based PID path tracking control strategy of AGV system can be transformed to an equivalent bilinear matrix inequality (BMI). Consequently, by the proposed two-step method, the complex BMI can be transformed into two linear matrix inequalities (LMIs), which can be easily solved via LMI TOOLBOX in MATLAB. Therefore, control restriction is also considered to meet the constraints of physical actuator saturation on PID controller, making the proposed control scheme more applicable. Finally, the triple-lane change task of AGV is simulated as a numerical example to illustrate the design procedure and to validate the performance of proposed design method.

This article addresses the collaborative wildfire tracking problem in air-ground heterogeneous multiple agent systems (HMAS) with faulty actuators during fire tracking missions. A fault-tolerant dynamic formation control technique is proposed to enable HMAS to dynamically track wildfire propagation using the fractional-order nonsingular terminal sliding mode (FO-NFTSM) control approach. Additionally, a higher-order sliding mode observer (HOSMO) is designed to estimate unavailable linear velocities and multi-source disturbances arising from external disturbances, system uncertainties, and actuator faults. The results demonstrate the effectiveness of the proposed control technique in guiding all agents for accurate wildfire tracking, leading to the convergence of collaborative tracking errors within a finite time. Comparative numerical simulations further validate the efficiency of the proposed approach.

Summary: Due to the long‐term operation of the tower crane, various faults will inevitably occur, such as actuator faults, which further increases the difficulty of controller design. In this paper, a fault‐tolerant control method with adaptive gain is proposed for the double‐pendulum tower crane with distributed payload beam (DTCDPB) system in the existence of external disturbances and actuator failures. First, a nonlinear fault‐tolerant observer is designed for fault diagnosis. Second, an S‐shaped trajectory functions are coupled online and embedded into the system target trajectories for payload swing suppression. Then, feedforward compensation is applied in the controller for the observed faults. Moreover, the adaptive suppression term to be activated is also designed in the controller taking into account the errors existing in the observation. Finally, the effectiveness of the proposed observer and controller is experimentally verified. [ABSTRACT FROM AUTHOR]

The practical preset time fault‐tolerant control (FTC) problem is explored in this article for uncertain Euler–Lagrange systems with input saturation and guaranteed performance. To cope with the uncertainty of the Euler–Lagrange systems, the adaptive neural network (NN) is exploited to approximate the unknown continuous function. Most existing results that consider input saturation and actuator faults simultaneously need to design compensation strategies separately, which increases the complexity of control algorithms. To overcome the above obstacle, the Nussbaum gain technique is used to deal with the effects of input saturation and actuator faults in this article. Besides, with the help of error transformation technology and speed function, the proposed control algorithm can ensure that the tracking error converges within the preset time and its overshoot is constrained within the prescribed performance boundaries. Furthermore, the boundedness of all closed‐loop system signals is confirmed. Finally, comparative simulation results are depicted to highlight the superiority of the designed control algorithm. [ABSTRACT FROM AUTHOR]

This article is concerned with the fixed‐time fault‐tolerant control problem of multiple Euler–Lagrange systems (MELSs) with intermittent communication, actuator faults and input disturbances. A nonsingular fixed‐time control framework with three parts is built for the above problem. In the first part, a novel adaptive controller is proposed for MELSs to ensure the fixed‐time stability of sliding modes while successfully solving the actuator faults, parameter uncertainties and unknown disturbances. In the second part, the fixed‐time estimators based on event‐triggered communication are designed by an error decomposition approach. In the third part, an auxiliary system is introduced for the singularity problem and sufficient condition for achieving the consensus is rigorously proved by synthesizing the results of the above two parts. The key feature of the proposed control framework is that the convergence time is constrained by a constant without involving initial states, and the singularity problems of fixed‐time control is avoided. Finally, simulation examples are provided to prove the efficacy of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Summary: This work primarily concentrates on the design of fault‐tolerant anti‐disturbance control for synchronization of multiple memristor‐based neural networks subject to time delay, matched and mismatched disturbances. Moreover, in the addressed network model, we consider parameter uncertainties and actuator faults. Firstly in order to estimate the matched disturbances generated by the exogenous system, a disturbance observer is devised. Whereas, the mismatched part is tackled by employing the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Subsequently, a unified controller is designed by incorporating error feedback control and the disturbance estimate. Further, with the assistance of Lyapunov stability theory and linear matrix inequality technique, an adequate criteria is procured to ascertain the required synchronization criteria for the assayed network model with the mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passivity performance indexes. Following this, by basing on the established conditions, the explicit form of the controller and observer gain matrices is obtained. In the end, a numerical example with simulation results is shown to confirm the potential and usefulness of the conclusions acquired from the theoretical analysis. [ABSTRACT FROM AUTHOR]

This research provides a method that accelerates learning and avoids local minima to improve the policy gradient algorithm’s learning process. Reinforcement learning has the advantage of not requiring a model. Consequently, it can improve control performance, mainly when a model is generally unavailable, such as when an error occurs. The proposed method efficiently and expeditiously investigates the action space. First, it quantifies the resemblance between agents’ and traditional controllers’ actions. Then, the principal reward function is modified to reflect this similarity. This reward-shaping mechanism guides the agent to maximize its return via an attractive force during the gradient ascent. To validate our concept, we establish a satellite attitude control environment with a similarity subsystem. The outcomes demonstrate the effectiveness and robustness of our method. [ABSTRACT FROM AUTHOR]

This study proposes a non-fragile fault-tolerant control design based on adaptive robust observer for a type of Markov-type active suspension system with sensor and actuator faults under the external road disturbance. First, the faulty active suspension system is reconfigured into an augmented system by extending the sensor fault as part of the system state vector. Then, an appropriate adaptive observer is designed to estimate the sensor fault, the actuator fault, as well as the active suspension system states simultaneously. Afterwards, an expected non-fragile fault-tolerant control scheme based on state feedback technology is presented to asymptotically stabilize the vertical and pitch motions of the faulty active suspension system. Benefit from its non-fragility, the proposed controller has been proven to be highly stable against its internal gain perturbation. Finally, the comparative simulation results of a half-vehicle active suspension system are provided to validate the effectiveness of the proposed fault-tolerant controller. It is shown that the designed adaptive observer can precisely estimate the sensor and actuator faults, together with the active suspension system states, and the designed non-fragile fault-tolerant control controller can effectively compensate the performance loss of the faulty active suspension system and improve the reliability of the vehicle active suspension system. [ABSTRACT FROM AUTHOR]

The problem of robust, angular velocity-free control and fault-tolerant control for liquid-filled flexible spacecraft attitude maneuver subject to unknown external disturbances is investigated. Moreover, state variables measurement uncertainty and actuator failures are explored. The liquid sloshing effect of spacecraft fuel is equivalent to a two-order spring-mass model, and the flexible attachments are equivalent to the Euler–Bernoulli beams. The external disturbance, multiple failures of the output actuator, and the coupled interference caused by liquid sloshing and vibrations of flexible attachments are distinguished as continuous and percussive disturbances. First, a fault-tolerant control method against the percussive disturbances is proposed, and the robustness performance and characteristics of this method are analyzed. Then, both continuous and percussive disturbances are considered to propose a new fault-tolerant control method based on a nonlinear disturbance observer, which is used to estimate the integrated disturbance. The Lyapunov stability theory proves that the proposed control strategy can make the state variables converge to a small neighborhood of the origin in finite time. Finally, the numerical simulation is used to verify the effectiveness and robustness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations. Design/methodology/approach: First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers' location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance. Findings: It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy. Originality/value: A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network. [ABSTRACT FROM AUTHOR]

This paper focuses on the trajectory tracking problem of nth-order uncertain nonlinear systems with sensor faults. The proposed approach utilizes a fuzzy observer to estimate the unmeasurable states in the systems. Moreover, the finite-time control strategy and the command filtered technique are added in the controller design. The former aims to enhance the systems' response speed, and the latter is to mitigate the "differential explosion" problem. Meanwhile, the adaptive technique is incorporated to compensate for sensor faults. The boundedness of all the signals within the closed-loop systems is confirmed through stability analysis. Finally, the effectiveness of the proposed approach is verified through two simulation examples. [ABSTRACT FROM AUTHOR]

Due to the widespread application and significant investment required for a single crane, there is an increased emphasis on crane safety and service life. Fault-tolerant control as an effective solution to unexpected faults has been widely studied recently. However, most fault-tolerant control methods require redundant actuators or a complex design process, which is unsuitable for the tower crane. Following these problems, a fault-tolerant controller based on an adaptive backstepping technique is proposed. Firstly, the system states are reconstructed and written as a cascade system. Secondly, a fixed-time convergence optimized backstepping controller is proposed to achieve smooth control of the tower crane without generating sudden or abrupt values. Then, an adaptive approach has been proposed to update fault parameters for the crane system in case of a sudden fault occurrence. Finally, after conducting comparison tests, it has been determined that the proposed controller not only performs exceptionally well in terms of position accuracy and swing elimination, but also maintains a satisfactory control performance when faced with sudden faults. • The jib and trolley positioning and load swing suppression problems for tower cranes are investigated. • The adaptive backstepping fault-tolerant controller is designed. • The control performance is demonstrated by comparative experiments. [ABSTRACT FROM AUTHOR]

In this article, the problems of fault diagnosis (FD) and fault-tolerant control (FTC) are investigated for a class of nonlinear systems with output measurement noise. Due to the influence of measurement noise in the output sensor, the output observation error cannot be accurately obtained, which causes obstacles to the accuracy of FD. To address this issue, an output filter and disturbance estimator are constructed to decrease the negative effects of measurement noise and observer gain disturbances, and a novel non-fragile neural observer is designed to estimate the unknown states. A new evaluation function is also introduced to detect faults. Then, a novel neural FTC controller is proposed in the presence of faults, to ensure that all the closed-loop system signals are semiglobally uniformly ultimately bounded (SGUUB). The effectiveness of the proposed methodology is verified via numerical simulation of a one-link robot system. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The apparition of faults is a well-known phenomenon in automatic control systems. Faults cause undesired behaviour and disruption of a controlled plant, which can lead to damage. This article addresses the actuator fault problem for nonlinear systems described by a discrete time Takagi–Sugeno fuzzy systems. An active fault-tolerant control based on a fault estimator is designed using the matrices norms approach instead of the usual Lyapunov stability theory. In this work, we consider the case where the premise variables do not depend on the unmeasurable variables. This allows the separate design of the gains of the controller, the observer and the estimator. Two nonlinear systems represented by discrete Takagi–Sugeno fuzzy models are studied to investigate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

The manuscript proposes a data-based integral terminal sliding mode control approach to determine fault-tolerant control (FTC) concerning a class of discrete-time nonlinear systems (DTNS) containing sensor fault. The proposed scheme can be readily implemented because it purely utilizes the input and output data of the system to employ a model called the compact form dynamic linearization (CFDL) data model, while the one-step forward approximator is employed to estimate the fault function term in the system. Moreover, the fault diagnosis mechanism utilizes a time-varying threshold with prescribed performance to judge whether the fault occurs. Hence, the problem of a standard fixed threshold used at the start-up state of the control system is resolved. Then, the discrete-time integral terminal sliding mode fault-tolerant control (DITSM-FTC) method is proposed. Concurrently, the sturdiness of the proposed method is assured by hypothetical investigation. When compared with the literature, the fundamental features of the proposed method are presented as follows: (1) the problem pertinent to fault utilizing a data-driven model is resolved; (2) a fault diagnosis mechanism with prescribed performance is proposed, and (3) one step forward approximator is utilized to devise an estimation approach of fault detection. Finally, the efficacy of the proposed method is presented by running simulations. [ABSTRACT FROM AUTHOR]

This paper provided a robust strategy for controlling nonlinear interconnected large-scale systems subject to a sensor fault. The inherent challenge in controlling such systems is to sustain robust closed-loop stability and performance in nonlinear interactions, faults, and exogenous inputs. A new closed-loop structure has been devised to tackle this challenge by integrating the sliding mode controller with the unknown input observer. By exploiting the decoupling capability of the controller and observer, this integration ensures the robustness of the closed-loop system against the simultaneous effect of interaction, fault, and disturbance. In this context, the unknown input observer has been constructed to supply the controller with an accurate sensor fault assessment despite additional unknown inputs. A novel approach is proposed for designing a decentralized fault-tolerant control system that utilizes sliding mode control and proportional-integral-derivative controller tuning via a bacterial foraging optimization algorithm to compensate for the fault effect, leading to a robust output performance. The observer and controller gains are accomplished by utilizing the H∞ performance and linear matrix inequality formulation. The Lyapunov technique is used to demonstrate stability. A power system model emphasizes the proposed approach's robustness and effectiveness. The system performance with and without the proposed controller was compared, where the simulation results show a fast reaction to offset undesirable impacts, whereas the state estimation error approaches to zero in each subsystem. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Electric ships have been developed in recent years to reduce greenhouse gas emissions. In this system, inverters are the key equipment for the permanent-magnet synchronous motor (PMSM) drive system. The cascaded insulated-gated bipolar transistor (IGBT)-based H-bridge inverter is one of the most attractive multilevel topologies for modern electric ship applications. Usually, the fault-tolerant control strategy is designed to keep the ship in operation for a certain period. However, the fault-tolerant control strategy with hardware redundancy is expensive and slow in response. In addition, after fault-tolerant control, the ship's PMSM may experience shock and overheating, and IGBT life is reduced due to uneven switching frequency distribution. Therefore, a stratified reconfiguration carrier disposition Sinusoidal Pulse Width Modulation (SPWM) fault-tolerant control strategy is proposed. The proposed strategy can achieve fault tolerance without any extra hardware. A reconfiguration carrier is applied to improve the fundamental amplitude of inverter output voltage to maintain the operation of the ship's PMSM. In addition, the available states of faulty H-bridge are fully used to contribute to the output. These can improve the life of IGBTs by reducing and balancing the power loss of each H-bridge. The principles of the proposed strategy are described in detail in this study. Taking a cascaded H-bridge seven-level inverter as an example, simulation and experimental results verify that the proposed strategy, in general, has a potential future application on electric ships. [ABSTRACT FROM AUTHOR]

With the development of safety technologies for intelligent commercial vehicles, electronic pneumatic braking systems (EBSs) have been widely used. However, EBS actuators may fail during vehicle operation and thus create safety problems. For this reason, we propose a path-tracking fault-tolerant control strategy under EBS actuator failure in intelligent commercial vehicles. First, in order to be able to characterize different types of brake actuator faults during the EBS differential braking process of a vehicle, a comprehensive fault coefficient for calculating the degree of fault is designed, and a BES generalized fault model is established. Second, the faults are introduced into the fault-tolerant controller through the comprehensive fault coefficients for braking torque calculation and braking pressure allocation. Thus, a vehicle path model with the complete fault coefficients as variable parameters is established. Then, based on the LPV system gain scheduling, a path-tracking LPV/H∞ fault-tolerant controller under EBS actuator faults in commercial vehicles is designed, which is used to solve the safety problem arising from sudden EBS actuator faults. Finally, we conducted experimental validation through hardware-in-the-loop tests. The results demonstrate that the control strategy designed in this paper redistributes the braking torque and synergizes with the steering system to enhance vehicle stability, thereby improving vehicle safety in the EBS failure mode. [ABSTRACT FROM AUTHOR]

A lack of available information on heating, ventilation, and air-conditioning (HVAC) systems can affect the performance of data-driven fault-tolerant control (FTC) models. This study proposed an in situ selective incremental calibration (ISIC) strategy. Faults were introduced into the indoor air ( T t z 1 ) thermostat and supply air temperature ( T s a ) and chilled water supply air temperature ( T c h w s ) sensors of a central air-conditioning system. The changes in the system performance after FTC were evaluated. Then, we considered the effects of the data quality, data volume, and variable number on the FTC results. For the T t z 1 thermostat and T s a sensor, the system energy consumption was reduced by 2.98% and 3.72% with ISIC, respectively, and the predicted percentage dissatisfaction was reduced by 0.67% and 0.63%, respectively. Better FTC results were obtained using ISIC when the T t z 1 thermostat had low noise, a 7-day data volume, or sufficient variables and when the T s a and T c h w s sensors had low noise, a 14-day data volume, or limited variables. [ABSTRACT FROM AUTHOR]

In the quest for unparalleled reliability and robustness within control systems, significant attention has been directed toward mitigating actuator faults in diverse applications, from space vehicles to sophisticated industrial systems. Despite these advances, the prevalent assumption of homogeneous actuator faults remains a stark simplification, failing to encapsulate the stochastic and unpredictable nature of real-world operational environments. The problem of finite-time fault-tolerant control for nonlinear flexible spacecraft systems with actuator faults is addressed in this paper, utilizing the T-S fuzzy framework. In a departure from conventional approaches, actuator failures are modeled as random signals following a nonhomogeneous Markov process, thus comprehensively addressing the issue of timeliness, which has previously been overlooked in the literature. To effectively manage the intricacies introduced by these factors, the nonhomogeneous Markov process is represented as a polytope set. The proposed solution involves the development of a nonhomogeneous matrix transformation, accompanied by the introduction of adaptable parameters. This innovative controller design methodology yields a stability criterion that ensures H ∞ performance in a mean-square sense. To empirically substantiate the effectiveness and advantages of the proposed approaches, a numerical example featuring a nonlinear spacecraft system is presented. [ABSTRACT FROM AUTHOR]

Aiming at the trajectory tracking task of quadrotor UAV under actuator malfunction, an adaptive fault-tolerant control method based on fuzzy gain sliding mode is proposed. Firstly, for the direct control channel, the adaptive mechanism is used to estimate and compensate for actuator faults and the sliding mode controller based on fuzzy gain is used to design the adjustable controller to meet the requirements of robustness. For the indirect drive channel, the sliding mode controller based on fuzzy gain is designed to achieve control of the UAV. This method has good fault-tolerant ability and it can suppress the system chatter and obtain smooth control signals. Finally, the tracking performance of the quadrotor UAV under different controllers is compared and simulated and the results show that the system has good flight performance in the presence of fault and interference. [ABSTRACT FROM AUTHOR]

T-type three-level inverters (T23LIs) are widely used in the electric drive system of new energy vehicles. However, the open-circuit (OC) faults of their switching devices will cause serious damage to the entire system operation. To mitigate the impact of switching faults, this paper proposes an OC fault diagnosis method based on the variations of common-mode voltage in small sectors of T23LI. Firstly, the normal characteristics of T23LI under SVPWM control algorithm are analyzed, and the correspondence between the space voltage vectors and the values of common-mode voltage is established. Then, the common-mode voltage variations under fault conditions are analyzed, and a fault diagnosis method based on these variations is proposed. The faults of the four switching devices in one phase is divided into two groups through the qualitative analysis of common-mode voltage variations, and the specific location of the faulty switch is located by further quantitative analysis. Finally, by analyzing the changes in the three-phase bridge output voltages after faults, the accurate location of the faults in the 12 switches of the three phases is located. Simulation and experimental results verify that the proposed method can accurately and quickly diagnose the single-switch OC faults of all switches, and it effectively accelerates the diagnosis speed and reduces costs by only requiring the collection of a single voltage signal. [ABSTRACT FROM AUTHOR]

In this paper, a novel fault‐tolerant control scheme is designed and analyzed for multi‐agent systems (MASs) with incipient faults, disturbances, parameter uncertainties, time delay, and nonlinear terms, and the proposed MAS with switching communication topologies. Firstly, the proposed distributed extended state observer estimates the incipient fault and system states in follower agents, which extends the incipient fault vector to a new system state. Meanwhile, the designed observer considers the output errors of itself and other agents. Further, a state estimation feedback‐based fault‐tolerant controller is constructed, composed of a delay estimator and a non‐delay estimator to guarantee the proposed MASs have good operation performance. Then, some stability analysis conclusions of the MAS with incipient faults, time delay, disturbances, parameter uncertainties, and nonlinear terms are obtained. The proposed results can also be applied to practical systems like the wireless power transfer system. Finally, two simulation results are provided to demonstrate the effectiveness of the proposed fault‐tolerant control technique. [ABSTRACT FROM AUTHOR]

Summary: This work focuses on designing an observer to measure states and actuator faults as well as fault‐tolerant control (FTC) for fuzzy Takagi–Sugeno (T–S) singular systems. An enhanced system is built by creating a new vector from the system state and the actuator faults. The first task is simultaneously to estimate system states and actuator faults with an adaptive observer. Then, in order to get a stabilized faulty singular system, we conceive an observer based on FTC. Using Lyapunov's approach, a linear matrix inequalities (LMIs) feasibility problem is formulated to provide the controller and the observer gains. Compared with previous studies, the proposed method significantly simplifies the design and simultaneously provides the controller and the observer gains in one step. Finally, three examples are given to demonstrate the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

Summary: This article discusses the tracking problem of adaptive fault‐tolerant finite‐time control (AFFC) for a class of strict‐feedback nonlinear systems with unmatched disturbances. Unlike most of the existing results, fault‐tolerant control is combined with finite‐time control, adaptive control and tuning functions. The significant virtue of the combination of these schemes lies in the improvement of the system's reliability, rapidity and robustness. This article uses tuning functions to deal with the problem of the over‐parameterization in the traditional backstepping method. The proposed AFFC scheme ensures that the closed‐loop system is semi‐globally practically finite‐time stable in the presence of sensor/actuator faults, and the tracking error converges to a small neighborhood near the origin in finite time. Finally, the effectiveness of the proposed control strategy is verified by the simulation example. [ABSTRACT FROM AUTHOR]

The problem of adaptive fault-tolerant fixed-time control is studied for a class of strict-feedback nonlinear systems with multiple faults and multiple disturbances. We incorporate the tuning functions and the command filter technique into the controller design. Note that the former reduces the order of the controller, and the latter simplifies the derivation and calculation process and avoids the high calculation cost and differential explosion. In addition, since our proposed strategy is based on fixed-time control, it can ensure that the closed-loop system keeps the practically fixed-time stable, and the tracking error converges to a small neighborhood near the origin within fixed-time. As for the unknown items in the systems, fuzzy logic systems are used to approximate them. The simulation results show that the proposed control strategy is effective even if there exist actuator faults and multiple disturbances. [ABSTRACT FROM AUTHOR]

It is the first report about fault-tolerant-based prescribed performance control of switched nonlinear systems under multiple faults. The concerned faults include not only external faults but also actuator faults. In the process of backstepping control design, prescribed performance control is fully considered, and the combination of unknown nonlinear functions is estimated by multi-dimensional Taylor network. Finally, the developed adaptive fault-tolerant control strategy guarantees the boundedness of all controlled signals while prescribed tracking performance is satisfied. In an effort to further manifest the validity of the fault-tolerant controller, a numerical simulation and a practical simulation are introduced. • This paper is dedicated to balancing prescribed tracking performance and multiple faults. • It is the first time that actuator fault, external fault are discussed in the complicated switching framework. • The adaptive fault-tolerant MTN-based controller is developed to cope with performance constraints. [ABSTRACT FROM AUTHOR]

The research investigates the fixed-time command-filtered composite adaptive neural fault-tolerant (FCCANF) control issue of strict-feedback nonlinear systems (SFNSs). There exist unknown functions and bounded disturbances in the considered systems. Radial basis function neural networks (RBFNNs) will be used in the estimate of the unknown functions. By the serial–parallel estimation models (SPEMs), the forecast biases and the track biases can change the weights of RBFNNs and the approximate characteristics of RBFNNs will be improved. Then, utilizing the novel fixed-time command filter and adaptive disturbance observers, the issue of complex explosion will be effectively solved and the external disturbance is effectively compensated. Subsequently, by utilizing the adaptive control technique, a novel FCCANF controller is developed. Additionally, we have that the system internal variables are bounded and the output variable inclines to a little interval around zero in fixed time which is not determined by the system initial variables. Eventually, numerical and practical examples are shown to prove the availability of the obtained control technique. • For the paper [23], a second-order fixed-time command filter with the symbolic function is introduced to estimate the derivatives of the virtual controllers. However, in this manuscript, a first-order fixed-time command filter with the smooth hyperbolic tangent function is designed to estimate the derivatives of the virtual controllers. Then, the compensation of filtering errors is not considered in the paper [23]. However, in this manuscript, the compensation of filtering errors is considered. • To improve the RBFNN approximation, the novel fixed-time convergence SPEMs are created and it is the first time to use the matrix element technique to solve the fixed-time patchwork problems for the adaptive laws. Then, to estimate the lumped disturbance, the fixed-time convergence adaptive neural disturbance observers are utilized firstly. • Compared with the papers [22] and [24], based on [25], the hyperbolic tangent functions are introduced to solve the singular problem. [ABSTRACT FROM AUTHOR]

This paper gives a fault-tolerant control scheme concerning with the optimal and near-optimal system performance for a class of nonlinear systems with time-varying actuator faults, time-varying disturbances, and identification errors of the neural network-based identifier. In this paper, the adaptive dynamic programming method is directly used to design the optimal sliding surface, so that the designer can design the target dynamics of the sliding mode in advance. In addition, the barrier function-based sliding-mode control is used to cope with the bounded but boundary-unknown estimation errors of the identifier, and the method ensures that the sliding-mode variable converges to the designer's predefined neighborhood of zero in finite time and the control gain is not overestimated. Specifically, first, by adaptive dynamic programming, near-optimal sliding surface is designed in the sense of the quadratic optimal criterion. Second, a neural network identifier is designed to model the lumped uncertainties including actuator faults and disturbances. Third, a barrier function-based adaptive sliding-mode control is used to cope with the identification errors of the neural network identifier and has no control gain overestimation, which can guarantee to confine the sliding variable to a predefined vicinity of the proposed sliding surface. For this system with faults and disturbances, it is shown that near-optimal property is achieved by this scheme, the chattering phenomenon is effectively suppressed, and the reconstruction error of the neural network identifier with unknown boundary is effectively handled by the adaptive sliding-mode control based on the barrier function. The proof of stability is given by Lyapunov's direct method and the effectiveness of this control scheme is verified by applying it to the spacecraft attitude system. [ABSTRACT FROM AUTHOR]

The problem of adaptive finite-time fault-tolerant control with smooth event-triggered mechanism is addressed for quadrotor trajectory tracking systems. In light of recent studies on fault-tolerant control in the field of nonlinear systems, this article focuses on quadrotor trajectory tracking systems with actuator faults and disturbances. Different from the previous works, an ingenious smooth event-triggered mechanism is proposed to circumvent the discontinuous triggered signal and alleviate the communication burden simultaneously, which is of great significance to increase the operation life of the quadrotor. Subsequently, the finite-time performance function is designed to guarantee the prescribed tracking performance. Furthermore, a novel finite-time convergent adaptive fault-tolerant controller is proposed via the time-varying barrier Lyapunov function technique. The radial basis function neural networks are utilized to deal with the nonlinear approximation, and the adaptive laws are developed to accurately estimate the unknown model uncertainty, thus effectively handling the challenge of the controller design caused by the actuator faults and disturbances. Under the developed adaptive fault-tolerant controller, all the closed-loop system signals are bounded and the tracking errors are convergent within finite time. Meanwhile, the Zone behavior can be excluded by the positive sampling intervals. Finally, two examples are employed to verify the effectiveness and advantages of the suggested control scheme. [ABSTRACT FROM AUTHOR]

In this paper, a finite-time, active fault-tolerant control (AFTC) scheme is proposed for a class of autonomous surface vehicles (ASVs) with component faults. The designed AFTC framework is based on an integrated design of fault detection (FD), fault estimation (FE), and controller reconfiguration. First, a nominal controller based on the Barrier Lyapunov function is presented, which guarantees that the tracking error converges to the predefined performance constraints within a settling time. Then, a performance-based monitoring function with low complexity is designed to supervise the tracking behaviors and detect the fault. Different from existing results where the fault is bounded by a known scalar, the FE in this study is implemented by a finite-time estimator without requiring any prioir information of fault. Furthermore, under the proposed finite-time AFTC scheme, both the transient and steady-state performance of the ASV can be guaranteed regardless of the occurrence of faults. Finally, a simulation example on CyberShip II is given to confirm the effectiveness of the proposed AFTC method. [ABSTRACT FROM AUTHOR]

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In electric drive systems, one of the most common faults is related to measurement equipment, including current sensors (CSs). As information about the stator current is crucial to ensure precise control of AC drives, such a fault significantly affects the quality and security of the entire system. For this reason, a modified extended Kalman filter (EKF) has been presented in this paper as an algorithmic solution to restore stator current in the event of CS failure. In order to minimize the impact of rotor and stator resistance variations on the quality of the estimation, the proposed model includes an estimation of the general coefficient of their changes. In contrast to solutions known in the literature, the presented model considers changes in both resistances in the form of a single coefficient. This approach allows us to maintain a low order of the estimator (fifth) and thus minimize the tendency to system instability and decrease computation burden. Extensive simulation tests have shown a significant improvement in the accuracy of stator current estimation under both motor and regenerating modes, a wide speed range (1–100%), and changes in motor parameters. [ABSTRACT FROM AUTHOR]

Due to their advantages in ensuring low harmonic distortion and high power factors, single-phase Pulse-Width Modulated (PWM) rectifiers are widely employed in several industrial applications. Generally, the conventional control loop of a single-phase PWM rectifier uses both voltage and current sensors. Hence, in case of sensor fault, the performance and the availability of the converter can be seriously compromised. Therefore, diagnosis approaches and fault-tolerant control (FTC) strategies are mandatory to monitor these systems. Accordingly, this paper introduces a novel multiple-sensor FTC scheme for a single-phase PWM rectifier. The proposed fault diagnosis approach relies on joining several Generalized Proportional Integral (GPI) and Model Reference Adaptive System (MRAS) observers with a residual generation technique to detect and isolate sensor faults in a simple and reliable manner. While conventional sensor FTC methods dedicated to PWM rectifiers can only deal with single faults, the suggested approach guarantees a very good effectiveness level of sensor fault detection, isolation (FDI) and FTC of multiple-sensor fault occurrence scenarios. Consequently, the single-phase PWM rectifier can work with only the survivable single sensor with the guarantee of very good performance as in healthy operation mode. The effectiveness of the proposed sensor FDI approach and its control reconfiguration performance are demonstrated through both extensive simulation and experimental results. [ABSTRACT FROM AUTHOR]

This work presents an event-triggered mechanism-based distributed fractional-order fault-tolerant control (FTC) paradigm for multiple unmanned aerial vehicles (multi-UAVs) subject to full-state constraints. Distinct from the existing control solutions for multi-UAVs with constant constraints and symmetric constraints, the time-varying asymmetric constraints considered in this paper are more suitable for practical requirements. Neural networks are exploited to cope with uncertainties arising from unknown nonlinear dynamics. By cleverly combining speed functions with nonlinear state-dependent functions, a novel distributed FTC protocol is established to drive the system states into the boundary functions within a predetermined finite time. Simultaneously, fractional-order calculus is introduced to provide additional adjustment of control parameters, and an event-triggered mechanism is derived to reduce the update frequency of the control signal. It is testified that all signals of each follower UAV are semi-globally uniformly ultimately bounded, and all follower UAVs can follow the attitudes of the leader UAV. In the end, case studies are reported to corroborate the outperformance of the proposed methodology. [ABSTRACT FROM AUTHOR]

In this article, the cooperative control for nonlinear multi-agent systems (NMSs) subject to non-affine faults is investigated under directed graphs. A new distributed fixed-time event-triggered control protocol is proposed based on the leader–follower communication architecture, which saves network resources effectively and avoids Zeno behavior. A novel dynamic switching event-triggered mechanism (DSEM) is presented for each follower to ensure the smooth switching of two dynamic threshold strategies, and a dynamic internal trigger variable is designed based on the control input signals and errors, which can dynamically adjust the update frequency of the controller to reduce the number of system triggers. A new DSEM fixed-time distributed controller is designed based on local information to guarantee that all signals of the closed-loop system are fixed-time bounded. It is also proved that the consensus tracking errors of NMSs can converge to an explicitly given bound independent of the initial state in a fixed time. Finally, the validity of the presented control strategy is illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

In this article, the attitude tracking problem for rigid spacecraft subject to external disturbance, inertia uncertainties, and actuator faults is investigated. A novel continuous control strategy is proposed to guarantee that the attitude tracking errors converge with desired performance before an appointed time. In addition, the proposed control law can enable the closed‐loop system to be unwinding‐free. For the purpose, a modified appointed‐time performance function (APF) is used to construct a disturbance observer‐based adaptive attitude control law based on the special orthogonal group (SO(3)). With the aid of the modified APFs, desired performance metrics, including transient and steady‐state performance, on the attitude tracking error can be specified in advance without the requirement for initial values of the tracking system to avoid singularity. By resorting to error transformation and backstepping technique, the control design process is simplified and a few control gains are involved in the proposed control law. Rigorous stability analysis based on the Lyapunov theory is provided to prove the appointed‐time stability of the attitude tracking error as well as the boundedness of all signals in the closed‐loop system despite external disturbance, inertia uncertainties, and actuator faults. Finally, numerical simulations are conducted to support the analysis. [ABSTRACT FROM AUTHOR]