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This article proposes a tracking control strategy based on fixed‐time for uncertain nonlinear systems with prescribed performance and actuator faults. Fuzzy logic systems are used to model unknown functions with uncertainties or fuzzy parameter features. The improvement of the conventional backstepping method through the introduction of command filtering technology has effectively addressed the challenge of a sharp increase in computational complexity during controller design. Additionally, a mechanism for error compensation has been established to mitigate the potential impact of errors that may arise during the filtering process on the system. Then, a new fixed‐time performance function is introduced into the adaptive backstepping method to ensure that the tracking signal with output error converges to an arbitrarily small neighborhood within a fixed time. Additionally, in order to enhance the tracking performance of the control method, the controller algorithm incorporates fault‐tolerant control based on the fixed‐time performance function. Finally, a numerical simulation of a power system with a static reactive power compensation device is presented, and demonstrate the effectiveness and feasibility of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This paper introduces a technique for simultaneous estimation of additive and multiplicative faults in the actuators of nonlinear systems represented by quasi‐linear parameter varying (qLPV) models based on a proportional‐integral unknown input observer. The qLPV model, structured with a tensor product, allows for optimized flexibility of the observer gain. A distinguishing aspect of our method is the novel approach to nonlinearity, which is not only recast as a convex sum but also in the input vector. The study comprehensively analyses the robustness and convergence conditions through Lyapunov stability evaluation. A robust H∞$$ {\mathcal{H}}_{\infty } $$ performance criterion is incorporated to minimize the influence of measurement noise and disturbances. As a result, a set of linear matrix inequalities are obtained. Two examples are examined to demonstrate the practical applicability and efficacy of the proposed method, highlighting the observer's performance under the actuator faults. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive fault-tolerant control method for nonstrict-feedback nonlinear systems with unmodeled dynamics and output dead-zone in the presence of actuator faults. A dynamic signal is used to handle the unmodeled dynamics and a multi-dimensional Taylor network (MTN) to approximate unknown functions. The presented adaptive fault-tolerant control method ensures that all signals in closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB) by applying the Lyapunov stability theory. It also guarantees that the tracking error will eventually converge to a bounded region around the origin. Finally, a numerical example and a real-world application of a one-link manipulator system are used to illustrate the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

This paper emphasises the study of switched nonlinear cyber-physical systems (CPSs) subjected to input delay, actuator faults and deception attacks by a $ H_\infty $ H ∞ -based truncated predictive control design. Particularly, the predictive controller uses delayed state information in addition to the traditional feedback control to estimate the present state for the feedback. Furthermore, the proposed control design is modelled with a truncated predictive approach which is also used to compensate the effects of actuator faults and attacks that also satisfy a predefined $ H_\infty $ H ∞ index simultaneously. With the assistance of the Lyapunov stability theory, a novel set of adequate criteria are acquired in terms of LMIs which assure the asymptotical stability of the switched nonlinear CPS under prescribed predefined $ H_\infty $ H ∞ performance levels. Eventually, the proposed theoretical results are validated through two numerical examples. [ABSTRACT FROM AUTHOR]

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

Spacecraft models that mimic the Planck satellite’s behaviour have produced information on cosmic microwave background radiation, assisting physicists in their understanding of the composition and expansion of the universe. For achieving the intended formation, a framework for a discrete fractional difference spacecraft model is constructed by the use of a discrete nabla operator of variable order containing the Mittag–Leffler kernel. The efficacy of the suggested framework is evaluated employing a numerical simulation of the concerning dynamic systems of motion while taking into account multiple considerations such as exterior disruptions, parameterized variations, time-varying feedback delays, and actuator defects. The implementation of the Banach fixed-point approach provides sufficient requirements for the presence of the solution as well as a distinctive feature for such mechanisms Furthermore, the consistent stability is examined. With the aid of discrete nabla operators, we monitor the qualitative behavioural patterns of spacecraft systems to provide justification for structure’s chaos. We acquire the fixed points of the proposed trajectory. At each fixed point, we calculate the eigenvalue of the spacecraft system’s Jacobian matrix and check for zones of instability. The outcomes exhibit a wide range of multifaceted behaviours resulting from the interaction with various fractional orders in the offered system. To maintain stability and synchronize the system, nonlinear controllers are additionally provided. The study highlights the technique’s vulnerability to fractional-order factors, resulting in exclusive, changing trends and equilibrium frameworks. Because of its diverse and convoluted behaviour, the spacecraft chaotic model is an intriguing and crucial subject for research.

• A modified far-field model (FFM) to simplify the calculation of the electromagnetic force is proposed and common interference forces of the dynamic model of Electromagnetic Formation Spacecraft (EMFS) are analyzed. • A novel proportional passive controller is designed as a nominal controller. For comparison, a saturation proportional-derivative (PD) controller is proposed. The proportional passive controller includes a damping term, which has the potential to avoid energy accumulation. The proposed proportional passive control method demonstrates good robustness and enables faster system stabilization. • Based on the observer determination of AFED, a fixed-time FTC method was developed. Although it can effectively handle unexpected failures of actuators, the design process is relatively complex [26]. The nature of actuator failures and efficiency factor information are determined before controller design, so unexpected actuator faults cannot be effectively handled [27]. Different from the FTC mentioned earlier, this paper proposes an ismc-based FTC scheme that can effectively suppress AFED without requiring a fault observer and the reconstruction of the nominal controller. This scheme combines an adaptive estimation method to estimate AFED in real-time, without requiring any information about the disturbance or actuator faults. Fault-tolerant control (FTC) is an essential consideration for the reason that the proper functioning of electromagnetic formation spacecraft (EMFS) actuators are challenged by the harsh space environment. An Integral-Type Sliding Mode Control (ISMC) scheme is proposed for actuator faults and external disturbances (AFED) caused by coil failure and external complex environment of EMFS system. Before the system state reaches the sliding mode surface, we use super-twisting algorithm to accelerate the reaching of the sliding mode surface and reduce the chattering. After reaching the sliding surface, a novel nominal proportional passive controller is proposed that integrates a damping term, thereby enhance system robustness and expediting system stabilization. Moreover, the FTC method proposed incorporates adaptive techniques to handle unknown AFED in real-time while ensuring system stability. This paper proposes a new adaptive FTC method that enhances the actuator's capability without requiring controller reconfiguration. Simulation results illustrate the effectiveness of this method for suppressing AFED in harsh space environment. [ABSTRACT FROM AUTHOR]

This study addresses the problem of fault accommodation in nonlinear systems described by multiple-models. The considered nonlinear system is an aerial vehicle with four-rotors that is subject to actuator fault. The complexity of the system dynamics poses a significant challenge to its control, especially with the presence of failures. Consequently, a new model is proposed and build, based on Takagi-Sugeno (TS) multiple models. The main objective is to stabilize the vehicle attitude even with the actuator fault. An accommodation strategy is proposed based on TS models. The stability of the suggested model is proved using Lyapunov theory and linear matrix inequalities (LMIs). [ABSTRACT FROM AUTHOR]

This paper explores the fault-tolerant cooperative control of multiagent systems, which are modeled via an uncertain leader system and multiple uncertain Euler–Lagrange systems with actuator faults. A self-adjusting observer is initially proposed to estimate the signal of the uncertain leader for different followers and compute the observer gain in real time. An adaptive fault-tolerant controller is designed based on the above observer and nonsingular fast terminal sliding mode surface. This controller estimates lumped uncertainty and ensures that tracking errors are ultimately bounded. The controller designed in this paper has the following three advantages. Firstly, the observer can estimate and transmit the leader's state to each follower even without precise knowledge of the leader's system matrix. Secondly, the controller is robust to actuator faults, uncertain parameters and external disturbances, the upper bounds of which can be arbitrarily large and unidentified. Thirdly, the controller has a simple structure and is also suitable for situations where the actuator is healthy. Lastly, simulations are provided to demonstrate the effectiveness of both the observer and the controller with or without actuator fault. [ABSTRACT FROM AUTHOR]

In this paper, a distributed observer-based resilient control scheme is proposed to solve the voltage regulation and current sharing problems of islanded direct current (DC) microgrids under actuator faults. First, an observer-based distributed fault estimation design is presented to estimate fault signals with high accuracy. Then, based on the estimated information, a primary decentralized fault-tolerant control layer is designed to ensure accurate voltage reference tracking. A secondary cooperative control layer is employed to achieve the goal of current sharing. Besides, both the fault estimation observers and the fault-tolerant controllers are designed in a plug-and-play fashion, which guarantees the scalability of the DC microgrid. The simulation and experimental results show that the proposed control strategy can efficiently improve the reliability and resilience of the DC microgrid. [ABSTRACT FROM AUTHOR]

A comprehensive RFD-FTC-DCA system is proposed for the hypersonic vehicle with saturation constraints to resist the control surface damage, actuator faults, disturbances and parameter perturbation. Firstly, the hypersonic vehicle fault model is established. Secondly, the robust fault detection (RFD) observer is designed to detect the control surface damage and actuator faults accurately under the influences of disturbances and parameter perturbation. Thirdly, the fault-tolerant control (FTC) law is designed to resist the control surface damage, actuator faults, disturbances and parameter perturbation simultaneously. Finally, a dynamic control allocation (DCA) algorithm is designed to reallocate the FTC law and limit the deflection angle and velocity within saturation constraint. The comparison simulation results are presented to demonstrate that the RFD observer can detect the faults accurately and reduce false alarm rates effectively, the FTC law can resist the control surface damage, actuator faults, disturbances and parameter perturbation simultaneously, and the tracing errors of attack angle, side-slip angle and roll angle are only $ \pm 0.7^\circ $ ± 0.7 ∘ , $ \pm 0.2^\circ $ ± 0.2 ∘ and $ \pm 1.5^\circ $ ± 1.5 ∘ , respectively, and the DCA algorithm can reallocate the FTC law and limit the deflection angle and velocity within saturation values. [ABSTRACT FROM AUTHOR]

The fault-tolerant tracking control problem is studied for the discrete-time systems with actuator faults. To lessen adverse impacts of actuator fault, a PPD information-driven fault estimation algorithm is established to adaptively estimate actuator fault information online, which avoids the additional construction and training process of neural network. With the aid of the adaptive fault compensation, a model-free adaptive fault-tolerant tracking control algorithm is constructed to ensure that the expected output reference trajectory can be tracked by system output. Moreover, only input and output data are employed throughout the design process, system dynamics are not demanded. Ultimately, the availability of developed strategy is proved through a simulation. [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.)

• A fixed-time disturbance observer is proposed under the event-triggered technique to provide an attenuation effect on multi-source disturbances such as exogenous disturbances, system uncertainties, actuator faults, periodic vibrations and uncertain modeled disturbance of actuator, and input saturation. • Propose a fault-tolerant fixed-time controller to track the attitude of spacecraft under multi-source disturbances and limited communication framework. The proposed controller overcomes the unwinding phenomenon, and results show that attitude attitude-tracking path described by quaternion is the shortest maneuvering path. • Stability analysis of a closed-loop system ensures that both disturbance estimation error and the attitude tracking error of the system converge to a final boundary within a fixed time. Moreover, Zeno-free behavior is always guaranteed. This paper studies the attitude tracking problem for rigid spacecraft under restricted communication resources. This work proposes a novel composite control scheme for spacecraft subjected to system uncertainty, exogenous disturbance, periodic vibrations and uncertain modeled disturbance of actuator, actuator faults, and input saturation, which consists of a fixed-time controller (FiTC) based on an integral non-singular fast terminal sliding mode technique and a fixed-time disturbance observer (FiTDO). The FiTDO estimates the total disturbance (combination of the abovementioned effects) within a fixed time. Further, it improves the attenuation disturbance property of the composite controller by feedforward compensation. The proposed controller relaxes the prior upper-bound knowledge of the total disturbance and has anti-unwinding characteristics. Moreover, the designed event-triggered mechanism reduces control workload reduction and guarantees the Zeno-free behavior in the proposed composite scheme. The stability analysis of the closed-loop system under the proposed scheme using Lyapunov theory ensures the system states converge to a small invariant set within a fixed time. Simulation analysis and comparative studies demonstrate that the proposed scheme is effective in terms of convergence time, steady-state performance, and anti-interference ability, rate of controller update. [ABSTRACT FROM AUTHOR]

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]

This paper proposes a monitoring procedure based on characterizing state probability distributions estimated using particle filters. The work highlights what types of information can be obtained during state estimation and how the revealed information helps to solve fault diagnosis tasks. If a failure is present in the system, the output predicted by the model is inconsistent with the actual output, which affects the operation of the estimator. The heterogeneity of the probability distribution of states increases, and a large proportion of the particles lose their information content. The correlation structure of the posterior probability density can also be altered by failures. The proposed method uses various indicators that characterize the heterogeneity and correlation structure of the state distribution, as well as the consistency between model predictions and observed behavior, to identify the effects of failures.The applicability of the utilized measures is demonstrated through a dynamic vehicle model, where actuator and sensor failure scenarios are investigated. [ABSTRACT FROM AUTHOR]

In this study, a vibration suppression control strategy for flexible variable-length strip rolling systems is explored under time-varying actuator failures and output constraints. First, a new partial differential equation and ordinary differential equations of variable-length strip rolling systems are established by considering the variable tension difference, variable speed, and unknown nonlinear rolling force in the rolling process. Then, in order to achieve the displacement constraints of the strip and avoid the initial value requirement of the system, an adaptive barrier Lyapunov function is put forward by introducing a shifting function. Additionally, the effect of the nonlinear rolling force of the system is eliminated by adopting the radial basis function neural network, and the adaptive technique is employed to approximate the unknown parameters. Next, a boundary vibration control law for the variable-length strip rolling system is proposed based on the backstepping approach to maintain the strip vibration displacement in a small neighborhood around zero. Finally, the applicability of the control algorithm is verified using numerical simulations, and the influence rule for the tension difference change in vibration displacement is implemented to confirm the correctness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this article, the attitude tracking problem for rigid spacecraft systems with the consideration of actuator fault, input saturation, inertia uncertainties. and external disturbances is investigated. By introducing a shifting function, the requirement for accurate values of the initial tracking errors has been removed. A novel adaptive prescribed performance function is developed to enable the relaxation and recovery of the performance bounds under the different conditions of the shifted tracking error. Then, an error transformation is employed to convert the problem of prescribed performance tracking into the stabilization problem of a new system. Subsequently, an adaptive controller is designed based on a nonsingular predefined-time sliding mode manifold and an auxiliary system. The proposed controller ensures a predefined-time convergence with prescribed static and transient performance for the tracking error. The stability analysis of the proposed attitude controller is rigorously established using Lyapunov methods. Finally, numerical simulations are conducted to exhibit the efficacy and superiority of the propounded scheme. • Transient and static behavioral bounds are specified for the attitude MRPs. • A shifting function is developed to achieve the initial condition-free purpose. • The system settling time is independent of the initial conditions. • An adaptive term is introduced to traditional performance function. [ABSTRACT FROM AUTHOR]

Time-varying formation tracking problems for multi-agent systems (MASs) under distributed Denial-of-Service (DDoS) attacks and actuator faults are studied. To deal with the hybrid threats at the cyber and physical layers, an estimator-based fault-tolerant hierarchical control scheme is introduced, which is applicable to channel-wise asynchronous communication. Sufficient conditions for formation tracking of maneuvering leader with ultimately bounded error are obtained, and the particular case of periodic communication and attacks with constrained duration and frequency is further analyzed. Comparative physical simulations based on ROS and Gazebo are first conducted to show the resilience of our scheme against the threats. Finally, an experimental platform containing DJI Tello quadrotors and a self-developed ground control station is built, based on which practical experiments with four quadrotors are carried out to evaluate the effectiveness and engineering practicability of the proposed control framework. • A formation tracking controller against DDoS attacks and actuator faults is proposed. • Conditions for achieving formation under hybrid constraints are obtained. • Quadrotor-based experiments validate the practicability of the control strategy. [ABSTRACT FROM AUTHOR]

This paper proposes a new adaptive super-twisting global integral terminal sliding mode control algorithm for the trajectory tracking of autonomous robotic manipulators with uncertain parameters, unknown disturbances, and actuator faults. Firstly, a novel global integral terminal sliding mode surface is designed to ensure that the tracking errors of autonomous robotic manipulators converge to zero in finite time and the global robustness of the system is also enhanced. Then a new adaptive method is devised to deal with the adverse effect of nonlinear uncertainty. To suppress the chattering phenomenon, the adaptive super-twisting algorithm is used in this paper, which can ensure that the control torque is a continuous input signal. Based on the adaptive mechanism, the adaptive super-twisting global integral terminal sliding mode controller is developed to provide superior control performance. The stability analysis of the system is demonstrated by using the Lyapunov method. Ultimately, the effectiveness of the control scheme is confirmed by a simulation study. • A novel adaptive finite-time global integral terminal sliding mode control scheme is designed. • A novel global integral terminal sliding mode surface is proposed to ensure faster convergence and better global robustness. • A novel adaptive law is designed to adjust the estimation parameters according to the change of system state to avoid overestimation. • The actuator fault is considered to make the proposed control logic more suitable for practical applications. [ABSTRACT FROM AUTHOR]

This paper is concerned with the attitude tracking problem of quadrotor unmanned aerial vehicles (UAVs) with respect to endogenous uncertainties, exogenous disturbances and actuator failures. Two different control methods are proposed to solve this problem. First, an adaptive extended state observer (AESO)-based control framework is devised to tackle the difficulties caused by model uncertainties and external disturbances. A fault-tolerant control method is proposed to cope with the occurrence of actuator failure, which is modeled as a constant loss of effectiveness. Another method employs AESOs to compensate for lumped disturbances, which include endogenous uncertainties, exogenous disturbances and actuator failures. Then, the error can exponentially converge to a bounded set. Finally, simulations are performed to ensure the feasibility of the designed technique. [ABSTRACT FROM AUTHOR]

This paper presents a novel nonlinear robust adaptive trajectory tracking control architecture for stabilizing and controlling a quadrotor in the presence of actuator partial faults. The proposed control strategy utilizes an Incremental Nonlinear Dynamic Inversion (INDI) algorithm as the baseline controller in the inner loop and augments a nonlinear model reference adaptive controller in the outer loop to ensure robustness against unmodeled faults. Additionally, a modified PID controller is introduced in the most outer-loop to track the desired path. The effects of actuator faults are modeled by considering sudden variations in motor thrust and torques. To enhance the control algorithm's robustness, a projection operator is employed in the robust adaptive structure. Comparative performance evaluations with a previous successful algorithm implemented on a quadrotor model demonstrate that the proposed controller achieves full controllability of the faulty quadrotor in pitch, roll, and yaw channels in the presence of actuator partial faults up to 50%. [ABSTRACT FROM AUTHOR]

Abstract The fault-tolerant tracking control problem is studied for the discrete-time systems with actuator faults. To lessen adverse impacts of actuator fault, a PPD information-driven fault estimation algorithm is established to adaptively estimate actuator fault information online, which avoids the additional construction and training process of neural network. With the aid of the adaptive fault compensation, a model-free adaptive fault-tolerant tracking control algorithm is constructed to ensure that the expected output reference trajectory can be tracked by system output. Moreover, only input and output data are employed throughout the design process, system dynamics are not demanded. Ultimately, the availability of developed strategy is proved through a simulation.

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

In this paper, an adaptive neural network (NN) fault-tolerant controller is designed for the leader-following consensus control problem of a nonlinear multi-agent systems (MASs) under the complex effect of actuator fault, state time-delay, asymmetric output error constraint and the lumped uncertainty. Firstly, by using an asymmetric barrier Lyapunov function (BLF), output errors are ensured to meet the asymmetric output error constraint requirements. Then, Lyapunov–Krasovskii (L–K) functional and Young's inequality are combined to tackle state time-delay. Radial basis function neural network (RBFNN) is employed to approximate the unknown nonlinear function. Furthermore, adaptive technique is utilized to solve actuator fault. Based on the Lyapunov stability theory, the semi-global bounded stability of closed-loop system is proved. Finally, the validity of the designed control strategy is verified by compared simulation and the application of the two-stage chemical reactors. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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.)

It is of great importance to simultaneously stabilize output power and suppress platform motion and fatigue loads in floating offshore wind turbine control systems. In this paper, a novel composite blade pitch control scheme considering actuator fault is proposed based on an augmented linear quadratic regulator (LQR), a fuzzy proportional integral (PI) and an adaptive second-order sliding-mode observer. Collective pitch control was achieved via the fuzzy PI, while individual pitch control was based on the augmented LQR. In the case of actuator fault, an adaptive second-order sliding-mode observer was constructed to effectively eliminate the need for the upper bound of unknown fault derivatives and suppress the chattering effect. This paper conducted co-simulations based on FAST (Fatigue, Aerodynamics, Structures, and Turbulence) and MATLAB/Simulink to verify the effectiveness and superiority of the proposed scheme under different environmental conditions. It is shown that platform roll was reduced by approximately 54% compared to that under PI control. For the tower fore–aft moment, load reductions of 45% or more were achievable. The proposed scheme can greatly reduce the pitch and roll of the floating platform and loads in the windward direction of the wind turbine. [ABSTRACT FROM AUTHOR]

In this paper, we explore the consensus of positive networked systems with actuator faults. Firstly, the undirected and strongly connected topology is established with graph theory. The positive system theory is used to analyze the positive consensus of the closed-loop networked systems. State feedback gains are derived utilizing Algebraic Riccati Inequalities. Bounded multiplicative faults are regarded as uncertainties in the system matrix, while treating additive faults as external disturbances. Further, this transformation refocuses the analysis on the consensus problem with an L 2 -gain. Subsequently, the Genetic Algorithm is employed to optimize the L 2 performance criteria. Finally, the effectiveness of the proposed theory is validated through simulations involving both single-input electric circuit systems and multi-input networked systems. [ABSTRACT FROM AUTHOR]

The decentralized control is provided for the multi‐agent unmanned aerial vehicle system and is designed based on leader‐follower configuration by graph theory. Next, primary model predictive control (MPC) is proposed in order to steer the error signal to the origin and specifically, an optimization algorithm is considered for the primary MPC controller in which the Newton optimization with back‐stepping step size definition is proposed for this manner. A robust modification is investigated for the system based on tube definition and considered to overcome the high‐frequency noise and external disturbances in a bound of 20% of the system output. The high‐frequency noises are designed outside of the primary controller band‐width. The hybrid controller is proposed for the system. The closed‐loop swarm system's control architecture, switches between the primary MPC controller to tube‐MPC controller in the presence of high‐frequency noises and external disturbances. The hybrid controller provides a more energy‐efficient outcome compared to the single mode controller. The final results provides a 7% faster simulation time. Afterward, the flexible formation theory is generalized for system. The possibility of changing leader is investigated in flexible formation and a scenario of switching leader is proposed for the system. The result of tracking for the controller is compared to proportional‐integral‐derivative and the problem of four agents in a flight scenario illustrates the issues and the comparison between the H∞$$ {H}_{\infty } $$ robust controller and the switching Tube‐MPC controller is provided. The results provide that the novel control architecture has a 47.6% lower rise time and 30.8% lower overshoot. [ABSTRACT FROM AUTHOR]

An adaptive sliding mode fault‐tolerant control strategy is proposed for a quadrotor unmanned aerial vehicle in this article to accommodate actuator faults and model uncertainties. First, a new reaching law is proposed, with which a sliding mode control (SMC) law is constructed. The proposed reaching law is made up of a sliding variable and the distance between it and a designated boundary layer, and it can effectively suppress the unexpected control chattering while preserving the necessary system tracking performance. Then, an adaptive SMC scheme is proposed to further solve the fault and uncertainty compensation problem. The proposed adaptation law helps to prevent overestimation of the adaptive control parameters, as well as avoiding control chattering. Finally, a number of comparative simulation tests are carried out to validate the effectiveness and superiority of the proposed control strategy. The demonstrated quantitative comparison results confirm its advantages. [ABSTRACT FROM AUTHOR]

This paper presents a fault-tolerant human-machine shared scheme for collision avoidance considering driver error and actuator fault. A fault-tolerant method of trajectory planning and decision-making is developed for dealing with the actuator fault. We calculate the remainder trajectory tracking capability of the faulted actuator and utilise the motion redundancy in the system to generate feasible fault-tolerant trajectories for collision avoidance. In addition, an assessment criterion of driver error is conducted to supervise the driver's steering response to the potential collision and actuator fault. The shared system dynamically adjusts the driving authority based on the driver error. A model predictive control (MPC) algorithm is employed for tracking the fault-tolerant trajectory. Simulation and hardware-in-the-loop (HIL) experiment results demonstrate the effectiveness of the presented approach, reducing traffic accidents due to driver error and actuator fault. [ABSTRACT FROM AUTHOR]

This study investigates the problem of robust fault diagnosis for nonlinear systems subjected to actuator faults and unknown input disturbances. A novel adaptive fast smooth super-twisting observer based on the super-twisting and adaptive dual-layer algorithms is presented, and a robust fault-diagnosis scheme based on an adaptive threshold is proposed to take the estimation error generated by the observer as the residual. In the adaptive fast smooth super-twisting observer, additional fractional powers less than 1 and linear terms are added to improve the smoothness and rapidity of the observer. The finite-time stability of the adaptive fast smooth super-twisting observer is then analyzed based on the Moreno–Lyapunov function algorithm, and rigorous proof confirms that the estimation-error dynamic is robust to unknown input disturbances and can converge to a region of zero in finite time. Finally, simulations of the rigid spacecraft attitude kinematics and dynamics are used to validate the effectiveness of the developed adaptive fast smooth super-twisting observer and the designed robust fault-diagnosis scheme. [ABSTRACT FROM AUTHOR]

In this article, for a class of stochastic pure-feedback nonlinear systems with simultaneous actuator and sensor faults, the problem of adaptive fault-tolerant control is examined. The stochastic pure-feedback nonlinear system is first converted into a strict-feedback by applying the mean value theorem and radial basis function neural networks are used to approximate the unknown functions. Only one adaptive parameter needs to be calculated online rather than the actual weight vector elements by determining the greatest value of the norm of the neural network weight vector. With the help of regrouping and parameter separation methods, the unavailability of state variables caused by sensor faults is addressed. The Lyapunov function methods and the backstepping recursive design technique are used to design an adaptive fault-tolerant controller. It is shown that by choosing proper the design parameters, the tracking errors converge to a small region of the origin, and all the signals in the closed-loop system are bounded in probability. The performance of the proposed controller is illustrated using a numerical example and a real-world example of a rigid robot manipulator system. [ABSTRACT FROM AUTHOR]

This paper investigates the event-based adaptive fixed-time (FT) control problem for active suspension systems (ASSs) with actuator faults. The fuzzy approximator is utilized to estimate the continuous function with the unknown car body mass parameters. The FT controller with continuous piecewise function is presented to avoid the singularity problem caused by the derivation of the virtual controller in the backstepping method and to compensate the actuator faults. A switching threshold event-triggered mechanism is evolved for ASSs, which has the advantages of fixed threshold strategy and relative threshold strategy to reduce the communication burden more reasonably. The suspension vertical displacement is restricted by constructing a time-varying barrier Lyapunov function. It is proved that the signals in the closed-loop systems are bounded by Lyapunov stability criterion. Finally, simulation results show that the controller is effective in suppressing the vertical vibration of ASSs. [ABSTRACT FROM AUTHOR]

To improve the anti-disturbance and reliability performance for unmanned surface vehicles subject to actuator faults and external disturbances, an adaptive event-triggered observer-based output feedback control method is proposed. Firstly, a Takagi-Sugeno fuzzy system is established by considering unknown disturbances and actuator faults. Secondly, an adaptive event-triggered mechanism is designed and then the state and disturbance observers are constructed using the output of the event generator. Based on the outputs of the observers, an adaptive event-triggered observer-based output feedback dynamic positioning controller is developed and the asymptotical stability with H ∞ performance is analyzed via the Lyapunov function method. Finally, the advantages of the proposed method are demonstrated via an example. [ABSTRACT FROM AUTHOR]

Over the past few decades, there have been increasing research activities in fault diagnosis (FD) and fault-tolerant control (FTC) for switched hybrid systems. This paper addresses the problem of active-fault tolerant control (AFTC) for switched hybrid systems subject to actuator faults to enhance system security and keep system stability. The proposed FTC is designed by adding the state feedback control with integral action to an additive control law which requires accurate fault estimation to compensate for the fault effect. Thus, a data-based projection method (DPM) is extended (EDPM) based on inputs and outputs measures to estimate the fault without using mathematical models. The synthesis of the state feedback control with integral action is proposed for recovering the desired performances. It integrates a set of controllers corresponding to a set of partial models to design a set of switching control laws. Indeed, new linear matrix inequalities (LMIs) using Lyapunov stability analysis are proposed to find the optimal values of the control gains matrices and keeping system stability. A comparative study of the proposed FTC with existing work is given to show the effectiveness of the proposed technique. [ABSTRACT FROM AUTHOR]

This paper investigates the distance-based formation and cooperative path-following control problems for multiple fixed-wing unmanned aerial vehicles (UAVs). In this study, we design the distance-based formation control structure to achieve the virtual leader and followers pre-defined rigid formation pattern, ensuring simultaneously relative localization. A path-following control strategy based on adaptive dynamic surface and neural network control technology is proposed to approximate the uncertain disturbances of the environment and unmodeled dynamics. And the longitudinal and lateral subsystems' adaptive fault-tolerant controllers are designed, respectively, to achieve the fault-tolerant control of UAVs' formation in three-dimensional environments. Furthermore, the adaptive sliding mode controller with an auxiliary controller is designed to realize the UAVs path following with limited input saturation. Finally, simulation examples are given to clarify and verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]