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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 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]

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]

• 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]

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 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]

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.

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]

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]

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]

In this paper, the fault-tolerant time-varying formation tracking control problem for high-order linear multi-agent systems with multiple leaders is studied in the case of actuator faults and switching topologies, where the control inputs of the leaders are unknown. Followers form a predefined formation while tracking the convex combination of the states of the multiple leaders. Based on the adjacent relative information of agents, a fault-tolerant time-varying formation control protocol is constructed to compensate for the bias fault, loss of effectiveness fault, and unknown control inputs of the leaders. The feasible conditions of formation are given. In addition, a new algorithm is proposed to determine the parameters of the formation control protocol. The stability of the closed-loop system is proved based on Lyapunov theory. Finally, the effectiveness of the theory is verified by simulations.

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.

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.

For the Conical Tow-Tank Non-Interacting Level (CTTNL) prototype system, this article discusses the design of an unique optimal fractional order TID controller employing a type-1 fuzzy set. To generate a linearized model transfer function for the nonlinear CTTNL process, local linearization around the equilibrium state was performed. This work compares the performance of a fuzzy tilted-integral-derivative (FTID) controller for the CTTNL system to a traditional proportional–integral–derivative (PID) controller. The parameters of the FTID controller were optimized using the Chicken Search Optimization (CSO) algorithm in this study, and those values were used to create a PID controller. Thereafter, the FTID and PID controllers’ performance is compared. The investigation shows that the FTID controller beats the PID controller in terms of IAE, ISE, ITAE, and ITSE integral errors. The suggested controller’s fault-tolerant performance was also assessed using the fault recovery time (Frt) parameter. The FTID controller outperforms traditional PID controllers in terms of transient and steady-state performance. The fault tolerance capabilities of the FTID controller will be tested on the CTTNL system in the future, using additive and multiplicative failures. Further research will include a comprehensive examination of robustness in the context of model parameter uncertainties.

This paper is concerned with the trajectory tracking control of unmanned surface vehicles (USVs) subject to input quantization, actuator faults and dead zones. In scenarios with dense marine facilities, there are constraints on the tracking performance and convergence time of USVs. First, the designed control signal is quantized by a hysteresis quantizer to reduce the transmission rate. Second, to guarantee the transient and steady-state tracking performance of the USV, a prescribed performance control technology with a predefined settling time is employed. Third, a predefined-time adaptive sliding mode control (SMC) method is designed by integrating the auxiliary function and the barrier function. Moreover, the lumped uncertainties caused by quantization, actuator faults, and dead zones are simultaneously processed using control gain based on barrier function. The proposed control method guarantees that the tracking error and sliding variable converge to the corresponding predefined bounds within a predefined time. The predefined bounds are independent of the upper bound on the lumped uncertainty. The stability of the controlled system is proven via the Lyapunov theorem. Finally, the effectiveness of the designed controller is verified by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper proposes a new method of detection and reconstruction of the incipient fault of fixed-wing actuators based on an adaptive sliding-mode observer. First, a mathematical model of a fixed-wing aircraft is derived under certain assumptions, considering nonlinear terms and system disturbances. Second, by introducing a nonsingular coordinate transformation, the incipient faults are separated from the disturbances. For a subsystem with no disturbances, the Luenberger observer can estimate the incipient fault. For a subsystem with disturbances, the sliding-mode observer is robust against these disturbances. The Lyapunov stability theory guarantees dynamic error convergence and system stability. The evaluation function was designed to realize residual evaluation and threshold judgment. Third, based on the concept of equivalent output injection, an adaptive sliding-mode observer method is proposed to reconstruct actuator faults precisely under the condition of the uncertain system structure. The design steps of the proposed reconstruction method are introduced in the form of a linear matrix inequality problem, which provides an effective method for calculating the design parameters. Finally, the simulation results of the De Havilland DHC-2 "Beaver" aircraft demonstrate the correctness and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the actuator fault detection and tolerant control problem for vehicle platoons with partial loss of effectiveness and bias faults. Considering the inherent coupling between the control input and the nonlinear term in the actuator, a decoupled observer based fault detection algorithm with time-varying threshold is developed to decide whether the actuator fault occurs in the platoon. Then, by employing radial basis function neural networks (RBF NNs) and backstepping control method, an adaptive robust fault-tolerant control (FTC) scheme is proposed, which is proved to be capable of achieving the safety, stability and tracking performance of vehicle platoons in the presence of actuator fault. Simulation studies illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

A new optimum interval type-2 fuzzy fractional-order controller for a class of nonlinear systems with incipient actuator and system component faults is introduced in this study. The faults of the actuator and system component (leak) are taken into account using an additive model. The Interval Type-2 Fuzzy Sets (IT2FS) is used to design an optimal fuzzy fractional order controller, and two different nature inspired metaheuristic algorithms, Follower Pollination Algorithm (FPA) and Genetic Algorithm (GA), are used to optimize the parameters of the fuzzy PID controller and Interval Type-2 Fuzzy Tilt-Integral-Derivative Controller (IT2FTID) for nonlinear system. The suggested control approach consists of two parts: an Interval Type-2 Fuzzy Logic Controller (IT2FLC) controller and a fractional order TID controller. Additionally, the two inputs of the IT2FLC are also calibrated using two fine tuning parameters [Formula: see text] and [Formula: see text], respectively. The stability of the proposed controller is presented with some conditions. In addition to unknown dynamics, some unknown process disturbances, such as rapid changes in the control variable, are taken into account to check the efficacy of the proposed control scheme. Two nonlinear conical two-tank level systems are used in the simulation as a case study. The performance of the suggested approach is also compared to that of a widely recognized Interval Type-2 Fuzzy Proportional-Integral-Derivative (IT2FPID) Controller. Finally, the proposed control scheme's fault-tolerant behaviour is demonstrated using fault-recovery time results and statistical Z-tests for both controllers, and the proposed IT2FTID controller's effectiveness is demonstrated when compared to IT2FPID and existing passive fault tolerant controllers in recent literature.

This paper proposes a novel methodology for trajectory tracking of unknown discrete-time nonlinear systems under sensor and actuator faults. The proposed approach combines a recurrent neural identifier trained online with well-known characteristics of sliding mode technique. This paper includes a stability analysis based on Lyapunov theory. Finally applicability of the proposed scheme is shown through simulation results for a three-phase induction motor whose mathematical model is considered unknown. Furthermore, the system is operated in the presence of unknown disturbances as well as sensor and actuator faults.

Unmanned aerial vehicles (UAVs) are subject to the wind and other environmental disturbances that can destabilize them. The high performance and robustness of the Linear Quadratic Regulator (LQR) controllers ensure the ability to reduce the deviations in state trajectories with minimum control effort. In this paper, the weighting matrices are adjusted automatically via a novel method implemented through state variables matrix of the quadrotor together with a preference factor. This proposed factor is determined by the designer via penalizing or rewarding a certain state of the quadrotor out of others so that the model insufficiencies against disturbances are compensated. The effectiveness of the proposed method of selecting these matrices is evaluated for the cases of LQR and LQR with a PI controller. They were evaluated with respect to the convergence of state variables to their reference values within a specific time and compliance with their desired performance characteristics. The experimental results revealed that both control strategies could stabilize the quadrotor in the desired position and attitude with better performance and robustness characteristics. The results also showed that the LQR-PI control method is a more reliable and effective approach in achieving higher tracking performances compared to the LQR only.

In this article, the design and experimental evaluation of a fault-tolerant controller are introduced for a double-rod electro-hydraulic actuator subjected to actuator faults and disturbances. The internal leakage fault is captured as a bias fault, whilst the faults in servo-valve and supply failure are considered as a partial loss of effectiveness (LOE) fault. The design obstacles caused by the disturbances and bias fault are suppressed by nonlinear disturbance observers (NDO) while an asymmetric barrier Lyapunov function is used to ensure the non-violated boundary of the output position. To tackle the LOE fault, the development of an enhanced adaptive compensation technique for actuator fault-tolerant control (FTC) is then constructed. Moreover, to mitigate the "explosion of complexity" in the traditional backstepping design, the command-filtered control is utilized to elaborate the FTC scheme. It is shown by theoretical analysis that system stability is ensured under faulty conditions. Finally, simulation/experiment results and comparison studies are performed to further verify the effectiveness of the proposed approach. • The lumped disturbances, bias fault and a partial LOE faults is firstly considered for EHA. • The NDOs and an enhanced adaptive law is developed to tackle bias fault and LOE fault. • The proposed FTC method based on CFC approach and BLF is performed. • The stability of the closed-loop system is ensured based on the Lyapunov theory. • Comparative experimental results confirm the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper presents a fault-tolerant attitude control scheme, incorporating reconfiguration control allocation for supersonic tailless aircraft subject to nonlinear characteristics, actuator constraint, uncertainty, and actuator faults. The main idea is to propose an incremental reconfiguration closed-loop control allocation scheme, coupled with a basic backstepping attitude controller, to achieve attitude control. Based on the virtual control input generated by the basic backstepping attitude controller, firstly, the incremental nonlinear control allocation method is adopted to deal with the nonlinear characteristics and actuator constraint. Secondly, a distribution error feedback loop is constructed in the incremental nonlinear control allocation method to enhance the robustness against the uncertainty of the control effectiveness matrix. Thirdly, the control effectiveness matrix is reconstructed by different kinds of fault information to deal with actuator faults, and the proper combination of actuator deflections is generated to achieve accurate command tracking. The stability of the proposed scheme is guaranteed by the Jury stability criterion and the Lyapunov stability analysis. Finally, in comparison with the three existing approaches, the simulation results of two cases are provided to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Hybrid aircraft configurations with combined cruise and vertical flight capabilities are increasingly being considered for unmanned aircraft and urban air mobility missions. To ensure the safety and autonomy of such missions, control challenges including fault tolerance and windy conditions must be addressed. This paper presents an observer-based optimal control approach for the active combined fault and wind disturbance rejection, with application to a quadplane unmanned aerial vehicle. The quadplane model is linearised for the longitudinal plane, vertical takeoff and landing and transition modes. Wind gusts are modelled using a Dryden turbulence model. An unknown input observer is first developed for the estimation of wind disturbance by defining an auxiliary variable that emulates body referenced accelerations. The approach is then extended to simultaneous rejection of intermittent elevator faults and wind disturbance velocities. Estimation error is mathematically proven to converge to zero, assuming a piecewise constant disturbance. A numerical simulation analysis demonstrates that for a typical quadplane flight profile at 100 m altitude, the observer-based wind gust and fault correction significantly enhances trajectory tracking accuracy compared to a linear quadratic regulator and to a H-infinity controller, which are both taken, without loss of generality, as benchmark controllers to be enhanced. This is done by adding wind and fault compensation terms to the controller with admissible control effort. The proposed observer is also shown to enhance accuracy and observer-based rejection of disturbances and faults compared to three alternative observers, based on output error integration, acceleration feedback and a sliding mode observer, respectively. The proposed approach is particularly efficient for the active rejection of actuator faults under windy conditions. [ABSTRACT FROM AUTHOR]

In this paper, the problem of actuator and sensor faults of a quadrotor unmanned aerial vehicle (QUAV) system is studied. In the system fault model, time delay, nonlinear term, and disturbances of QUAV during the flight are considered. A fault estimation algorithm based on an intermediate observer is proposed. To deal with a single actuator fault, an intermediate variable is introduced, and the intermediate observer is designed for the system to estimate fault. For simultaneous actuator and sensor faults, the system is first augmented, and then two intermediate variables are introduced, and an intermediate observer is designed for the augmented system to estimate the system state, faults, and disturbances. The Lyapunov–Krasovskii functional is used to prove that the estimation error system is uniformly eventually bounded. The simulation results verify the feasibility and effectiveness of the proposed fault estimation method. [ABSTRACT FROM AUTHOR]

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.

A new optimum interval type-2 fuzzy fractional-order controller for a class of nonlinear systems with incipient actuator and system component faults is introduced in this study. The faults of the actuator and system component (leak) are taken into account using an additive model. The Interval Type-2 Fuzzy Sets (IT2FS) is used to design an optimal fuzzy fractional order controller, and two different nature inspired metaheuristic algorithms, Follower Pollination Algorithm (FPA) and Genetic Algorithm (GA), are used to optimize the parameters of the fuzzy PID controller and Interval Type-2 Fuzzy Tilt-Integral-Derivative Controller (IT2FTID) for nonlinear system. The suggested control approach consists of two parts: an Interval Type-2 Fuzzy Logic Controller (IT2FLC) controller and a fractional order TID controller. Additionally, the two inputs of the IT2FLC are also calibrated using two fine tuning parameters β1 and β2, respectively. The stability of the proposed controller is presented with some conditions. In addition to unknown dynamics, some unknown process disturbances, such as rapid changes in the control variable, are taken into account to check the efficacy of the proposed control scheme. Two nonlinear conical two-tank level systems are used in the simulation as a case study. The performance of the suggested approach is also compared to that of a widely recognized Interval Type-2 Fuzzy Proportional-Integral- Derivative (IT2FPID) Controller. Finally, the proposed control scheme’s fault-tolerant behaviour is demonstrated using fault-recovery time results and statistical Z-tests for both controllers, and the proposed IT2FTID controller’s effectiveness is demonstrated when compared to IT2FPID and existing passive fault tolerant controllers in recent literature. [ABSTRACT FROM AUTHOR]

In this paper, aiming at the actuator fault-tolerant trajectory tracking problem of two-wheeled differential-driven mobile robots, a super-twisting fractional-order sliding mode fault-tolerant control method combined with a fault observer is proposed. The method not only ensures the pose tracking of the robot in normal condition but also guarantees the tracking performance while the fault occurs. The proposed method mainly includes: A fractional-order sliding mode surface which improves the transient response is utilized to design the fault-tolerant controller, and the super twisting reaching algorithm is adopted to reduce the chattering; A fault observer is designed to estimate the fault value, ensures system stability and safety through real-time compensation. Finally, the proposed fault-tolerant control method is verified by numerical simulation. The results show that the method proposed in this paper can effectively reduce the impact of actuator fault and ensure trajectory tracking performance. And the advantage of the control strategy over the general sliding mode controller is that compared with the integer-order sliding mode control (IOSMC), the fractional-order sliding mode control (FOSMC) we designed in this paper converges all the error states to zero faster, and the tracking error chattering is smaller. [ABSTRACT FROM AUTHOR]

Focusing on the actuator fault of the quadrotor unmanned aerial vehicle (QUAV), an active fault-tolerant control scheme based on fixed-time linear active disturbance rejection control is proposed. Firstly, in order to simplify the complex dynamic model, the virtual control quantity is introduced to decouple the flight control system of the QUAV. Secondly, the fixed-time extended state observer (ESO) is utilized to estimate and compensate the internal uncertainty, external disturbance and actuator fault of the QUAV in fixed time. Thirdly, a continuous output feedback controller based on fixed-time ESO is designed to keep the stability of the flight control system with actuator fault and external disturbance. Finally, the closed-loop stability of the flight control system is demonstrated by Lyapunov function. The numerical simulation is carried and the results also verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, the problem of adaptive neural fault-tolerant control (FTC) for the fractional-order nonlinear systems (FNSs) with positive odd rational powers (PORPs) is considered. By using the radial basis function neural networks (RBF NNs), the unknown nonlinear functions from the controlled system can be approximated. With the help of an adaptive control ideology, the unknown control rate of the actuator fault can be handled. In particular, the FNSs subject to high-order terms are studied for the first time. In addition, the designed controller can ensure the boundedness of all the signals of the closed-loop control system, and the tracking error can tend to a small neighborhood of zero in the end. Finally, the illustrative examples are shown to validate the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

A guaranteed fault-estimation algorithm based on interval set inversion observer filtering is proposed for linear discrete-time systems with unknown but bounded disturbance and noise. The minimal conservative interval observer is designed by minimizing the F-norm of the state error. Vector Boolean operations and dimensional operations are used to develop a new interval set inversion algorithm to further contract the guaranteed interval estimation results of the observer. The computational complexity, memory requirements, and accuracy of the proposed algorithm are also analyzed. Finally, simulation examples are provided to verify the efficiency and practicability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The control strategy for Internet of Connected Vehicles (IOCV) with unidentified actuator faults and saturation is examined in this study. The IOCV system is represented by a third-order nonlinear model that takes into account the unknown nonlinear dynamics with time-varying faults and saturation. A fuzzy adaptive sliding mode (FASM) controller with a nonlinear disturbance observer has been developed based on the new model, and it can concurrently achieve the control goals of string stability and individual vehicle stability with zero initial spacing error. In addition, a novel modified constant time headway (MCTH) is proposed to address string instability caused by nonzero starting conditions. In order to confirm the superiority, numerical simulation and experiment are tested on Matlab and the IOCV made of four Ackermann cars. [ABSTRACT FROM AUTHOR]

The stability and drivability of distributed drive electric vehicles over split-friction regions and with actuator faults are studied in this paper by using control allocation. Under the integrated control architecture of high-, medium-, and low-level controllers, a slip-ratio-based synchronization approach is presented to redistribute the driving force for all the driving wheels. The synchronization of slip ratios on wheels is accomplished by autonomously regulating the distribution parameters in the design of a low-level controller. Therefore, the driving force and moment can be adjusted from the design of the regulator on distribution parameters so that the stability and driving performance are ensured when electric vehicles drive over split-friction regions. Subsequently, the concept of distribution parameters is extended to handle actuator faults in electric vehicles by regulating the driving force via the adjustment of distribution parameters. The proportional fault, additive fault, and motor saturation are considered in this paper by compensating for the loss of driving force from the force allocation approach. Numerical examples using CarSim with MATLAB/Simulink and human/hardware-in-the-loop validations are illustrated to demonstrate the efficacy and performance of the proposed control schemes. • A slip-ratio-based force allocation control is presented for DDEVs over split-friction regions. • Auto-regulation of distribution parameters ensures stability of DDEVs with actuation faults. • Integrated controller with force allocation and fault-tolerant control are validated using HIL. [ABSTRACT FROM AUTHOR]

An iterative learning fault-tolerant control method is designed for an actuator fault intermittent process with simultaneous uncertainties for the system parameters. First, an intermittent fault tolerance controller is designed using 2D system theory, and the iterative learning control (ILC) intermittent process is transformed into a 2D Roesser model. Secondly, sufficient conditions for the controller's existence are analyzed using the linear matrix inequality (LMI) technique, and the control gain matrices are obtained by convex optimization with LMI constraints. Under these conditions for all additive uncertainties for the system parameters and admissible failures, the controller can ensure closed-loop fault-tolerant performance in both the time and batch directions, and it can also meet the H∞ robust performance level against outside disturbances. Eventually, the algorithm's computational complexity is analyzed, and the effectiveness of the algorithm is verified by simulation with respect to an injection molding machine model. Compared with traditional ILC laws, which do not consider actuator faults, the proposed algorithm has a better convergence speed and stability when the time-invariant and time-variant actuator faults occur during implementation. [ABSTRACT FROM AUTHOR]

As an important equipment for deep well hoisting, the safe and stable operation of the Blair mine hoist is vital for the development and utilization of deep mineral resources. However, it is always a challenging task to keep consistent wire rope tension in the event of an actuator fault. In this study, an adaptive dynamic surface technology-based actuator fault-tolerant scheme is proposed. A fault observer with a neural network adaptation term is designed to estimate the loss of actuator efficiency caused by faults. Considering the redundant characteristic of the two actuators, a novel dynamic surface technology-based controller with a fuzzy assignment and state constraints is developed to eliminate the impact of fault. The stability of the closed-loop system under the proposed strategy is theoretically proved by rigorous Lyapunov analysis. Comparative experiments under various conditions are carried out on a xPC based mine hoist platform, and the results show the applicability together with the superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

In order to improve the safety and reliability of the hypersonic flight vehicle, a sliding mode observer-based fault detection scheme is applied in this paper to handle the actuator fault detection issue, including stuck fault detection and PLOE fault detection. A dynamic linear model with uncertainty is first derived from the original nonlinear hypersonic flight vehicle model by using Taylor's linearization approach at the equilibrium point. Secondly, the actuator fault model, reflecting stuck faults and PLOE faults, is constructed. Then, a sliding mode-based fault detection observer, considering system decomposition, is developed based on the linearized hypersonic flight vehicle model. At last, the designed sliding mode observer is applied to the original nonlinear hypersonic flight vehicle for single-input, single-style actuator fault detection. The simulation results show that stuck faults and big proportion PLOE faults can be timely and accurately detected at the fault time, and the stuck actuator fault from input 3 can cause a deadly impact to the hypersonic flight vehicle, which deserves much more attention than the actuator faults from the other three inputs. Meanwhile, the detection of a small proportion of PLOE faults encounters some difficulties and needs special attention and further investigation. [ABSTRACT FROM AUTHOR]

This study aims to design a generalized fault diagnosis observer (GFDO) and an active fault tolerant control system (AFTCS) for external disturbances based on an aircraft control system and actuator faults. Unlike the traditional approach that assumes external disturbances are norm bounded, the Gronwall Lemma based on the external disturbances constraint condition is modelled to satisfy the system stability. Then, the GFDO is designed by two performance indices defined to simultaneously estimate system states and faults. In addition, the AFTCS is designed to obtain the desired performances in the fault case. When the fault is diagnosed by GFDO, the regular controller switches to AFTCS. Finally, an analysis of the performance of the proposed algorithm is discussed based on simulations of the F-18 aircraft control system, which illustrates the effectiveness and applicability of this method.

In this paper, an appointed-time prescribed performance fault-tolerant control (ATPPFTC) method for quadrotor unmanned aerial vehicle (QUAV) system is studied in the presence of model parameters uncertainties, actuator faults and external disturbances. For the position loop and the attitude loop, the proposed method overcomes the model parameters uncertainties caused by the changes of rotary inertia, the mass and aerodynamic damping coefficients. Meanwhile, unknown actuator faults and unknown external disturbances are investigated by using adaptive method. Moreover, a new appointed-time prescribed performance function and coordinate transformation are introduced to impose performance characteristics on the tracking errors. Based on the Lyapunov stability theory, an adaptive dynamic surface control method is proposed to ensure that the position and attitude tracking errors of the closed-loop system can achieve the appointed-time convergence and prescribed transient and steady-state performance. Incidentally, the convergence speed and convergence time of the system tracking error can be set flexibly. Finally, the simulation verifies the effectiveness and superiority of the proposed control scheme from both qualitative and quantitative aspects.

In this paper, aiming at the actuator fault-tolerant trajectory tracking problem of two-wheeled differential-driven mobile robots, a super-twisting fractional-order sliding mode fault-tolerant control method combined with a fault observer is proposed. The method not only ensures the pose tracking of the robot in normal condition but also guarantees the tracking performance while the fault occurs. The proposed method mainly includes: A fractional-order sliding mode surface which improves the transient response is utilized to design the fault-tolerant controller, and the super twisting reaching algorithm is adopted to reduce the chattering; A fault observer is designed to estimate the fault value, ensures system stability and safety through real-time compensation. Finally, the proposed fault-tolerant control method is verified by numerical simulation. The results show that the method proposed in this paper can effectively reduce the impact of actuator fault and ensure trajectory tracking performance. And the advantage of the control strategy over the general sliding mode controller is that compared with the integer-order sliding mode control (IOSMC), the fractional-order sliding mode control (FOSMC) we designed in this paper converges all the error states to zero faster, and the tracking error chattering is smaller.

This article investigates a problem of event-triggered controller design for DC microgrid, in which multiple nonlinear Constant power loads (CPLs) and probabilistic actuator fault are considered. A novel pre-averaged event-triggered mechanism (PAETM) is put forward, under which the average value of each time interval is used to determine the triggering instead of using the sample data that represents the system characteristic partially. Benefit from this mechanism, triggering events are reduced and the network burden is mitigated while the system performance is ensured, which contributes to a higher efficiency for DC microgrid. Considering various disturbances in DC microgrid, a unified PAETM controller design for DC microgrid with probabilistic distribution actuator fault and disturbance is proposed. Finally, a simulation example is shown to illustrate the validity of the proposed control strategy.

For nonlinear multi-phase batch processes with time-varying reference trajectories, actuator faults and nonlinear characteristics, a robust asynchronous fuzzy predictive fault-tolerant tracking control method is proposed. First, considering an asynchronous switching situation between a state and a controller when switching occurs, an extended Takagi-Sugeno fuzzy switching model, including the matched and mismatched cases, is established. Then, a robust asynchronous fuzzy predictive fault-tolerant tracking controller is constructed based on the switching model by taking into account whether the model rules match the controller rules. Second, in order to ensure the stability of the system, the conditions for system stability indicated by the linear matrix inequality are provided using the relevant theories and methodologies. Next, the stability conditions are solved online, which can obtain the gains of control law in each phase, the minimum running time in the matched case, and the maximum running time in the mismatched case. By utilizing the maximum running duration allows the switching signal to be sent out in advance, preventing asynchronous switching situations and ensuring stable system operation. The simulation results finally demonstrate the viability and effectiveness of the developed controller. [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.

Fault detection (FD) and fault-tolerant cooperative control (FTCC) strategies are proposed in this paper for multiple fixed-wing unmanned aerial vehicles (UAVs) under actuator faults, sensor faults, and wind disturbances. Firstly, the faulty model is introduced while the effectiveness loss, deviation of thrust throttle setting, and pitot sensor faults are considered. Secondly, the faulty UAV model with wind disturbances is linearized and the system is then converted into two subsystems by using state and output transformations. Further, cooperative unknown input observers (UIOs) are developed to estimate the faults, disturbances, and states. By combining with the observers’ estimations, adaptive thresholds are designed to detect actuator and sensor faults in the system. Then, considering state constraints, a backstepping-based FTCC scheme is proposed for multiple UAVs (multi-UAVs) suffering from actuator faults, sensor faults, and wind disturbances. It is shown by Lyapunov analysis that the tracking errors are fixed-time convergent. Finally, the effectiveness of the FD and FTCC scheme is verified by numerical simulation.