Finite-time Fault-tolerant Control Research Articles

Fault-tolerant trajectory tracking control of an unmanned marine vehicle via an adaptive non-singular fast terminal sliding mode control

In this paper, a novel finite-time fault-tolerant trajectory tracking controller is created to render a marine vehicle to enhance tracking performance in the presence of complex unknown variables, including model uncertainties, environmental disturbances, and actuator faults. An adaptive fault-tolerant finite-time sliding mode controller is designed by introducing adaptive control techniques, the non-singular fast terminal sliding mode (NSFTSM) function, and a radial base function (RBF) neural network. The radial base function neural network (RBFNN) is developed to eliminate the influences of model uncertainties and environmental disturbances. A fault compensation by integrating the adaption technique is designed to reduce the effects of actuator faults and approximation errors. Suffering from uncertainties and actuator faults, the proposed finite-time tracking controller can track the desired trajectory with high precision. Simulation results and compared simulations indicate the efficiency and superiority of the proposed controller.

Adaptive finite time fault tolerant control for the quadrotor unmanned aerial vehicles based on time‐triggered strategy

AbstractThis article investigates the adaptive finite time tracking control problem for quadrotor unmanned aerial vehicles (QUAV) subject to actuator failure with event‐triggered control strategy. It is assumed that the models of actuator failure are actuator blockage and saturation faults. The finite time performance function and adaptive backstepping method are combined to design the controller to compensate the influence of actuator failure, so as to ensure that the tracking error converges to the preset neighborhood near the origin in finite time. In addition, a new event‐triggered strategy is introduced to save communication resources and avoid the Zeno‐behavior, which defines the variable threshold as a function combining with tracking error and positive constants. The variable threshold not only effectively reduces triggering times, but also makes the design of the controller more flexible. It is proved that the closed‐loop system is stability. Finally, the effectiveness of this method is verified by simulation.

Finite-time Fault-tolerant Control of Robotic Systems with Uncertain Dynamics

Finite-time Fault-tolerant Control of Robotic Systems with Uncertain Dynamics

Adaptive fuzzy finite‐time fault‐tolerant control design for non‐linear systems under sensor faults

In this article, an adaptive fuzzy finite-time fault-tolerant control (FTC) scheme for uncertain non-linear systems under sensor faults is proposed. Compared with the existing methods, the considered system contains unknown time-varying fault parameters, uncertain non-linear functions, and can guarantee the performance of the system in finite time. The coupling between fault parameters and actual states is solved by the fault parameters separation method. The fuzzy logic system (FLS) is used to approximate the unknown functions, and combining the backstepping technology an adaptive fault-tolerant controller is designed. The finite-time stability of the closed-loop system is proved by the Lyapunov theory. At last, the numerical simulation and the real physical system simulation verified the effectiveness of the proposed scheme.

Observer-Based Adaptive Fuzzy Finite-Time Fault-Tolerant Control for Stochastic Nonlinear Systems with State Constraint

Observer-Based Adaptive Fuzzy Finite-Time Fault-Tolerant Control for Stochastic Nonlinear Systems with State Constraint

Performance-improved finite-time fault-tolerant control for linear uncertain systems with intermittent faults: an overshoot suppression strategy

This paper presents a novel prespecified finite-time and overshoot-restrained fault-tolerant tracking control scheme to compensate the intermittent faults in linear uncertain systems. Starting from the system tracking error dynamics model, we design a speed excitation function to improve the response speed of the control. A finite-time performance index function is established in the zero-sum game framework for the fault-free optimal control policy. Based on Lyapunov stability theory, a fault compensation oriented fault estimation and diagnosis method is proposed to ensure the uniformly ultimately bounded stability of tracking errors. It is noteworthy that the proposed speeding fault-tolerant control can accelerate the trajectory tracking, narrow the upper bound of tracking errors and restrain the overshoot. Numerical and practical experiments fully illustrate the effectiveness of the proposed strategy.

Quaternion-based finite-time fault-tolerant trajectory tracking control for autonomous underwater vehicle without unwinding

This brief disposes the finite-time anti-unwinding trajectory tracking control problem of the autonomous underwater vehicle (AUV) encountering model uncertainties, ocean disturbances and actuator failures. Primarily, the kinematic model of translational and rotational motions is depicted by unit quaternion in lieu of classical Euler angle such that the AUV’s dynamics could be globally and uniquely formulated. Subsequently, two finite-time control strategies are presented here to leave the state variables of AUV can converge to an adjustable region. Additionally, the adaptive laws could be applicable to the existence of actuator faults by utilizing a passive fault-tolerant technology. By integrating the initial value of the scalar quaternion into the sliding mode surface, the proposed controllers are characterized with anti-unwinding property. Then, with the application of hyperbolic tangent function, finite-time stability will be achieved for tracking errors without singularity. Stability of the closed-loop system is verified via the Lyapunov theorem. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed controllers.

Model free based finite time fault‐tolerant control of robot manipulators subject to disturbances and input saturation

AbstractThis article proposed a model free based finite time fault‐tolerant control (FTC) method of robot manipulators subject to unknown disturbances, input saturation, and actuator faults. First, an accuracy‐driven integral terminal sliding mode surface (ADITSMS) was constructed, and the finite‐time convergence and the parametric analysis were investigated. Second, based on the proposed ADITSMS, a double‐loop control framework which consists of the position loop and velocity loop was proposed, and the finite time command filtered algorithm was utilized to estimate the derivative of the virtual control law of the position loop, thus a novel finite‐time robust adaptive FTC was proposed. Third, to eliminate the negative effects of the faults and disturbances and implement model free control, the uncertainty and disturbance estimation is designed, and a novel adaptive algorithm is developed to suppress the estimation error whose upper bound or derivative was not required. Meanwhile, an auxiliary system is constructed to deal with the input saturation. The proposed controller possess the superiorities of model free nature and global finite time convergence property. Finally, numerical simulations and comparison studies were conducted to demonstrate the effectiveness of the proposed controller.

Multiple delay-dependent finite-time fault-tolerant control for switched fuzzy systems

The work is concerned with this issue of multiple delay-dependent finite-time fault-tolerant control (FTC) for uncertain switched Takagi-Sugeno (T-S) fuzzy systems against state and input constraints. There exist intermittent faults (IFs), exogenous disturbances along with measurement noise in the models. There are few attempts for this theme. A nonlinear dynamic output feedback controller is explored for these uncertain switched T-S fuzzy systems first. And an augmented system with respect to realizing FTC is acquired. Moreover, sufficient conditions of robust finite-time H∞ control are constructed by piecewise fuzzy Lyapunov function. At the same time, finite-time boundedness (FTB) as well as input-output finite-time stability (IO-FTS) is achieved. The effectiveness as well as feasibility of this approach is verified through an example.

Finite-Time Fault-Tolerant Control for a Stewart Platform Using Sliding Mode Control With Improved Reaching Law

In this paper, a fault-tolerant control (FTC) is proposed for a nonlinear system as a Stewart platform (SP). To reject the singularity issue of a traditional fast terminal sliding mode control (FTSMC) and to have a fast finite-time convergence, a nonsingular fast terminal sliding mode control (NFTSMC) is used. In addition, an extended state observer (ESO) is applied for the control scheme to estimate uncertainties, disturbances, and faults. To increase the convergence speed and alleviate the chattering phenomenon, a novel reaching law is proposed which gives the system a quick reaching speed. Finally, a novel FTC that ensures robustness to disturbances and faults is developed based on the NFTSMC, the ESO, and the proposed reaching law. Consequently, the proposed FTC has outstanding features such as high tracking performance, a decrease in the effects of disturbances and faults, a fast convergence speed in finite time, and less chattering. The simulation and experiment results demonstrate the efficiency of the proposed FTC compared to other control schemes.

Finite-time fault tolerant neural control of nonlinear multi-agent systems under switching topologies

The neural tracking control problem for nonlinear strict-feedback multi-agent systems (MASs) subject to actuator faults in finite-time is considered, where each agent communicates with its neighbours on a time-varying directed topology. Radial basis function neural networks (RBFNNs) are used to approximate the unknown internal dynamics of system. By utilising backstepping method and dynamic surface control (DSC) technique, a novel adaptive fault tolerant controller is put forward. It turns out that the designed controller can compensate the effect of uncertainties and actuator faults. Meanwhile, by constructing piecewise Lyapunov functions, sufficient conditions for dwell time of topologies are given such that system achieves finite-time tracking consensus under the designed controller. Finally, an example is carried out to verify feasibility of the theoretical result.

Vibration suppression and fault-tolerant attitude control for flexible spacecraft with actuator faults and malalignments

An efficient and cost-effective finite-time fault-tolerant attitude controller for a class of flexible spacecraft is designed in this paper to cater to flexible appendages' vibrations, along with the simultaneous consideration of erratic inertial uncertainties, environmental disturbances, and actuator-related faults. First, a novel and in-depth modeling of the actuator's performance under output degradation, bias and orientation alignment faults is enacted, which redefines the actuator's performance matrix. Then adaptive estimators are conceived to estimate the lumped uncertainties and actuator-related faults. Based on a modified fast nonsingular terminal sliding mode control (MFNTSM), an adaptive fault-tolerant attitude controller is propounded to realize highly precise attitude tracking and error trajectories' finite-time convergence. The proposed controller's prominent feature is that the unknown uncertainties, actuator-related faults, and flexible vibrations are simultaneously tackled without the aid of intelligent actuators and sensors, which are generally applied for vibration suppression. The spacecraft can accomplish the coveted control objective in bounded time, and the stability of the propound controller is established via Lyapunov techniques. Finally, the simulation outcomes exhibit the profound performance of the propound controller.

Adaptive distributed finite‐time fault‐tolerant controller for cooperative braking of the vehicle platoon

Vehicle platooning can significantly reduce traffic accidents and enhance transportation safety. Among many subsystems and functionalities equipped in a vehicle platoon, cooperative braking is a safety-critical one. Besides, as actuator faults would deteriorate vehicle safety and stability, they pose a great challenge to the platoon, particularly during cooperative braking. To address the aforementioned problems, this study designed an adaptive distributed finite-time fault-tolerant controller for vehicle platoons under cooperative braking condition. First, based on the graph theory and vehicle longitudinal dynamics, the cooperative braking model of a platoon is constructed. Then, the models of hydraulic braking system and regenerative braking system are developed with malfunction analysis. Based on the vehicle's fault model and the representation of the platoon consensus errors, an adaptive finite-time sliding-mode fault tolerant controller is proposed to maintain consensus between vehicle's states during fault occurring. Further, a distributed adaptive law is presented considering the parameter estimation error and sliding-mode surface. The finite-time convergence property and the stability of the proposed controller are demonstrated. Numerical simulations are conducted under different conditions. The simulation results reflected by the control performance and actuators' responses validate the feasibility and effectiveness of the designed control method.

A novel finite-time prescribed performance control scheme for spacecraft attitude tracking

This paper studies the issue of finite-time prescribed performance control for spacecraft attitude tracking with inertia perturbations, external disturbances, actuator saturations and faults. To the best of the authors' knowledge, limited results have been reported in the relevant literature, and how to achieve the prescribed performance attitude tracking within a preset time interval is still an open problem. A novel finite-time prescribed performance function (FTPPF) whose settling time can be arbitrarily preset is first proposed. With the FTPPF predefining the envelope of tracking-error trajectories, the original spacecraft model is transformed into a new error system. Based on the barrier Lyapunov function of converted errors, the attitude controller is derived via backstepping design. During the process, the fuzzy approximation is used to handle inertia perturbations and external disturbances, while the Nussbaum gain technique is adopted to compensate for the efficiency loss caused by actuator saturations and faults. Finally, a finite-time fault-tolerant control scheme that guarantees both transient and steady-state performances (e.g., the maximum overshoot, steady-state error, and settling time) is developed. To verify the effectiveness of the solution, numerical experiments involving comparisons with related achievements are performed.

Robust Adaptive Finite-time Fault-tolerant Control for Dynamic Positioning of Vessels

Robust Adaptive Finite-time Fault-tolerant Control for Dynamic Positioning of Vessels

Adaptive Finite-Time Fault-Tolerant Control for Half-Vehicle Active Suspension Systems with Output Constraints and Random Actuator Failures

The problem of adaptive finite-time fault-tolerant control (FTC) and output constraints for a class of uncertain nonlinear half-vehicle active suspension systems (ASSs) are investigated in this work. Markovian variables are used to denote in terms of different random actuators failures. In adaptive backstepping design procedure, barrier Lyapunov functions (BLFs) are adopted to constrain vertical motion and pitch motion to suppress the vibrations. Unknown functions and coefficients are approximated by the neural network (NN). Assisted by the stochastic practical finite-time theory and FTC theory, the proposed controller can ensure systems achieve stability in a finite time. Meanwhile, displacement and pitch angle in systems would not violate their maximum values, which imply both ride comfort and safety have been enhanced. In addition, all the signals in the closed-loop systems can be guaranteed to be semiglobal finite-time stable in probability (SGFSP). The simulation results illustrate the validity of the established scheme.

Fault identification and fault-tolerant control for unmanned autonomous helicopter with global neural finite-time convergence

In this paper, the issue of global neural finite-time fault-tolerant control (FTC) is investigated for the medium-scale unmanned autonomous helicopter (UAH). To recognize the actuator bias and loss of effectiveness (LOE) faults, a novel fault detection and identification (FDI) strategy is proposed, which consists of a fault detection observer, two adaptive fault observers and a decision-making algorithm. The neural network (NN) technique is employed to deal with the unknown system uncertainty. In view of the backstepping approach and Lyapunov theory, a finite-time FTC scheme is developed to assure that all closed-loop system tracking errors converge to a small range of zero after a limited amount of time. Meanwhile, by integrating a switching mechanism into the control design, the traditional semi-globally uniformly ultimately bounded (SGUUB) stability is extended to globally uniformly ultimately bounded (GUUB) stability, such that the constraints on initial conditions of the NN controller is moderated. Simulation studies are implemented to demonstrate the usefulness of the presented controller.

Robust finite-Time control and reachable set estimation for uncertain switched neutral systems with time delays and input constraints

This work focuses on robust finite-time fault-tolerant control and reachable set estimation for uncertain switched neutral systems subject to time delays as well as input constraints. There are few attempts to investigate robust finite-time boundedness and reachable set estimation for uncertain switched neutral systems. At the same time, input-output finite-time stability is also investigated. Compared with the existing studies, this system has wider application. A dynamic output feedback nonlinear controller is researched. An augmented closed-loop system is provided. Moreover, the sufficient conditions of finite-time boundedness, reachable set estimation and input-output finite-time stability for the closed-loop system are obtained in the framework of linear matrix inequalities via piecewise Lyapunov function. Ultimately, two examples are provided to demonstrate this validity of this approach in this paper.

Neural Network-Based Finite-Time Fault-Tolerant Control for Spacecraft without Unwinding

In this paper, we focus on solving the problems of inertia-free attitude tracking control for spacecraft subject to external disturbance, unknown inertial parameters, and actuator faults. The robust control architecture is designed by using the rotation matrix and neural networks. In the presence of external disturbance and parametric uncertainties, a fault-tolerant control (FTC) scheme synthesized with the minimum-learning-parameter (MLP) algorithm is proposed to improve the reliability of the system when unknown actuator faults occur. These methods are developed based on backstepping to ensure that finite-time convergence is achievable for the entire closed-loop system states with low computational complexity. The validity and advantage of the designed controllers are highlighted by using Lyapunov-based analysis. Finally, the simulation results demonstrate the satisfactory performance of the developed controllers.

Adaptive neural finite-time formation control for multiple underactuated vessels with actuator faults

This paper proposes a novel neural finite-time formation control algorithm for multiple underactuated surface vessels with actuator faults. In the algorithm, the leader-follower formation problem is formulated as a two-stage tracking problem. First, to address the leader-follower configuration without the information of leader velocity, the virtual vessel is designed to track the reference trajectory of the leader. Second, an adaptive finite-time fault-tolerant control (AFFTC) algorithm is presented for the follower to track the virtual vessel. By fusion of the neural network (NN) and the fractional power, the model uncertainty is approximated and the finite-time convergence is obtained. Furthermore, a concise adaptive law is developed to compensate the upper bounded of NN weights and lump disturbance which include the approximation error of NN, control gain uncertainty, actuator faults and marine environmental disturbance. On the basis of Lyapunov theory, stability analysis proves that all the signals in the closed-loop system are practical finite-time stable. Finally, numerical simulations are performed to demonstrate the performance and superiority of the proposed algorithm.