Adaptive Fault-tolerant Control Research Articles

Switching-based adaptive fault-tolerant control for uncertain nonlinear systems against actuator and sensor faults

In previous research on fault switching of redundant actuators using monitoring modules, the interference of sensor faults on monitoring results has not received enough attention. In this paper, a new fault-tolerant control (FTC) method combining adaptive compensation and active switching is proposed for a class of uncertain nonlinear systems with backup actuators against actuator and sensor faults. While using command filtered backstepping to reduce computational burden, a direct adaptive compensation scheme is designed to ensure that sensor faults within tolerable bounds do not trigger actuator switching. Based on this, a new lumped monitoring function (MF) containing prescribed performances and tolerable sensor fault bounds is designed to detect and isolate faulty actuators and ensure that the tracking error always satisfies prescribed transient and steady-state performances. Two simulation cases are used for illustrating the proposed method. It is proved that the proposed method can effectively reduce the interference of sensor faults on actuator fault detection and improve the accuracy of actuator switching.

Adaptive Fault-Tolerant Control for Nonlinear MASs Under Actuator Faults and DoS Attacks

In this article, we study the adaptive fault-tolerant control (FTC) for multiagent systems (MASs) under denial-of-service (DoS) attacks and actuator faults. The mixed connectivity-maintained/broken attack containing both connectivity-maintained and connectivity-broken attacks is considered, which results that the MASs are with switching topologies. Also, characteristics of DoS attacks, such as durations and frequencies of attacks, make it more difficult to design fault-tolerant controllers and analyze the stability for MASs with node faults. A novel FTC strategy is presented to compensate for node faults. Then, by using the Lyapunov stability analysis, an average dwell-time condition is presented for the bounded synchronization of MASs under DoS attacks. An example of nonlinear forced pendulum systems is proposed to verify the proposed approach.

Distributed Adaptive Path-Following Control for Distance-Based Formation of Fixed-Wing UAVs under Input Saturation

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.

Distributed adaptive fault tolerant formation control for multiple underwater vehicles: Free-will arbitrary time approach

This note examines the distributed free-will arbitrary time (FwAT) fault-tolerant formation control for heterogeneous multiple autonomous underwater vehicles (AUVs) operating under actuator faults, uncertainties, and exogenous disturbances. The established formation control protocol is free from initial conditions and provides higher tracking accuracy, singularity-free and smooth control signal, while the convergence time of the system is non-conservative. An adaptive nonsingular sliding mode is then developed in which the bound of lumped uncertainty is not necessary to know in advance. Due to the need for a rapid and immediate response in fixed-time control, the actuators are prone to saturation as a result of the high control torque required and to overcome this issue, an input saturation compensator is designed and incorporated into the control framework. Stability analysis under the developed control law is thoroughly performed using the Lyapunov stability theory. Finally, simulations and comparisons are demonstrated in order to verify the effectiveness of the proposed distributed formation control algorithm for a group of AUVs.

Disturbance Observer-Enhanced Adaptive Fault-Tolerant Control of a Quadrotor UAV against Actuator Faults and Disturbances

For a quadrotor unmanned aerial vehicle (UAV), this paper proposes an adaptive sliding mode control (SMC) strategy enhanced with a disturbance observer to attain precise trajectory and attitude tracking performance while compensating for the detrimental impacts of actuator faults and disturbances. First, an adaptive SMC strategy that utilizes an integral sliding surface is presented to enhance the fault-tolerance capabilities of the studied quadrotor UAV against actuator faults. In addition, a disturbance observer is further created to compensate for the disturbances. By integrating the proposed adaptive SMC strategy with the designed disturbance observer, both actuator faults and disturbances can be effectively accommodated. It was theoretically demonstrated that the system is stable while using the proposed adaptive fault-tolerant control strategy. The effectiveness and benefits of the proposed strategy is verified with comparative simulation results under different faulty scenarios.

Adaptive Fault-Tolerant Control of a Hybrid Canard Rotor/Wing UAV Under Transition Flight Subject to Actuator Faults and Model Uncertainties

This paper proposes an adaptive fault-tolerant control scheme for an over-actuated hybrid vertical take-off and landing (VTOL) canard rotor/wing unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties without the requirement of fault information and uncertain bounds. The proposed control scheme is constructed with two separate control modules. The high-level control module is developed with a novel adaptive sliding mode controller, which is employed to maintain the overall system tracking performance in both faulty and fault-free conditions. The low-level control allocation module is used to distribute the virtual control signals that are generated by the high-level control module among the available redundant actuators. In the case of actuator faults, the proposed adaptive scheme can seamlessly adjust the control parameters to compensate the virtual control error and reconfigure the distribution of control signals among the available redundant actuators. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of both actuator faults and model uncertainties and overestimation of the adaptive control parameters can be avoided. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios.

Distributed adaptive fault-tolerant containment control for multi-agent systems with nonautonomous leaders: A hierarchical event-triggered scheme

Distributed adaptive fault-tolerant containment control for multi-agent systems with nonautonomous leaders: A hierarchical event-triggered scheme

Command-Filtered Finite-Time Fuzzy Adaptive Fault-Tolerant Control of Output-Constrainted Robotic Manipulators With Unknown Dead-Zones

This article presents a barrier Lyapunov functions-based (BLFs) adaptive fuzzy finite-time fault-tolerant control scheme for the manipulator with actuator faults and unknown dead-zones. Firstly, by constructing time-varying BLFs, the system output will be constrained in time-varying regions. Secondly, an adaptive method is designed to estimate the degree of actuator faults and to compensate for the effect of dead-zones. Thirdly, the command filtered backstepping with error compensation mechanism is introduced to approximate the virtual control laws, which can not only solve the “explosion of complexity” problem, but also improve the control accuracy. The control method can ensure that all signals of the closed-loop system are finite-time bounded, the tracking errors of joint positions converge to a small neighborhood of the origin, and meets the requirements of time-varying constraints. Finally, a rigid manipulator is used to verify the effectiveness of the scheme.

Neural Network Output-Feedback Consensus Fault-Tolerant Control for Nonlinear Multiagent Systems With Intermittent Actuator Faults.

In this article, the distributed adaptive neural network (NN) consensus fault-tolerant control (FTC) problem is studied for nonstrict-feedback nonlinear multiagent systems (NMASs) subjected to intermittent actuator faults. The NNs are applied to approximate nonlinear functions, and a NN state-observer is developed to estimate the unmeasured states. Then, to compensate for the influence of intermittent actuator faults, a novel distributed output-feedback adaptive FTC is then designed by co-designing the last virtual controller, and the problem of "algebraic-loop" can be solved. The stability of the closed-loop system is proven by using the Lyapunov theory. Finally, the effectiveness of the proposed FTC approach is validated by numerical and practical examples.

Fault-Tolerant Control for Uncertain Nonstrict-Feedback Stochastic Nonlinear Systems With Output Constraints

This article investigates the problem of fault-tolerant control (FTC) for nonstrict-feedback (NSF) stochastic nonlinear systems subject to actuator faults and output constraints. Most of the existing backstepping-based FTC techniques have been developed for strict-feedback systems, which may cause algebraic loop problems when applied directly to NSF systems. In this work, unknown nonlinear functions are approximated by neural networks (NNs). Based on the properties of NN basis functions and a barrier Lyapunov function, a novel adaptive FTC strategy for an NSF system is proposed to achieve tracking control without violating the output constraint. Adaptive fault accommodation terms are constructed to compensate for the faults without a priori information to achieve online fault tolerance. The designed controller guarantees the fault-tolerant tracking performance while ensuring that all signals are bounded in probability and that the output is within the specified constraint. The performance of the proposed FTC strategy is illustrated by simulation studies.

Adaptive fault-tolerant double asynchronous control for switched semi-Markov jump systems via improved memory sampled-data technique

In this article, the issue of adaptive fault-tolerant (AFT) double asynchronous control for a category of switched semi-Markov jump systems (SSMJSs) is studied. Ground on the average dwell time (ADT) mechanism, a high-level switching signal is designed to adjust the change of the low-level semi-Markov chain. For two different switching rules, the double asynchronous phenomenon from the system to the controller is considered, namely, the asynchronous issue of low-level Markov jump modes and the mismatched switching when the high-level switching signals occur in the sampling interval. In addition, a new nonlinear AFT control method is proposed, which is more general than the traditional fault-tolerant model. Besides, an improved double-sided looped-functional method is constructed for sampled-data control (SDC), such that the selected Lyapunov-Krasovskii functional (LKF) can include two novel time-integral states. By using integral inequalities, the sufficient conditions for the system to be exponentially stable are obtained. In the end, the feasibility of the results is proved by comparing the results with some existing approaches through two examples.

Nonlinear-Observer-Based Neural Fault-Tolerant Control for a Rehabilitation Exoskeleton Joint with Electro-Hydraulic Actuator and Error Constraint

The rehabilitation exoskeleton is an effective piece of equipment for stroke patients and the aged. However, this complex human–robot system incurs many problems, such as modeling uncertainties, unknown human–robot interaction, external disturbance, and actuator fault. This paper addresses the adaptive fault-tolerant tracking control for a lower limb rehabilitation exoskeleton joint driven by an electro-hydraulic actuator (EHA). First, the model of the exoskeleton joint is built by considering the principle of the hydraulic cylinder and the servo valve. Then, a novel disturbance-observer-based neural fault-tolerant control scheme is proposed, where the neural network and disturbance observer are incorporated to reduce the influence of the the nonlinear uncertainties and disturbance. Meanwhile, a barrier Lyapunov function is constructed to ensure the stability of the closed-loop system. Finally, comparative simulations on an exoskeleton joint validate the effect of the proposed control scheme.

Decentralized adaptive fault-tolerant control of interconnected systems with sensor faults

The paper considers a class of interconnected nonlinear systems with unknown sensor faults and uncertain interactions. Each subsystem is subject not only to the local sensor faults but also to the possible effects of faults from other subsystems through uncertain interactions. Both multiplicative and time-varying additive sensor faults are taken into consideration, which are allowed to be unknown. A decentralized adaptive fault-tolerant control (FTC) scheme has been established. To eliminate the effects of faults in the control loop, several auxiliary quantities are constructed wisely and estimated by the designed adaptive mechanism. A smooth function is proposed, by which the uncertain interactions can be compensated even if they are coupled with sensor faults. It is proved that, by using only the corrupted states, all the closed-loop signals are globally uniformly bounded, and the output tracking error converges into an adjustable residual set. Finally, simulation and comparison studies are presented to illustrate the effectiveness of the proposed scheme.

Adaptive fault-tolerant trajectory tracking control of twin-propeller non-rudder unmanned surface vehicles

This paper studies the fault-tolerant trajectory tracking control problem of twin-propeller non-rudder unmanned surface vehicles (TPNR USVs) subject to propeller faults. Firstly, a propeller model of TPNR USVs is constructed by decomposing propeller thrusts on the body-fixed reference frame. A propeller fault model is also established by taking into account floating and loss-of-effectiveness faults. Secondly, to ensure tracking errors stay in reasonable ranges, a novel guaranteed transient performance method is proposed. Meanwhile, corresponding error transformation functions are constructed. Thirdly, by utilizing the excellent nonlinearity approximation performance of neural networks (NNs), an adaptive fault-tolerant trajectory tracking control scheme, which can guarantee TPNR USVs track the desired trajectory quickly and accurately even in the event of propeller faults, is proposed. Finally, the fault-tolerant trajectory tracking performance analysis demonstrates the efficiency of the proposed control scheme.

Saturation-tolerant prescribed function-based adaptive fault-tolerant tracking control for ACV with uncertainty and faults

This paper presents an adaptive fault-tolerant control system for Trajectory tracking of air-cushioned vehicles (ACVs) in the presence of actuator saturation, internal and external system perturbations. The proposed approach utilizes a state observer to estimate and compensate for the disturbances and saturation fault information present in the tracking system of the ACV. To achieve the desired performance, a new prescribed performance function (PPF) is introduced that is both global and saturated-tolerant. The PPF ensures that the error converges to a predetermined function in fixed time for any initial value, although it weakens the limits on the amount of overshoot. The combination of the observer and PPF with a backstepping fault-tolerant controller leads to improved transient and steady-state performance of the tracking control system for ACV. Simulation results demonstrate the effectiveness of the proposed approach.

Distributed Adaptive Fault-Tolerant Control for Leaderless/Leader–Follower Multi-Agent Systems against Actuator and Sensor Faults

The faults of actuators and sensors can lead to abnormal operations or even system faults in multi-agent systems (MASs). To address this issue, this paper proposes an adaptive fault-tolerant control (FTC) algorithm for leaderless/leader–follower MASs against actuator and sensor faults. First, extended states integrating the fault components are constructed and the MAS is transformed into a descriptor system form. Then, a sliding-mode observer is designed for the transformed MAS. Based on the estimated MAS states and faults, adaptive FTC algorithms are developed, which update the control gains with the distributed tracking error. Finally, numerical simulations demonstrate that the proposed method can guarantee MAS stability against actuator and sensor faults.

Adaptive Fault-Tolerant Control for a 2-Body Point Absorber Wave Energy Converter Against Actuator Faults: An Iterative Learning Control Approach

In this paper, the design issue of adaptive fault-tolerant control (FTC) is investigated for a class of continuous-time 2-body point absorber wave energy converter (WEC) systems against actuator faults based on the iterative learning approach. The actuator faults considered in this paper contain both the lock-in-place and the loss of effectiveness faults, simultaneously. The WEC dynamic equations, including two moving parts (i.e., the float and the spar), are firstly transformed into a state-space model. Then, a group of novel iterative learning based adaptive multiple controllers are developed to decrease the tracking error between the measurement output and the desired output, and two novel adaptive laws are designed to cope with two types of actuator faults. Based on the theories mentioned above, a novel algorithm is provided to present the operation flows of both adaptive laws and iterative learning. Furthermore, a sufficient condition is obtained with the aid of proper Lyapunov function, such that the related closed-loop faulty-WEC system is asymptotically stable with a guaranteed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance index. Finally, an example with a set of physical parameters of a WEC dynamic model is worked out to verify the applicability and effectiveness of the proposed iterative learning based adaptive FTC strategy.

Adaptive attitude angle constrained fault-tolerant control of hypersonic vehicle with unknown centroid shift

This work takes a further step into the adaptive fault-tolerant control (FTC) scheme to cope with the challenges deriving from the hypersonic vehicle (HSV) in the presence of unknown centroid shift, input saturation, and actuator fault. The influence of unknown centroid shift is mainly manifested in the following aspects: 1) uncertainties of the system input matrix, 2) mixed system uncertainties, and 3)eccentric moments. A novel attitude state constraint control strategy is technically proposed by incorporating the extended barrier Lyapunov function (Ex-BLF) and the Nussbaum-type function into the backstepping design to keep the safe flight of HSV. A unified controller is designed to handle the cases with/without state constraints based on the Ex-BLF with its auxiliary system. For unknown mixed system input matrix due to the coupling of uncertainties of the inertial matrix, actuator fault, and system input saturation, a specific Nussbaum-type function assisted by a state-depend auxiliary system is designed to compensate for the influence of those time-varying nonlinear terms. As a consequence, combined with the Lyapunov stability theory, it is confirmed that the proposed FTC scheme ensures that all the closed-loop signals are bounded. Simulation results are carried out to illustrate the effectiveness and advantage of the proposed control scheme.

Unmodeled dynamics suppressed adaptive fault tolerant control for a class of space robots with actuator saturation and faults

This paper investigates the tracking control issue of a class of complicated space robots subject to actuator saturation and faults, unmodeled dynamics and external disturbances under asymmetric error constraints, and develops a Bias Radial Basis Function Neural Network (BIAS-RBFNN) based intelligent adaptive fault tolerant control scheme. First, considering that the unmodeled dynamics may be coupled with the states and inputs of the system, dynamic auxiliary signal and related mathematical tools are used to decouple and suppress the coupling uncertainties. Moreover, a mapping function based nonlinear error transformation technology is utilized to guarantee the transient performance of the system. Considering the shortcomings of traditional neural networks, the BIAS-RBFNNs have been constructed to improve the approximation and compensation performance. Finally, numerical simulations are carried out to illustrate the effectiveness and advantages of the proposed BIAS-RBFNN based intelligent adaptive fault tolerant control method.

Fault-tolerant control based on reinforcement learning and sliding event-triggered mechanism for a class of unknown discrete-time systems

This paper presents an adaptive fault-tolerant control (FTC) system based on reinforcement learning using an even-triggered mechanism. The even-triggered mechanism is established through a justifiable sliding surface and triggered function, without the need for any fault detection or observer. The learning laws are derived to ensure the convergence of internal signals and tracking error, and an actor–critic architecture is designed accordingly. To validate the proposed scheme, an experimental system is constructed and tested using five typical actuator faults. The results indicate a positive closed-loop performance and a reduction of approximately 25% in data transmission for both cases with and without faults.