Adaptive Fault-tolerant Control Law Research Articles

Event-triggered adaptive vibration control for a flexible satellite with time-varying actuator faults

In this study, vibration control is studied for the flexible satellite through wireless communication, and given the fact that the actuators are prone to unknown faults, the input signal event-triggering and time-varying actuator faults are considered for the flexible satellite simultaneously. The satellite system is composed of two symmetrical flexible panels attached to a centrebody, which is a distributed parameter system and the established model is represented by partial differential equations (PDEs). Based on the PDEs model of the flexible satellite, the input event-triggered mechanism using the relative threshold strategy is designed firstly to lower the communication burden, and then the event-triggered-based adaptive fault-tolerant control laws are developed with the aid of the designed auxiliary signals for the system with time-varying actuator faults. With the proposed control scheme, the vibration of the system is controlled to the small neighborhood of zero, and the angle of the panels is regulated to the desired position. Finally, numerical simulation results are given to further show the effectiveness of the designed control scheme.

Robust Adaptive Fault-Tolerant Control for a Riser-Vessel System With Input Hysteresis and Time-Varying Output Constraints.

Recently, with the development of the marine economy, marine risers have garnered increasing attention as they present facile and reliable methods for oil and gas transportation. However, these risers are susceptible to vibrations, which can lead to system performance degradation and fatigue damage. Therefore, effective vibration control strategies are required to address this issue. In this study, a novel adaptive fault-tolerant control (FTC) strategy is adopted to suppress the vibrations of a 3-D riser-vessel system against the effects of actuator failures, backlash-like hysteresis, and external disturbances. A barrier-based Lyapunov function is merged to eliminate the time-varying output constraints of the system. Adaptive FTC laws with projection mapping operators are designed to compensate for parameter uncertainties and consider input nonlinearities to improve system robustness. Finally, a rigorous Lyapunov analysis and numerical simulations are performed to verify the validity of the proposed controller and guarantee uniformly bounded stability of the system.

Fault tolerant attitude control of under-actuated spacecraft: Theory and experiment

This paper investigates fault tolerant attitude control theory and experiment for under-actuated spacecraft with one reaction wheel completely broken and two others suffering actuator faults of partial loss of effectiveness or bias. A non-smooth robust adaptive fault tolerant control law is proposed under the zero-momentum and input saturation conditions. It shows that the available reaction wheels need to produce sufficient control torque for the fault tolerance. Such a new control method is implemented in a semi-physical simulation system of an air-bearing platform. Experimental results show the effectiveness of the proposed method in spacecraft practical engineering.

Sensor fault-tolerant control for wind turbines: an iterative learning method

The combined wind speed estimator and tip speed ratio (WSE-TSR) tracking control scheme is widely used to regulate power production for large-scale modern wind turbines. Although very effective, such an advanced control scheme, based on the prior model information, is highly dependent on external measurements. For partial-load region control, the only external information involved is commonly the measured rotor or generator speed. Inaccuracy in such sole measurement results in an unintended turbine operation and might lead to sub-optimal power production and instability. This paper presents a fault-tolerant control (FTC) method, which aims to eliminate the sensor fault effects for modern wind turbine systems. To fulfil this goal, an iterative learning scheme is proposed to detect and estimate the multiplicative sensor fault, on which an adaptive FTC law is formulated such that the effects of the sensor fault are eliminated. Case studies show that the proposed iterative learning FTC method performs well in detecting, estimating, and accommodating the sensor fault under realistic turbulent wind conditions. The advanced wind turbine controller can maintain its control performance even under faulty conditions, preventing further damage to other turbine components and allowing for continuous power production.

Adaptive robust fault-tolerant control for a two-slider synchronization system with a flexible beam

In this paper a novel adaptive robust fault-tolerant sync control method is proposed for a two-slider system where two sliders are constrained by a flexible beam. At first the dynamic models of sync motion system subject to external disturbances and actuator faults are derived. In order to avoid the shortcomings of truncated model, the model of flexible beam is described by using infinite dimensional equation. Then based on the models a novel disturbance observer and an adaptive fault-tolerant control law are designed. The disturbance observer is used to estimate and cancel external disturbances. The adaptive fault-tolerant control is used to deal with the partial loss of effectiveness faults. Lyapunov functional approach is used to prove that the closed-loop system with the proposed control laws is uniformly bounded stable. Finally, some simulation results display that the proposed control laws can obtain excellent sync performance in the present of external disturbances and actuator partial loss of effectiveness faults.

Robust synchronization of uncertain Markovian jumping complex interconnected neural networks via adaptive fault-tolerant control

This article inspects the problem of robust synchronization for uncertain Markovian jumping complex interconnected neural networks with randomly occurring uncertainties and time delays. The uncertainties considered here occur randomly and are assumed to follow certain mutually uncorrelated Bernoulli distributed white noise sequences. The presence of sensor faults may cause degradation or even instability of the entire network. Therefore, control laws are designed with sensor faults to ensure the controlled synchronization of the complex interconnected neural networks. Three types of fault-tolerant controls are designed based on the Lyapunov stability theory and adaptive schemes which include passive and adaptive fault-tolerant control laws. By constructing a new Lyapunov-Krasovskii functional (LKF) and by using Jensen’s inequality with a free-weighting matrix approach, some new delay-dependent synchronization criteria are obtained in terms of linear matrix inequalities (LMIs). By using the Lyapunov stability theory, the existence condition for the adaptive controller that guarantees the robust mean-square synchronization of complex interconnected neural networks in terms of LMIs are derived. Finally, a numerical example is presented to demonstrate the performance of the developed approach.

Neural adaptive fault-tolerant finite-time control for nonstrict feedback systems: An event-triggered mechanism

The problem of event-triggered neural adaptive fault-tolerant finite-time control is investigated for a class of nonstrict feedback nonlinear systems in the presence of nonaffine nonlinear faults. The event-triggered signal is designed by using a relative-threshold to reduce communication burden. The dynamic surface control method is used to relax the assumption of the reference signal and deal with the computational complexity issue. Based on the finite-time stability, a new neural adaptive backstepping design method is developed. The event-triggered neural adaptive fault-tolerant control law is developed for the closed-loop system so that not only the semi-global practical finite-time stability is ensured, but also the tracking performance with a small residual set is guaranteed. Finally, the effectiveness of the proposed control law is verified via simulation results.

Adaptive fault-tolerant flutter control considering related failure

This article proposes a novel adaptive fault-tolerant control method for suppressing flutter and compensating for related failure in a flutter system. Considering cubic nonlinearity, external disturbances, and related failure, the flutter dynamic model was established firstly. Then, an adaptive fault-tolerant control law was proposed on basis of this model to compensate for related failure and suppress flutter. By Lyapunov stability analysis, the stability of proposed control law was proved in detail. On the last, simulation results further proved the effectiveness of the control law which can not only suppress flutter and compensate for related failure successfully but also has good robustness for external disturbances and system perturbation.

Dynamics and adaptive fault-tolerant flight control under structure damage of horizontal stabilizer

This paper proposes a mathematical model and an adaptive flight controller that considers structural damage to the horizontal stabilizer of an aircraft. The aerodynamic derivatives are determined based on the structural damage rate of the horizontal stabilizer. A failure model that considers the aerodynamic derivatives of the damaged horizontal stabilizer is established, and the efficiency coefficients is modified based on wind tunnel experiments. An adaptive fault-tolerant control law based on parameter estimation is designed to achieve active fault tolerance in case of horizontal stabilizer damage. The simulation and experimental results indicate that the proposed model and adaptive fault-tolerant controller provide preferable performance when the horizontal stabilizer is damaged.

A Neural Network Adaptive Fault-Tolerant Control Method for Launch Vehicles with the Limited Faults

To tolerate the limited faults such as thrust decline or actuator jamming of launch vehicles, an adaptive fault-tolerant control method based on radial basis function neural network (RBFNN) is proposed in this paper. The method is based on a limited faults dynamics model, and the baseline controller is designed based on the pole placement, using RBFNN to online identify and compensate the fault parameters and uncertain disturbances in the model. Then an adaptive fault-tolerant control law is designed based on Lyapunov theory. The simulation results show that the proposed adaptive control method can effectively ensure the attitude stability as well as control accuracy under the limited faults of launch vehicles, compared with the traditional PD control method.

Adaptive Backstepping Sliding Mode Fault Tolerant Control for Satellite Attitude under Actuator Faults

Modern spacecraft missions place stringent performance requirements on the reliability and stability of spacecraft attitude control system. However, during long-term in-orbit mission, actuators may suffer faults. In this paper, we proposed an adaptive fault tolerant control law for attitude control under actuator failures and external disturbances. Firstly, the attitude dynamic model under actuator faults and attitude kinematics are described. Then, in order to solve the attitude control problem under actuator faults and external disturbances, an adaptive backstepping sliding mode fault tolerant control scheme is designed. According to Lyapunov theory, the closed-loop system is proved to be globally asymptotically stable. Finally, the numerical simulation results demonstrate that the proposed adaptive controller can achieve anticipative attitude control performance, fault information estimation and well fault-tolerant capability.

Multi-Agent Fault-Tolerant Control Based on Distributed Adaptive Consensus

This paper proposes a distributed adaptive control approach based on consensus theory so that a multi-agent formation can still complete the task despite the local fault of the leader for the multi-agent formation system. The controlled object consists of four agents that form a triangle formation system, where one agent acts as the vertex of the triangle, and the remaining agents act as followers in a line. In addition, the speed of the leader is the forward direction of the formation, and the followers are behind the leader. Based on graph theory, the distributed adaptive updating of the agents' local information parameters are conducted, and the distributed adaptive control law is used to supplement the influence of the leader's fault in the multi-agent formation. According to the local information of adjacent agents, an overall distributed adaptive fault-tolerant control law is designed, and the stability of the designed controller is proved by constructing the Lyapunov function. Meanwhile, the relative distance error between the horizontal direction and longitudinal direction of the leader-follower converge to zero. The simulation results show that the proposed adaptive control approach has good robustness, which provides a theoretical basis for engineering practice.

Global fixed-time attitude tracking control for the rigid spacecraft with actuator saturation and faults

This paper investigates the global finite-time attitude tracking problem for the rigid spacecraft subject to inertial uncertainties, external disturbances, actuator faults, and input saturation constraints. The exponential coordinates vector in conjunction with a hysteretic-based jump condition is introduced to overcome the topological obstacles of global stability on the special orthogonal group. A novel nonsingular fixed-time-based sliding mode is designed, which not only avoids the singularity but also guarantees that the convergence time of tracking errors along the sliding surface is independent of the state value. Then, an adaptive fault-tolerant control law is constructed to enforce the system state to reach a neighborhood of the sliding surface in the sense of the fixed-time concept, which can accommodate actuator failures under limited control torque. The total convergence time is independent of the initial conditions information. A rigorous mathematical stability Proof is given. Numerical simulations are finally performed to demonstrate the effectiveness of the proposed finite-time controller.

Adaptive dynamic programming method‐based synchronisation control of a class of complex dynamical networks with unknown dynamics and actuator faults

This study is concerned with the adaptive fault-tolerant synchronisation control problem for a class of complex dynamic networks with unknown internal dynamics and actuator faults. A controller which consists of adaptive fault-tolerant control laws and a static feedback gain is designed to achieve the synchronisation. A modified iterative algorithm via adaptive dynamic programming technique is developed to compute the static feedback gain, and based on which adaptive fault-tolerant control laws are then designed, without requiring the a priori knowledge of the system matrices, to compensate the actuator faults. Furthermore, the asymptotic convergence of synchronisation errors is rigidly analysed by combining graph theory and Lyapunov theory, and all the other signals in synchronised error system are also proved to be bounded. Finally, a simulation example is illustrated to demonstrate the effectiveness of the proposed method.

Adaptive-gain fast super-twisting sliding mode fault tolerant control for a reusable launch vehicle in reentry phase

In this paper, a novel adaptive-gain fast super-twisting (AGFST) sliding mode attitude control synthesis is carried out for a reusable launch vehicle subject to actuator faults and unknown disturbances. According to the fast nonsingular terminal sliding mode surface (FNTSMS) and adaptive-gain fast super-twisting algorithm, an adaptive fault tolerant control law for the attitude stabilization is derived to protect against the actuator faults and unknown uncertainties. Firstly, a second-order nonlinear control-oriented model for the RLV is established by feedback linearization method. And on the basis a fast nonsingular terminal sliding mode (FNTSM) manifold is designed, which provides fast finite-time global convergence and avoids singularity problem as well as chattering phenomenon. Based on the merits of the standard super-twisting (ST) algorithm and fast reaching law with adaption, a novel adaptive-gain fast super-twisting (AGFST) algorithm is proposed for the finite-time fault tolerant attitude control problem of the RLV without any knowledge of the bounds of uncertainties and actuator faults. The important feature of the AGFST algorithm includes non-overestimating the values of the control gains and faster convergence speed than the standard ST algorithm. A formal proof of the finite-time stability of the closed-loop system is derived using the Lyapunov function technique. An estimation of the convergence time and accurate expression of convergence region are also provided. Finally, simulations are presented to illustrate the effectiveness and superiority of the proposed control scheme.

Fault-tolerant control for multiple networked spacecraft under actuator saturation

In this paper, fault-tolerant attitude tracking control problem is investigated for multiple spacecraft formation flying system with external disturbance, actuator saturation, and faults. A quaternion-based adaptive fault-tolerant control law is proposed based on input normalized neural network. The desired nonlinear smooth function is approximated by using input normalized neural network with an adaptive learning algorithm, and no prior knowledge about spacecraft dynamics is required. Meanwhile, in order to guarantee that the output of input normalized neural network used in the controller is bounded by the corresponding bound of the approximated unknown function, a modified adaptive law is designed to revise the sliding mode manifold. Moreover, the stability of system can be guaranteed by Lyapunov theory. Finally, the validity of the proposed control algorithm is verified through numerical simulations.

Prescribed-performance fault-tolerant control for feedback linearisable systems with an aircraft application

ABSTRACTThis paper investigates fault-tolerant control (FTC) for feedback linearisable systems (FLSs) and its application to an aircraft. To ensure desired transient and steady-state behaviours of the tracking error under actuator faults, the dynamic effect caused by the actuator failures on the error dynamics of a transformed model is analysed, and three control strategies are designed. The first FTC strategy is proposed as a robust controller, which relies on the explicit information about several parameters of the actuator faults. To eliminate the need for these parameters and the input chattering phenomenon, the robust control law is later combined with the adaptive technique to generate the adaptive FTC law. Next, the adaptive control law is further improved to achieve the prescribed performance under more severe input disturbance. Finally, the proposed control laws are applied to an air-breathing hypersonic vehicle (AHV) subject to actuator failures, which confirms the effectiveness of the proposed strategies.

Fault estimation and adaptive fault tolerant control for dynamic systems based on the second-order sliding mode observer

This article is concerned with observer-based fault estimation and adaptive fault tolerant control for a class of continuous-time dynamical systems. First, a second-order sliding mode observer is proposed, which is capable to eliminate chattering effects for fault estimation caused by the conventional sliding mode observer. Second, in order to avoid the cumbersome stability proving process by the geometric method, a Lyapunov function is adopted to prove the observer error dynamical system. Third, based on the estimated fault information by the proposed observer, an adaptive fault tolerant control law is developed to guarantee the stability of the faulty system. Finally, the proposed method is applied to the Boeing 747-100/200 flight control system, and the simulation results verify the effectiveness of the proposed scheme.

Fault tolerant synchronization for a class of complex interconnected neural networks with delay

SUMMARYThis paper is concerned with the fault tolerant synchronization problem for a class of complex interconnected neural networks against sensor faults. As sensor faults may lead to performance degradation or even instability of the whole network, fault tolerant control laws are designed to guarantee the controlled synchronization of the complex interconnected neural networks. On the basis of Lyapunov stability theory and adaptive schemes, three kinds of fault tolerant control laws are designed on the basis of linear matrix inequality technique. One is the passive fault tolerant control law, the other two are adaptive fault tolerant control laws. The latter two methods use the adaptive adjusting mechanism of the coupling coefficients to ensure the synchronization of the networks in the presence of sensor faults. Simulation results are given to verify the effectiveness of the proposed methods. Copyright © 2013 John Wiley & Sons, Ltd.

Fault tolerant small satellite attitude control using adaptive non-singular terminal sliding mode

The Attitude Control System (ACS) plays a pivotal role in the whole performance of the spacecraft on the orbit; therefore, it is vitally important to design the control system with the performance of rapid response, high control precision and insensitive to external perturbations. In the first place, this paper proposes two adaptive nonlinear control algorithms based on the sliding mode control (SMC), which are designed for small satellite attitude control system. The nonlinear dynamics describing the attitude of small satellite is considered in a circle reference orbit, and the stability of the closed-loop system in the presence of external perturbations is investigated. Then, in order to account for accidental or degradation fault in satellite actuators, the fault-tolerant control schemes are presented. Hence, two adaptive fault-tolerant control laws (continuous sliding mode control and non-singular terminal sliding mode control) are developed by adopting the nonlinear analytical model to describe the system, which can guarantee global asymptotic convergence of the attitude control error with the existence of unknown external perturbations. The nonlinear hyperplane based Terminal sliding mode is introduced into the control law design; therefore, the system convergence performance improves and the control error is convergent in “finite time”. As a result, the study on the non-singular terminal sliding mode control is the emphasis and the continuous sliding mode control is used to compare with the non-singular terminal sliding mode control. Meanwhile, an adaptive fuzzy algorithm has been proposed to suppress the chattering phenomenon. Moreover, several numerical examples are presented to demonstrate the efficacy of the proposed controllers by correcting for the external perturbations. Simulation results confirm that the suggested methodologies yield high control precision in control. In addition, actuator degradation, actuator stuck and actuator failure for a period of time are simulated to demonstrate the fault recovery capability of the fault tolerant controllers. The numerical results clearly demonstrate the good performance of the adaptive non-singular terminal control in the event of actuator fault compare with the continuous sliding mode control.