Fault-tolerant Compensation Control Research Articles

Event-Triggered Fault Estimation and Fault Tolerance for Cyber-Physical Systems with False Data Injection Attacks

This paper investigates an event-triggered framework for addressing fault estimation and fault tolerance issues in discrete-time cyber-physical systems (CPSs) with partial state saturations and random false data injection attacks (FDIAs). A stochastic variable is introduced to characterize the random FDIAs and to establish the corresponding model. A reduced-order fault estimator and an event condition are co-derived to reconstruct system states and actuator faults. The proposed event-triggered transmission scheme helps reduce network utilization in the sensor-to-estimator channel. A sufficient condition for the proposed event-triggered estimator is derived, which minimizes state and fault estimation errors even when the controlled plants are subject to exogenous disturbances, fault signals, and random attacks. Furthermore, a fault-tolerant compensation controller is proposed using the estimated states and faults, ensuring that the considered systems achieve mean-squared stability. Finally, a DC motor platform is developed to further demonstrate the effectiveness of the designed estimator-based fault-tolerant controller.

Feasibility Conditions-Free Prescribed Performance Decentralized Fault-Tolerant Neural Control of Constrained Large-Scale Systems

This article investigates the command filter-based decentralized prescribed performance adaptive fault-tolerant compensation control strategy for uncertain nonlinear large-scale systems subject to asymmetric time-varying full-state constraints. Via integrating the performance function with command filter-based backstepping technique, the prescribed performance control problem is addressed, under which the complexity of controller design is reduced. Under the prescribed performance control framework, the nonlinear transformed function is constructed so as to ensure that the asymmetric time-varying full-state constraints free from feasibility conditions imposed on virtual control signals are not violated. Besides, the effect of infinite number of time-varying actuator faults is compensated with the aid of projection adaption design. Furthermore, based on the piecewise Lyapunov function analysis, it is rigorously testified that entire involved signals are bounded, desired constraints are not breached and tracking errors within the predefined domains. Finally, the effective performances of the developed control algorithm are confirmed by some simulation results.

Adaptive neural network state constrained fault-tolerant control for a class of pure-feedback systems with actuator faults

In this paper, an adaptive neural network (NN) constrained fault-tolerant control (FTC) method is proposed for a class of nonlinear pure feedback systems with actuator faults and state constraints. By designing a fault-tolerant compensation controller and a new asymmetric time-varying tangent Barrier Lyapunov function (ATVTBLF), the problem of time-varying asymmetric state constraints caused by actuator failure is solved. The actuator takes into account both loss of effectiveness and bias fault. Different from the existing asymmetric BLF, the new BLF solves the problem of asymmetry under tangent constraints and expands the application range of the asymmetric constraint. NN is used to approximate the unknown items generated in the process of designing fault-tolerant controllers. Based on the Lyapunov stability analysis, it is proved that all signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and all states do not violate the bounds. Finally, the simulation example verifies the effectiveness of the proposed method.

Adaptive neural network–based fault estimation for nonlinear systems with actuator faults in simultaneous multiplicative and additive forms

Non-linearities and actuator faults often exist in practical systems which may degrade system performance or even lead to catastrophic accidents. In this article, a fault-tolerant compensation control strategy is proposed for a class of non-linear systems with actuator faults in simultaneous multiplicative and additive forms. First, radial basis function neural network is employed to approximate the system non-linearity. The approximation is achieved by only one adaptive parameter, which simplifies the computation burden. Then, by means of the backstepping technique, an adaptive neural controller is developed to cope with the adverse effects brought by the system non-linearity and actuator faults in multiplicative and additive forms. Meanwhile, the proposed control design scheme can guarantee that the considered closed-loop system is stable. The novelty of the article lies in that the system non-linearity, the additive actuator faults, and the multiplicative actuator faults that often exist in practical engineering are catered for simultaneously. Furthermore, compared with some existing works, the approximation of the system non-linearity is achieved by only one adaptive parameter for the purpose of reducing the computation burden. Therefore, its applicability is more general. Finally, a numerical simulation and a comparative simulation are carried out to show the effectiveness of the developed controller.

Fault-tolerant model predictive control of six-phase permanent magnet synchronous hub motors

Permanent magnet synchronous hub motors (PMSHMs) have been gradually introduced into the applications of electric vehicles. On this basis, the six-phase motor has the characteristics of high reliability, high power density and low torque ripple. And its fault tolerance is a large advantage compared with the three-phase motor. The multi-phase permanent magnet synchronous motor is redundant due to the number of phases. When the motor fails, it does not have to stop running, merely adjust its control mode and enter the fault-tolerant compensation control algorithm to resume the operation of the system. The FCS-MPC algorithm can replace the cascade structure in the traditional control and eliminate the modulation module. This makes it have good steady-state performance. The speed response is also improved. It can be combined with multiple control objectives with strong flexibility by simply changing the objective function. The prediction model is compensated. Finally, the experimental results show the effectiveness of this method.

Adaptive fuzzy output feedback FTC for nonstrict-feedback systems with sensor faults and dead zone input

This paper solves the fault-tolerant control (FTC) problem of uncertain nonlinear systems in nonstrict-feedback form. The controlled plants considered in this paper are more complicated than existing ones, which is composed of the unknown nonlinearities, unmeasured states, and sensor faults and unknown dead zone input nonlinearity. Fuzzy logic systems and a fault-estimation-based state observer are used for identifying the unknown nonlinearities and obtaining the unmeasured states, respectively. By designing the sensor faults compensation and the dead zone inverse compensation methods, an observer-based fault-tolerant compensation control scheme is developed under backstepping recursive design frame. And it is testified that the closed-loop signals are bounded, and the tracking performance is satisfied even when the controlled systems are not free of sensor faults and unknown dead zone input nonlinearity. An electromechanical system is used to test the effectiveness of the developed control strategy.

Robust Adaptive Fault-Tolerant Tracking Control for Uncertain Linear Systems With Actuator Failures Based on the Closed-Loop Reference Model

This paper addresses the problem of robust adaptive fault-tolerant tracking control for a class of linear systems with parameter uncertainty, external disturbance, and actuator faults including loss of effectiveness, outage, and stuck. According to the online estimation information provided by adaptive mechanism, a fault-tolerant compensation controller is constructed for robust tracking of closed-loop reference model systems. Compared with the existing results, by introducing the closed loop reference model which provides the additional degree-of-freedom, the transient performance of the systems can be improved. It is shown that the signals of the resulting adaptive closed-loop systems are bounded and the tracking error converges to zero asymptotically. A simulation example is provided to verify the effectiveness of the proposed fault-tolerant design method.

Adaptive Fault-Tolerant Compensation Control for T–S Fuzzy Systems With Mismatched Parameter Uncertainties

This paper is concerned with the adaptive fault-tolerant compensation control problem for a class of Takagi–Sugeno (T–S) fuzzy systems with mismatched parameter uncertainties and actuator faults. A matrix transformation technique is introduced to relax the restriction regarding the input matrices of T–S fuzzy systems considered in the existing results. Moreover, by combining backstepping-like technique and adaptive control method, a new adaptive fault-tolerant control scheme with compensation mechanism is proposed to achieve the desirable control performance. In addition, it is proved that the states of the resulting closed-loop fuzzy system converge to zero asymptotically even in the presence of actuator faults and mismatched parameter uncertainties. Finally, two simulation examples are given to verify the effectiveness of the presented control scheme.

Adaptive Fault-Tolerant Compensation Control and Its Application to Nonlinear Suspension Systems

In this paper, an adaptive fault-tolerant method is proposed to synthesize a compensation controller for the uncertain nonlinear pure-feedback systems possessing dead-zone actuators and stochastic failures. Each actuator’s failure mode is described by a scalar Markovian type function, which is not only much more practical in control engineering but also challenging in control theory. By exploring the adaptive backstepping methodology, a compensation scheme for actuator failure is presented to guarantee that the solution of the closed-loop system is a unique and bounded in probability. Importantly, the proposed control method can achieve arbitrarily small tracking error in the presence of nonlinear actuators with random failures. The case study of active suspension system using the adaptive fault-tolerant compensation controller shows the effectiveness of the presented method.

Adaptive Fuzzy Fault-Tolerant Control for Markov Jump Systems With Additive and Multiplicative Actuator Faults

This article proposes a fault-tolerant compensation control approach against nonlinearity, simultaneous additive, and multiplicative actuator faults in Markov jump systems. In this article, we first exploit the fuzzy logic system (FLS) to approximate the nonlinear functions, which have no available knowledge. Then, by utilizing the adaptive backstepping technique, a FLS-based adaptive fault-tolerant compensation controller is proposed, which can completely compensate for the adverse effects, arising from the additive actuator faults, the multiplicative actuator faults, and the mismatched nonlinearity simultaneously. The stability of the closed-loop system can be guaranteed by the proposed FLS-based adaptive controller with the adaptation laws. The novelty of this article lies in the fact that the additive and multiplicative actuator faults, and mismatched nonlinearity are considered simultaneously. Besides, the renown sliding mode control approach has limitations to deal with the FTC problem considered in this article because the considered nonlinearity is a mismatched one. The proposed control approach can cope with the challenging case. Finally, a practical wheeled mobile manipulator system is used to demonstrate the effectiveness and validity of the proposed approach.

Fault-tolerant Compensation Control Based on Sliding Mode Technique of Unmanned Marine Vehicles Subject to Unknown Persistent Ocean Disturbances

This paper is concerned with a robust adaptive fault-tolerant compensation control problem based on sliding mode technique for an unmanned marine vehicle (UMV) with thruster faults and unknown persistent ocean disturbances. A general thruster fault model including partial, total and time-varying stuck is built for the first time. Once the thrusters occur unknown and time-varying stuck faults, the mission of the UMV may be canceled. To avoid it, full-rank decomposition of the thruster configuration matrix is made, based on which a linear sliding surface is constructed and adaptive mechanism is incorporated into sliding mode reaching law. Without the prior knowledge of ocean external disturbances, sliding mode stability is analyzed and a sufficient stability condition through H∞ technique is given. Further the nonlinear unit vector gain of the adaptive sliding mode fault-tolerant compensation controller is designed to ensure the UMV system errors converge to zero independent of fault detection and diagnosis (FDD) mechanism. Finally, the comparison simulation results through a typical floating production ship are shown to testify the feasibility of the presented method.

Auxiliary Fault Tolerant Control With Actuator Amplitude Saturation and Limited Rate

In this paper, the problem of fault tolerant tracking control for a linear time-invariant system subject to actuator faults and saturations is addressed. An auxiliary system is developed to ensure actuators behave within amplitude and rate limits under the influence of partial loss of control effectiveness. Based on the auxiliary system, a fault tolerant compensation controller is constructed to guarantee tracking errors to converge to a small region. Some relationships among tracking errors, command signals, actuator faults, amplitude and rate limits as well as controller parameters are comprehensively studied and explicitly illustrated with formulas. An example of rudder-roll damping control for a cruise keeping ship is included to illustrate the proposed procedures and their effectiveness.

Integral Sliding Mode Fault-Tolerant Control for Uncertain Linear Systems Over Networks With Signals Quantization.

In this paper, a new robust fault-tolerant compensation control method for uncertain linear systems over networks is proposed, where only quantized signals are assumed to be available. This approach is based on the integral sliding mode (ISM) method where two kinds of integral sliding surfaces are constructed. One is the continuous-state-dependent surface with the aim of sliding mode stability analysis and the other is the quantization-state-dependent surface, which is used for ISM controller design. A scheme that combines the adaptive ISM controller and quantization parameter adjustment strategy is then proposed. Through utilizing H∞ control analytical technique, once the system is in the sliding mode, the nature of performing disturbance attenuation and fault tolerance from the initial time can be found without requiring any fault information. Finally, the effectiveness of our proposed ISM control fault-tolerant schemes against quantization errors is demonstrated in the simulation.

Data-Driven Output-Feedback Fault-Tolerant Compensation Control for Digital PID Control Systems With Unknown Dynamics

For digital proportional–integral–derivative control systems with unknown dynamics, the data-driven output-feedback fault-tolerant control (FTC) problem is studied in this paper. In a framework of active FTC, the issue of online recursive identification of the residual generator, the state observer, and the observability canonical form of the plant under consideration is addressed; the problem of reconfiguration of the data-driven fault-tolerant compensation controller with $L_2$ -gain properties is also dealt with by means of the above-obtained results, the prefilter and the Riccati equation related to $H_{\infty }$ control so as to accommodate faults and ensure tracking performance. The resulting fault-tolerant compensation control scheme is designed based on the closed-loop systems, and therefore has more practical significance than the existing FTC methodologies developed in terms of the open-loop systems. Finally, the effectiveness of the proposed FTC approach is validated by the speed control experiment on a dc motor.

Adaptive fault-tolerant control of reentry vehicle considering actuator and sensor faults based on trajectory optimization

Based on the trajectory optimization, this article studies the adaptive fault-tolerant compensation control method for a reentry vehicle with external disturbances and parameter uncertainties. The sensor and actuator faults are both considered including loss of effectiveness, stuck and outage of actuator, and loss of effectiveness of sensor. First, we need to set up the reentry model for the reentry vehicle, use computational fluid dynamics to calculate the heating rate on the surface of the vehicle, divide the vehicle into several isothermal regions appropriately according to the heating rate, and establish the corresponding database for the aerodynamic characteristics. Next, based on the database accomplished, more accurate control variables and flight path can be achieved using the conjugate gradient method, and the aerodynamic heating rate on the surface of the reentry vehicle will be improved considerably. Then, based on the trajectory optimization, an adaptive fault-tolerant compensation control method is introduced to deal with the external disturbances and parameter uncertainties of the reentry vehicle system. And the Lyapunov functional is adopted to guarantee the stability of the system. At last, the effectiveness of such adaptive fault-tolerant control method has been identified by numerous simulation results.

Adaptive fault-tolerant compensation control for Markovian jump systems with mismatched external disturbance

This paper investigates the fault-tolerant control problem for a class of continuous-time Markovian jump systems with actuator faults, nonlinearity and external disturbances. In this study, the exact knowledge for actuator fault and model nonlinearity is totally unknown, and the considered external disturbance contains matched and mismatched part which is more general and widely exists in practical engineering systems. Since sliding mode control exhibits limitations to be employed to stabilize jump systems (Xia et al. 2009) in this paper, an adaptive control scheme with backstepping method is developed to solve this control problem. By on-line estimating the loss of effectiveness of actuators faults and the bounds of Euclidean norm of nonlinearity function, the proposed adaptive backstepping controller can compensate these effects completely, and the stochastic stability of the fault closed-loop system is guaranteed. A numerical example with a wheeled mobile manipulator model is included to verify the effectiveness and show the potential of the proposed new design techniques.

Robust adaptive fault-tolerant control of uncertain linear systems via sliding-mode output feedback

Summary This paper is concerned with the robust adaptive fault-tolerant compensation control problem via sliding-mode output feedback for uncertain linear systems with actuator faults and exogenous disturbances. Mismatched disturbance attenuation is performed via H∞ norm minimization. By incorporating the matrix full-rank factorization technique with sliding surface design successfully, the total failure of certain actuators can be coped with, under the assumption that redundancy is available in the system. Without the need for a fault detection and isolation mechanism, an adaptive sliding mode controller, where the gain of the nonlinear unit vector term is updated automatically to compensate the effects of actuator faults, is designed to guarantee the asymptotic stability and adaptive H∞ performance of closed-loop systems. The effectiveness of the proposed design method is illustrated via a B747-100/200 aircraft model. Copyright © 2014 John Wiley & Sons, Ltd.

Robust fault-tolerant control based on sliding mode method for uncertain linear systems

In this article, a robust adaptive fault-tolerant compensation control problem via sliding mode method is studied for linear systems with actuator faults, disturbances, and parameter uncertainties. Based on a matrix full-rank factorization technique of an input matrix, a new lemma is presented and proved. In terms of this lemma and the information from adaptive mechanism, actuator faults, especially outage of certain actuators, can be compensated for under an actuator redundancy assumption. Without requiring any fault detection and isolation mechanism, a sliding mode fault-tolerant controller is then designed to guarantee the asymptotic stability and disturbance attenuation, where the gain of the nonlinear unit vector term is updated automatically to compensate the effects of actuator faults. Finally, a rocket fairing structural-acoustic model is used to demonstrate the effectiveness of the proposed design method.

Robust fault tolerant control based on sliding mode method for uncertain linear systems with quantization

This paper is concerned with the problem of robust fault-tolerant compensation control problem for uncertain linear systems subject to both state and input signal quantization. By incorporating novel matrix full-rank factorization technique with sliding surface design successfully, the total failure of certain actuators can be coped with, under a special actuator redundancy assumption. In order to compensate for quantization errors, an adjustment range of quantization sensitivity for a dynamic uniform quantizer is given through the flexible choices of design parameters. Comparing with the existing results, the derived inequality condition leads to the fault tolerance ability stronger and much wider scope of applicability. With a static adjustment policy of quantization sensitivity, an adaptive sliding mode controller is then designed to maintain the sliding mode, where the gain of the nonlinear unit vector term is updated automatically to compensate for the effects of actuator faults, quantization errors, exogenous disturbances and parameter uncertainties without the need for a fault detection and isolation (FDI) mechanism. Finally, the effectiveness of the proposed design method is illustrated via a model of a rocket fairing structural-acoustic.

Robust adaptive fault-tolerant control for uncertain linear systems with actuator failures

This study is concerned with the robust adaptive fault-tolerant compensation control problem for linear systems with parameter uncertainty, disturbance and actuator faults including outage, loss of effectiveness and stuck. It is assumed that the lower and upper bounds of actuator efficiency factor, the upper bounds of disturbance and the unparametrisable time-varying stuck fault, are unknown. Then, according to the information from the adaptive mechanism, the effect of actuator fault, exogenous disturbance and parameter uncertainty can be eliminated completely by designing adaptive state feedback controller. Furthermore, it is shown that the solutions of the resulting adaptive closed-loop system are uniformly bounded, the states converge asymptotically to zero. Finally, two examples are given to illustrate the effectiveness and applicability of the proposed design method.