Active fault‐tolerant control for switched systems with time delay

This paper focuses on the problem of active fault‐tolerant control for switched systems with time delay. By utilizing the fault diagnosis observer, an adaptive fault estimate algorithm is proposed, which can estimate the fault signal fast and exactly. Meanwhile, a delay‐dependent criterion is obtained with the purpose of reducing the conservatism of the adaptive observer design. Based on the fault estimation information, an observer‐based fault‐tolerant controller is designed to guarantee the stability of the closed‐loop system. In terms of linear matrix inequality, sufficient conditions are derived for the existence of the adaptive observer and fault‐tolerant controller. Finally, a numerical example is included to illustrate the efficiency of the proposed approach. Copyright © 2011 John Wiley & Sons, Ltd.     

A model reference tracking based on an active fault tolerant control for LPV systems

This work deals with the problem of a model reference tracking based on the design of an active fault tolerant control for linear parameter‐varying systems affected by actuator faults and unknown inputs. Linear parameter‐varying systems are described by a polytopic representation with measurable gain scheduling functions. The main contribution is to design an active fault tolerant controller whose control law is described by an adaptive proportional integral structure. This one requires 3 types of online information, which are reference outputs, measured real outputs, and the fault estimation provided by a model reference, sensors, and an adaptive polytopic observer, respectively. These types of information are used to reconfigure the designed controller, which is able to compensate the fault effects and to make the closed‐loop system able to track reference outputs in spite of the presence of actuator faults and disturbances. The controller and the observer gains are obtained by solving a set of linear matrices inequalities. Performances of the proposed method are compared to another previous method to underline the relevant results.     

Adaptive fault tolerant control against actuator faults

This paper investigates the problem of adaptive fault tolerant control for a class of dynamic systems with unknown un‐modeled actuator faults. The fault model is assumed to be an unknown nonlinear function of control input, not in the traditional form in which the faults can be described as gain and/or bias faults. Using the property of the basic function of neural networks and the implicit function theorem, a novel neural networks‐based fault tolerant controller is designed. Finally, the lateral dynamics of a front‐wheeled steered vehicle is used to demonstrate the efficiency of the proposed design techniques. Copyright © 2016 John Wiley & Sons, Ltd.     

Active fault tolerant control of piecewise affine systems with reference tracking and input constraints

An active fault tolerant control (AFTC) method is proposed for discrete‐time piecewise affine (PWA) systems. Only actuator faults are considered. The AFTC framework contains a supervisory scheme, which selects a suitable controller in a set of controllers such that the stability and an acceptable performance of the faulty system are held. The design of the supervisory scheme is not considered here. The set of controllers is composed of a normal controller for the fault‐free case, an active fault detection and isolation controller for isolation and identification of the faults, and a set of passive fault tolerant controllers (PFTCs) modules designed to be robust against a set of actuator faults. In this research, the piecewise nonlinear model is approximated by a PWA system. The PFTCs are state feedback laws. Each one is robust against a fixed set of actuator faults and is able to track the reference signal while the control inputs are bounded. The PFTC problem is transformed into a feasibility problem of a set of LMIs. The method is applied on a large‐scale live‐stock ventilation model. Copyright © 2013 John Wiley & Sons, Ltd.     

Active fault‐tolerant control for near space vehicles based on reference model adaptive sliding mode scheme

In this paper, an adaptive sliding mode (ASM) scheme is proposed for fault identification and fault‐tolerant control of near space vehicles (NSVs). First, the attitude dynamic model is introduced, and a baseline controller based on reference sliding mode scheme is designed in the case of no faults. Then fault parameterizations with actuator dynamics is presented for several classes of faults: lock‐in‐place, float, hard‐over, and loss of effectiveness. On the basis of adaptive observer design, fault parameters can be accurately estimated on‐line. Furthermore, an ASM fault‐tolerant controller is designed for both cases of actuator dynamic faults and control effector damage. Finally, simulation experiments show that the proposed ASM scheme is able to quickly and accurately identify faults and reconfigure the controller, resulting in excellent overall system performance. Copyright © 2012 John Wiley & Sons, Ltd.     

A new decentralized retrofit adaptive fault‐tolerant flight control design

In this paper, we develop a new decentralized retrofit adaptive fault‐tolerant control design for a class of nonlinear models arising in flight control. The proposed adaptive fault‐tolerant controller is designed to accommodate loss‐of‐effectiveness (LoE) failures in flight control actuators and achieve accurate estimation of failure‐related parameters. The design is based on local estimation of LoE parameters and generation of local retrofit control signals to accommodate the failures. Using state‐dependent closed‐loop estimation errors, we show the overall system to be stable and demonstrate the tracking error to converge to zero asymptotically for any combination of actuator failures. Through computer simulation of F/A‐18 aircraft under actuator LoE failures, the proposed approach is also shown to achieve better parameter estimation performance compared to the fully centralized design and the design employing local observers and a centralized adaptive controller. Copyright © 2012 John Wiley & Sons, Ltd.     

Active fault tolerant control systems by the semi‐Markov model approach

This paper investigates the active fault tolerant control problem via the H _∞ state feedback controller. Because of the limitations of Markov processes, we apply semi‐Markov process in the system modeling. Two random processes are involved in the system: the failure process and the fault detection process. Therefore, two corresponding semi‐Markov processes are integrated in the closed‐loop system model. This framework can generally accommodate different types of system faults, including the randomly happening sensor faults and actuator faults. A controller is designed to guarantee the closed‐loop system stability with a prescribed noise/disturbance attenuation level. The controller can be readily solved by using convex optimization techniques. A vertical take‐off and landing vehicle example with actuation faults is used to demonstrate the effectiveness of the proposed technique. Copyright © 2013 John Wiley & Sons, Ltd.     

基于模糊建模的非线性鲁棒模型预测控制

针对离散不确定模糊模型，提出了一种鲁棒非线性模型预测控制方法，导出了预测性能指标上界，将稳定性约束，输入约束和输出约束变换成容易求解的线性矩阵不等式（LMI）形式，从而将非线性模型预测控制Min-Max优化问题变换成具有线性矩阵不等式约束的广义特征值问题（GEVP）。对于采用的状态反馈预测控制器，讨论了滚动时域优化的可行性，证明了闭环系统的鲁棒稳定性。仿真结果表明了控制器的有效性。     

LMI‐based adaptive output feedback fault‐tolerant controller design for nonlinear systems

This paper presents 2‐novel linear matrix inequality (LMI)‐based adaptive output feedback fault‐tolerant control strategies for the class of nonlinear Lipschitz systems in the presence of bounded matched or mismatched disturbances and simultaneous occurrence of actuator faults, including failure, loss of effectiveness, and stuck. The constructive algorithms based on LMI with creatively using Lyapunov stability theory and without the need for an explicit information about mode of actuator faults or fault detection and isolation mechanism are developed for online tuning of adaptive and fixed output‐feedback gains to stabilize the closed‐loop control system asymptotically. The proposed controllers guarantee to compensate actuator faults effects and to attenuate disturbance effects. The resulting control methods have simpler structure, as compared with most existing recent methods and more suitable for practical systems. The merits of the proposed fault‐tolerant control scheme have been verified by the simulation on nonlinear Boeing 747 lateral motion dynamic model subjected to actuator faults.     

Sensor fault diagnosis and fault‐tolerant control for stochastic distribution time‐delayed control systems

In this paper, a new fault diagnosis and fault‐tolerant control method based on the model equivalent transformation is proposed for the stochastic distribution time‐delayed control system, in which the random delay between the controller and the actuator and the external disturbance is considered. The system is modeled by using a linear B‐spline to approximate the probability density function (PDF) of system output. The original system is transformed into an equivalent system without random delay based on the Laplace transformation method. Then, the equivalent system that is converted to the augmentation system with a new state variable is introduced. The observer is designed to estimate the fault information based on the augmentation system. Observer gain matrices and controller parameters are obtained by solving the linear matrix inequality. The PI control algorithm is used to make the PDF of the system output track the desired distribution. Finally, the validity of the proposed method is verified by computer simulation results.     

Direct design from input/output data of a fault‐tolerant control system based on GIMC structure

This paper deals with a method for the design of a fault‐tolerant control system based on the Generalized Internal Model Control (GIMC) structure, consisting of a standard outer loop feedback controller and an extra inner loop controller. The distinguishing feature of the GIMC structure is that controller design for performance and robustness may be performed separately. The outer loop controller is designed for nominal performance using some controller synthesis to meet the (nominal) control specification, while the inner loop controller is designed to make a trade‐off between robustness and performance. This feature is suitable for fault‐tolerant control. The outer loop controller is designed for the fault‐free case, and the inner loop controller for the fault‐time case. In the conventional methods, the inner loop controller is designed to maximize the robust stability margin without fault information. Therefore, the performance in the fault‐time case tends to become conservative. In this paper, the inner loop controller is directly designed from experimental data collected from the faulty system. Since the collected data contains information on the fault, conservativeness in the conventional methods is decreased. The inner loop controller is designed by Virtual Reference Feedback Timing (VRFT). VRFT is a method of direct design from input‐output data without identifying any models. Since the complexity of the controller can be specified by the designer, no complexity reduction is necessarily required, which is advantageous in implementation. The effectiveness of the proposed design method is confirmed by an experiment. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(4): 53–62, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20929     

单元机组负荷非线性预测控制及其仿真研究

大型单元机组负荷控制系统存在着强耦合、非线性等特性,常规线性控制策略难取得满意的控制效果。为此,该文提出了一种新的基于模糊模型和免疫优化的非线性预测控制方法,将离线辨识到的全局模糊模型作为预测模型,然后利用实数编码的免疫优化算法在线实现非线性预测控制的滚动优化,给出每个采样时刻的最优控制量。该方法还可通过修正的遗传算子方便地解决控制量受限问题。通过对一个500MW单元机组负荷控制系统的仿真试验,验证了该非线性预测控制方法的有效性。     

Robust economic model predictive control of nonlinear networked control systems with communication delays

In this work, we consider economic model predictive control of nonlinear networked control systems subject to external disturbances and communication delays in both sensor-to-controller and controller-to-actuator channels. The problem is addressed in the framework of the min-max model predictive control. First, a delay compensation strategy is proposed to minimize the impact of communication delays on the control performance. In the compensation strategy, once the receiver at the controller node receives a new state measurement, the controller generates a control sequence and sends the sequence to the actuator to compensate for delayed control inputs. Subsequently, the presence of disturbance is explicitly considered for robustness and the semi-feedback min-max optimization algorithm is used to design the control law based on the estimate of the current state reconstructed by the estimator. Furthermore, the input-to-state practical stability of the proposed approach is established by constructing a modified Lyapunov function. Simulation results of a numerical example and a chemical process example demonstrate the applicability and effectiveness of our approach.     

Adaptive neural control for nonstrict‐feedback stochastic nonlinear time‐delay systems with input and output constraints

This paper investigates an adaptive neural tracking control for a class of nonstrict‐feedback stochastic nonlinear time‐delay systems with input saturation and output constraint. First, the Gaussian error function is used to represent a continuous differentiable asymmetric saturation model. Second, the appropriate Lyapunov‐Krasovskii functional and the property of hyperbolic tangent functions are used to compensate the time‐delay effects, the neural network is used to approximate the unknown nonlinearities, and a barrier Lyapunov function is designed to ensure that the output parameters are restricted. At last, based on Lyapunov stability theory, a robust adaptive neural control method is proposed, and the designed controller decreases the number of learning parameters and thus reduces the computational burden. It is shown that the designed neural controller can ensure that all the signals in the closed‐loop system are 4‐Moment (or 2 Moment) semi‐globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of the origin. Two examples are given to further verify the effectiveness of the proposed approach.     

Compensation of performance degradation caused by fault based on GIMC structure: Application to a redundant sensor fault of flexible arm

In recent years, control system reliability has received much attention with an increase of situations where computer‐controlled systems such as robot control systems are used. In order to improve reliability, control systems need to have abilities to detect a fault (fault detection) and maintain the stability and the control performance (fault tolerance). This paper deals with the strain gauge sensor fault of a flexible arm robot. In order to achieve a fault‐tolerant control system, the effect of the fault is identified as dual Youla parameter by regarding the estimation error of the faulty sensor signal as the faulty plant output. Moreover, Youla parameter is designed so as to suppress the effect of dual Youla parameter. Youla parameter is implemented in GIMC (Generalized Internal Model Control) structure proposed by Zhou. Since GIMC structure includes a conditional feedback, it is suitable for achieving a fault‐tolerant control system. The effectiveness of the proposed fault‐tolerant control system is confirmed by experiments. © 2009 Wiley Periodicals, Inc. Electr Eng Jpn, 168(3): 48–58, 2009; Published online in Wiley InterScience ( www. interscience.wiley.com ). DOI 10.1002/eej.20830     

Active fault‐tolerant attitude control for flexible spacecraft with loss of actuator effectiveness

A theoretical framework for active fault‐tolerant attitude stabilization control is developed and applied to flexible spacecraft. The proposed scheme solves a difficult problem of fault‐tolerant controller design in the presence of severe partial loss of actuator effectiveness faults and external disturbances. This is accomplished by developing an observer‐based fault detection and diagnosis mechanism to reconstruct the actuator faults. Accordingly, a backstepping‐based fault‐tolerant control law is reconfigured using the reconstructed fault information. It is shown that the proposed design approach guarantees that all of the signals of the closed‐loop system are uniformly ultimately bounded. The closed‐loop performance of the proposed control strategy is evaluated extensively through numerical simulations. Copyright © 2012 John Wiley & Sons, Ltd.     

基于复合模型预测控制策略的三电平APF研究

电力有源滤波器(Active power filter,APF)是消除电网中非线性负载产生的电流谐波的有效手段之一。提出一种三相静止坐标下的基于模型预测控制复合控制器,复合控制器由改进的自适应广义积分器和模型预测控制两部分组成。该复合控制策略有效地整合了预测控制和自适应广义积分器的优点,在最大限度利用模型预测进行谐波电流快速跟踪的同时,采取自适应广义积分器对各次谐波进行无静差跟踪控制。所提出的复合控制器与三电平电压空间矢量调相结合,能够消除单独预测控制交流变量时所存在的稳态误差问题和改善系统鲁棒性。详细研究了复合控制器的设计方法,并给出了系统的参数设计和稳定性分析。最后通过实验验证了控制方法的正确性和有效性。     

Robust adaptive active fault‐tolerant control of UAH with unknown disturbances and actuator faults

This paper proposes a robust active fault‐tolerant control (AFTC) approach for medium‐scale unmanned autonomous helicopter (UAH) with rotor flapping dynamics in the presence of unknown external disturbances and actuator faults. The robust items are adopted to improve the disturbance rejection capability of the UAH system. The adaptive fault observers are developed to estimate the fault parameters and the fault detection (FD) algorithms are presented to detect the actuator faults in different loops. In order to obtain satisfactory trajectory tracking performance, a backstepping‐based robust AFTC scheme is designed for the simplified 6‐degree‐of‐freedom (DOF) UAH nonlinear dynamics model and the global stability of the closed‐loop system is proved by using the Lyapunov method. Several groups of numerical simulation results are carried out to verify the effectiveness of the developed method.     

Comparisons of adaptive fault‐tolerant insensitive control methods for a class of linear systems

In this paper, the problem of fault‐tolerant insensitive control is addressed for a class of linear time‐invariant continuous‐time systems against bounded time‐varying actuator faults and controller gain variations. Adaptive mechanisms are developed to adjust controller gains in order to compensate for the detrimental effects of partial loss of control effectiveness and bias‐actuator faults. Variations of controller gains arise from time‐varying and bounded perturbations that are supposed to always exist in adaptive mechanisms. Based on the disturbed outputs of adaptive mechanisms, three different adaptive control strategies are constructed to achieve bounded stability results of the closed‐loop adaptive fault‐tolerant control systems in the presence of actuator faults and controller gain variations. Furthermore, comparisons of convergence boundaries of states and limits of control inputs among adaptive strategies are developed in this paper. The efficiency of the proposed adaptive control strategies and their comparisons are demonstrated by a rocket fairing structural‐acoustic model.     

Composite learning fuzzy synchronization for incommensurate fractional‐order chaotic systems with time‐varying delays

This paper presents a composite learning fuzzy control to synchronize two different uncertain incommensurate fractional‐order time‐varying delayed chaotic systems with unknown external disturbances and mismatched parametric uncertainties via the Takagi‐Sugeno fuzzy method. An adaptive controller together with fractional‐order composite learning laws is designed based on both a parallel distributed compensation technology and a fractional Lyapunov criterion. The boundedness of all variables in the closed‐loop system and the Mittag‐Leffler stability of tracking error can be guaranteed. T‐S fuzzy systems are provided to tackle unknown nonlinear functions. The distinctive features of the proposed approach consist in the following: (1) a supervisory control law is designed to compensate the lumped disturbances; (2) both the prediction error and the tracking error are used to estimate the unknown fuzzy system parameters; (3) parameter convergence can be ensured by an interval excitation condition. Finally, the feasibility of the proposed control strategy is demonstrated throughout an illustrative example.