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     

Fault‐tolerant control of linear multivariable controllers using iterative feedback tuning

This paper introduces the iterative feedback tuning (IFT) into a Youla parameterization scheme for fault‐tolerant control. By off‐line IFT‐experiments of tuning Youla parameters, the proposed algorithm deals with a number of conditional failures that are described by the dual Youla parameter. The main contribution of this paper is to show how Youla scheme‐based IFT can be constructed for multivariable linear time‐invariant systems. Particular attention is given to the issue of the structure of the Youla parameter (filter), in which both finite impulse response and infinite impulse response filters are presented and compared. As an illustration, the method is applied to a simulation model of a continuous stirred tank heater system. Copyright © 2014 John Wiley & Sons, Ltd.     

Adaptive fault tolerant control for a class of multi‐input multi‐output nonlinear systems with both sensor and actuator faults

Compared with the fault diagnosis, detection, and isolation literature, very few results are available to discuss control algorithms directly for multi‐input multi‐output nonlinear systems with both sensor and actuator faults in the fault tolerant control literature. In this work, we present a fault tolerant control algorithm to address the system output stabilization problem for a class of multi‐input multi‐output nonlinear systems with both parametric and nonparametric uncertainties, subject to sensor and actuator faults that can be both multiplicative and additive. All elements of the sensor measurements and actuator components can be faulty. Besides, the control input gain function is not fully known. Backstepping method is used in the analysis and control design. We show that under the proposed control scheme, uniformly ultimate boundedness of the system output is guaranteed, while all closed‐loop system signals stay bounded. In the cases where the sensor faults are only multiplicative, exponential convergence of the system state variables into small neighbourhoods around zero is guaranteed. An illustrative example on a robot manipulator model is presented in the end to further demonstrate the effectiveness of the proposed control scheme.     

Integration of multiple model based fault detection and nonlinear model predictive fault‐tolerant control

In this paper, we present a new fault‐tolerant control system for a class of nonlinear systems with input constraints. Because of many important factors that stabilize a nonlinear model predictive controller, it can be used as a powerful controller in the event of fault occurrence. So, the reconfigurable controller is designed based on the quasi‐infinite model predictive control (QIMPC) approach as a fault‐tolerant approach. On the other hand, a fault detection and diagnosis (FDD) system is designed based on the multiple model method. The bank of extended Kalman filters (EKFs) is used to detect the predefined actuator fault and estimate the unknown parameters of a fault. When a fault is detected, the proposed FDD information is used to correct the model of the faulty system recursively and reconfigure the controller. Delay on FDD decision may lead to performance degradation or even instability for some systems. The timely proposed FDD approach will preserve stability. Moreover, a framework is presented to ensure stability when a fault occurs. The effectiveness of this method is demonstrated, in comparison with conventional nonlinear model predictive control, by two practical examples. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Sensor network design for fault tolerant estimation

This paper addresses the problem of fault tolerant estimation and the design of fault tolerant sensor networks. Fault tolerance is defined with respect to a given estimation objective, namely a given functional of the system state should remain observable when sensor failures occur. Redundant and minimal sensor sets are defined and organized into an automaton which contains all the subsets of sensors such that the estimation objective can be achieved. Three criteria, which evaluate the system fault tolerance with respect to sensor failures when a reconfiguration strategy is used, are introduced: (strong and weak) redundancy degrees (RD), sensor network reliability (R), and mean time to non‐observability (MTTNO). Sensor networks are designed by finding redundant sensor sets whose RD and/or R and/or MTTNO are larger than some specified values. A ship boiler example is developed for illustration. Copyright © 2004 John Wiley & Sons, Ltd.     

Detector design for active fault diagnosis in closed‐loop systems

Fault diagnosis of closed‐loop systems is extremely relevant for high‐precision equipment and safety critical systems. Fault diagnosis is usually divided into 2 schemes: active and passive fault diagnosis. Recent studies have highlighted some advantages of active fault diagnosis based on dual Youla‐Jabr‐Bongiorno‐Kucera parameters. In this paper, a method for closed‐loop active fault diagnosis based on statistical detectors is given using dual Youla‐Jabr‐Bongiorno‐Kucera parameters. The goal of this paper is 2‐fold. First, the authors introduce a method for measuring a residual signal subject to white noise. Second, an optimal detector design is presented for single and multiple faults using the amplitude and phase shift of the residual signal to conduct diagnosis. Here, both the optimal case of a perfect model and the suboptimal case of a model with uncertainties are discussed. The method is successfully tested on a simulated system with parametric faults.     

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.     

Less conservative criteria for fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer

This paper studies the problem of fault accommodation of time‐varying delay systems using adaptive fault diagnosis observer. Based on the proposed fast adaptive fault estimation (FAFE) algorithm using only a measured output, a delay‐dependent criteria is first established to reduce the conservatism of the design procedure, and the FAFE algorithm can enhance the performance of fault estimation. On the basis of fault estimation, the observer‐based fault‐tolerant tracking control is then designed to guarantee tracking performance of the closed‐loop systems. Furthermore, comprehensive analysis is presented to discuss the calculation steps using linear matrix inequality technique. Finally, simulation results of a stirred tank reactor model are presented to illustrate the efficiency of the proposed techniques. Copyright © 2009 John Wiley & Sons, Ltd.     

Simultaneous time‐varying actuator and sensor fault reconstruction based on PI observer for LPV systems

We consider problems of actuator and sensor fault reconstruction simultaneously for linear parameter varying systems expressed in polytopic forms. By extending the sensor fault as an auxiliary state, a polytopic unknown input proportional‐integral observer in which the actuator fault signals are assumed to be time varying is developed to estimate the system states and the actuator and sensor fault at the same time. The existence conditions of the observer are derived in terms of linear matrix inequalities that can be readily handled via some efficient tools. An example is given to demonstrate the advantages of the proposed method in comparison to the existing results. Copyright © 2014 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.     

Two‐stage Kalman filter‐based actuator/surface fault identification and reconfigurable control applied to F‐16 fighter dynamics

In this study, an active fault‐tolerant control technique with reconfiguration against actuator/surface failures is presented. A two‐stage Kalman filter is designed in order to identify the control distribution matrix elements that correspond to the faulty actuator/surface; thus, the control reconfiguration is carried out using this identified control distribution matrix. The actuator/surface fault identification problem is solved through two jointly operating Kalman filters: the first one is for the estimation of the control distribution matrix elements that correspond to the faulty actuator/surface, and the second one is for the estimation of the state variables of the aircraft model. A structure for the active fault‐tolerant aircraft flight control system with reconfiguration against actuator/surface failures is presented. A control reconfiguration action is taken in order to keep the performance of the impaired aircraft the same as that of the unimpaired aircraft. In simulations, the nonlinear flight dynamics of an AFTI/F‐16 fighter model is considered, and the performance of the proposed actuator/surface failure identification and reconfigurable control schemes are examined for this model. Copyright © 2012 John Wiley & Sons, Ltd.     

Soft‐fault diagnostic method based on locus circle of steady‐state node‐voltage vector

This study describes a relationship between an element parameter and a fault feature steady‐state node‐voltage vector (SSNVV). The locus of the SSNVV endpoints is proposed and proven to be an arc of circle under certain conditions, whereas the element parameter varies from small to large within a certain range. The arc of circle is called locus circle of SSNVV (LCoSSNVV). An LCoSSNVV‐based soft‐fault diagnostic method is also proposed. The method utilizes three discrete SSNVV endpoints to draw an LCoSSNVV for each element and collects all LCoSSNVVs to produce an LCoSSNVV set for fault diagnosis. In the following diagnostic process, the method measures a fault feature SSNVV of actual faulty circuit and judges which element is faulty on the basis of the relationship between the measured fault feature SSNVV and the LCoSSNVVs in an LCoSSNVV set. Subsequently, the fault can be further subdivided into different types of soft faults on the basis of the relative position of the SSNVV on the LCoSSNVV. A range of the faulty element parameter value can be estimated. Several examples illustrate the method. A measurement solution of SSNVV and a solution of a programming strategy are described. The new LCoSSNVV‐based method would effectively improve the soft‐fault diagnosis process of a linear time‐invariant circuit network. Copyright © 2015 John Wiley & Sons, Ltd.     

Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques

This paper aims at the blade root moment sensor fault detection and isolation issue for three‐bladed wind turbines with horizontal axis. The underlying problem is crucial to the successful application of the individual pitch control system, which plays a key role for reducing the blade loads of large offshore wind turbines. In this paper, a wind turbine model is built based on the closed loop identification technique, where the wind dynamics is included. The fault detection issue is investigated based on the residuals generated by dual Kalman filters. Both additive faults and multiplicative faults are considered in this paper. For the additive fault case, the mean value change detection of the residuals and the generalized likelihood ratio test are utilized respectively. For multiplicative faults, they are handled via the variance change detection of the residuals. The fault isolation issue is proceeded with the help of dual sensor redundancy. Simulation results show that the proposed approach can be successfully applied to the underlying issue. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

Fault estimation and accommodation for networked control systems with nonuniform sampling periods

This paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous‐time fault and system states by using nonuniformly discrete‐time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled‐data fault tolerant control law is designed to preserve the stability of the closed‐loop system. The proposed scheme can not only guarantee the impact of continuous‐time uncertainties and discrete‐time sampled estimation errors on the faulty system to satisfy a H _∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous‐time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

单相脉宽调制整流器传感器故障诊断与容错控制

单相脉宽调制(PWM)整流器通常采用网侧电流与直流侧电压双闭环控制系统结构,一旦其检测系统中的传感器发生故障,将导致反馈值出现偏差,影响系统的控制效果与运行安全。设计一种准确可靠的单相PWM整流器网侧电流与直流侧电压传感器故障诊断与容错控制方案。采用解析冗余的方法实现故障诊断,基于单、双极性两种调制方法的开关函数取值设计了系统滑模观测器与状态估计器;将传感器采集值与观测器估计值作差并归一化建立系统残差,故障诊断单元通过比较残差与阈值定位故障传感器并迅速采取容错控制策略,以观测器的估计值代替故障传感器的测量值实现控制系统重构。通过仿真与实验模拟了三种传感器故障,验证了所提出故障诊断与容错控制方案的有效性与可靠性。     

Experimental investigation of a speed‐sensor‐less IM drive system under Inverter fault‐tolerant control

This paper proposes an algorithm for fault tolerance of three‐phase, inverter‐fed, speed‐sensor‐less control of a three‐phase induction motor drive system. The fault tolerance of the inverter when one switch is open or one leg of six‐switch inverter is lost is considered. The control of the drive system is based on indirect rotor field‐oriented control theory. Also, the speed estimator is based on model reference adaptive system (using stator current and rotor flux as state variables for estimating the speed). The fault‐tolerant algorithm is able to adaptively change over from a six‐switch inverter to a four‐switch inverter topology when a fault occurs; also, it makes a smooth transition of the motor speed, torque, and current when changing over from a faulty condition to a new healthy status, which is four‐switch three‐phase inverter (FSTPI) topology; thus, the six‐switch three‐phase inverter (SSTPI) topology (pre‐fault status) is almost retained for the medium‐power range of induction motor applications. The proposed algorithm is simulated by using the MATLAB/SIMULINK package. Also, the proposed control system is tested experimentally using a digital signal processor (DSP1104). The obtained results from the simulation model and experimental system demonstrate the performance enhancement and good validity of the fault‐tolerance control for the speed‐sensor‐less induction motor drive system. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

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.     

A novel method for SLG fault location in power distribution system using time lag of travelling wave components

This paper presents an approach to single line‐to‐ground fault location in a power distribution system based on the time lag of different modal components . It is a single‐ended method applicable to unsynchronized measurements. The fault location formulation is derived by analyzing the traveling wave propagation characteristic in a distributed parameter model. To tackle the key problem of ground‐mode velocity estimation, an iterative velocity method based on prior knowledge is first proposed. Since the practical measurements are not ideal because of sensor accuracy and nonequivalent transient response, fuzzy neural network is utilized to process traveling wave data acquired at multiple measurements to get an error‐tolerant effect. Furthermore, electromagnetic transient simulations for a 34‐bus test feeder system under various conditions of fault resistances, inception angles, and distributed generator access reveal the robust estimation of fault location. The performance of the proposed method is also validated by simulations with noisy and noise‐free measurements. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

某型航空发动机容错控制仿真研究

利用卡尔曼滤波器的优点,提出了航空发动机容错控制模型,它的核心部分就是卡尔曼滤波器,考虑了当某一传感器发生故障后,利用一簇卡尔曼滤波器对发生故障的传感器进行诊断并隔离,并依据剩余非故障传感器的信息对自适应模型进行重构。实例仿真表明航空发动机容错控制系统可以保证航空发动机在一定的性能指标下稳定运行,达到了容错控制的目的。