Fault tolerant control using a fuzzy predictive approach

This paper proposes the application of fault-tolerant control (FTC) using fuzzy predictive control. The FTC approach is based on two steps, fault detection and isolation (FDI) and fault accommodation. The fault detection is performed by a model-based approach using fuzzy modeling and fault isolation uses a fuzzy decision making approach. The information obtained on the FDI step is used to select the model to be used in fault accommodation, in a model predictive control (MPC) scheme. The fault accommodation is performed with one fuzzy model for each identified fault. The FTC scheme is used to accommodate the faults of two systems a container gantry crane and three tank benchmark system. The fuzzy FTC scheme proposed in this paper was able to detect, isolate and accommodate correctly the considered faults of both systems.     

Fault-tolerant control systems design via subdivision of parameter region

This paper presents a linear matrix inequality （LMI） approach to solve the fault-tolerant control （FTC） problem of actuator faults. The range of actuator faults is considered as a parameter region and subdivided into several subregions to achieve a certain desired performance specification. Based on the integral quadratic constraint （IQC） approach, a passive fault-tolerant controller for the whole fault region and multiple fault-tolerant controllers for each fault subregion are designed for guaranteeing stability and improving performance of the FTC system, respectively. According to the estimation of parameters by FDI process, the corresponding subregion controller is chosen for the stability and optimal performance of closed-loop systems when the fault occurs. The case of incorrect estimation is also considered by comparing the performance index between the switched controller and the passive fault-tolerant controller. The proposed design technique is finally evaluated in the light of a simulation example.     

Novel MPC‐Based Fault Tolerant Tracking Control Against Sensor Faults

The problem of active fault‐tolerant tracking control with control input and system output constraints is studied for a class of discrete‐time systems subject to sensor faults. A time‐varying fault‐tolerant observer is first developed to estimate the real system state from the faulty sensor output and control input signals. Then by using the estimated state at each time step, a model predictive control (MPC)‐based fault‐tolerant tracking control scheme is presented to guarantee the desired tracking performance and the given input and output constraints on the faulty system. In comparison with many existing fault‐tolerant MPC methods, its main contribution is that the proposed state estimator is designed by the simple and online numerical computation to tolerate the possible sensor faults, so that the regular MPC algorithm without fault information can be adopted for the online calculation of fault‐tolerant control signal. The potential recursive infeasibility and computational complexity due to the faults are avoided in the scheme. Additionally, the closed‐loop stability of the post‐fault system is discussed. Simulative results of an electric throttle control system verify the effectiveness of the proposed method.     

A fault-tolerant control strategy for non-linear discrete-time systems: application to the twin-rotor system

In this paper, an active fault-tolerant control scheme is proposed in the case of actuator faults. In particular, the general idea of integrating fault identification and control schemes, which takes into account the fault estimation error is first presented in a linear context. As a result, the so-called separation principle for the controller and the fault identification scheme is developed. Subsequently, the proposed approach is extended to a class of non-linear systems. Similarly to the linear case, it is proven that using a suitable control strategy and a faulty identification scheme it is possible to obtain an integrated fault-tolerant control framework, which takes into account the fault identification error. As a result, a non-linear counterpart of the above-mentioned separation principle is developed. Finally, the last part of the paper shows the application results obtained using a twin-rotor system that confirm the high performance of the proposed approach.     

Sensor‐fault tolerance using robust MPC with set‐based state estimation and active fault isolation

In this paper, a sensor fault‐tolerant control scheme using robust model predictive control (MPC) and set‐theoretic fault detection and isolation (FDI) is proposed. The robust MPC controller is used to control the plant in the presence of process disturbances and measurement noises while implementing a mechanism to tolerate faults. In the proposed scheme, fault detection (FD) is passive based on interval observers, while fault isolation (FI) is active by means of MPC and set manipulations. The basic idea is that for a healthy or faulty mode, one can construct the corresponding output set. The size and location of the output set can be manipulated by adjusting the size and center of the set of plant inputs. Furthermore, the inputs can be adjusted on‐line by changing the input‐constraint set of the MPC controller. In this way, one can design an input set able to separate all output sets corresponding to all considered healthy and faulty modes from each other. Consequently, all the considered healthy and faulty modes can be isolated after detecting a mode changing while preserving feasibility of MPC controller. As a case study, an electric circuit is used to illustrate the effectiveness of the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Fault diagnosis and accommodation of nonlinear systems based on multiple-model adaptive unscented Kalman filter and switched MPC and H-infinity loop-shaping controller

In this paper, a new active fault tolerant control (AFTC) methodology is proposed based on a state estimation scheme for fault detection and identification (FDI) to deal with the potential problems due to possible fault scenarios. A bank of adaptive unscented Kalman filters (AUKFs) is used as a core of FDI module. The AUKF approach alleviates the inflexibility of the conventional UKF due to constant covariance set up, leading to probable divergence. A fuzzy-based decision making (FDM) algorithm is introduced to diagnose sensor and/or actuator faults. The proposed FDI approach is utilized to recursively correct the measurement vector and the model used for both state estimation and output prediction in a model predictive control (MPC) formulation. Robustness of the proposed FTC system, H_∞ optimal robust controller and MPC are combined via a fuzzy switch that is used for switching between MPC and robust controller such that FTC system is able to maintain the offset free behavior in the face of abrupt changes in model parameters and unmeasured disturbances. This methodology is applied on benchmark three-tank system; the proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated leading to an offset free behavior in the presence of sensor/actuator faults that can be either abrupt or drift change in biases. Analysis of the simulation results reveals that the proposed approach provides an effective method for treating faults (biases/drifts in sensors/actuators, changes in model parameters and unmeasured disturbances) under the unified framework of robust fault tolerant control.     

基于迭代学习观测器的航天器姿态主动容错控制

针对含有外部扰动和执行器故障的一类航天器姿态控制系统,本文提出基于迭代学习观测器的主动容错控制方案.首先,建立了含有外部扰动和执行器故障的航天器姿态控制系统的运动学和动力学模型.其次,为了提高观测器的故障估计精度,在传统迭代学习观测器设计基础上引入上一时刻状态估计误差信息,文章提出一种改进型学习估计算法.进一步,基于滑模控制和指定时间稳定理论,利用学习观测器的故障估计信息设计指定时间主动容错控制器.与现有的航天器主动容错控制方案相比,本文所提出的算法的优势在于可以使故障系统的姿态能在指定时间跟踪上指令信号.基于Lyapunov方法,本文从理论上证明了改进型学习观测器和姿态容错控制系统的稳定性.最后,通过数值仿真,说明了所提容错控制方案的有效性和可行性.     

双时滞系统的故障诊断和动态最优容错控制

对含有状态时滞和控制时滞的线性时滞系统, 研究系统发生不可直接测量的传感器故障和执行故障时的故障诊断和最优容错控制问题. 首先基于时滞系统的线性变换, 利用Riccati矩阵方程和Sylvester方程设计了故障情况下的最优容错控制律, 并证明了最优容错控制律的存在唯一性. 然后通过构造一种新的含有故障的增广系统的降维状态观测器, 实现了故障的实时在线诊断和系统状态的观测, 解决了最优容错控制的物理不可实现问题. 最后利用故障诊断的结果给出了物理可实现的动态最优容错控制律. 仿真实例验证了故障诊断方法和动态最优容错控制方法的可行性和有效性.     

Fault tolerant control for a dearomatisation process

In this paper, a fault tolerant control (FTC) for a dearomatisation process in the presence of faults in online product quality analysers is presented. The FTC consists of a fault detection system (FDI) and a logic for triggering predefined FTC actions. FDI is achieved by combining several process data driven approaches for detecting faults in online quality analysers. The FTC exploits the diagnostic information in adapting a quality controller (MPC) to the faulty situation by manipulating tuning parameters of the MPC to produce both proactive and reactive strategies. The proposed FTC was implemented, tested offline and validated onsite at the Naantali oil refinery. The successful testing and plant validation results are presented and discussed.     

Robust actuator fault isolation and management in constrained uncertain parabolic PDE systems

This paper presents a methodology for the design of an integrated robust fault detection and isolation (FDI) and fault-tolerant control (FTC) architecture for distributed parameter systems modeled by nonlinear parabolic Partial Differential Equations (PDEs) with time-varying uncertain variables, actuator constraints and faults. The design is based on an approximate finite-dimensional system that captures the dominant dynamics of the PDE system. Initially, an invertible coordinate transformation-obtained through judicious actuator placement-is used to transform the approximate system into a form where the evolution of each state is excited directly by only one actuator. For each state, a robustly stabilizing bounded feedback controller that achieves an arbitrary degree of asymptotic attenuation of the effect of uncertainty is then synthesized and its constrained stability region is explicitly characterized in terms of the constraints, the actuator locations and the size of the uncertainty. A key idea in the controller synthesis is to shape the fault-free closed-loop response of each state in a prescribed fashion that facilitates the derivation of (1) dedicated FDI residuals and thresholds for each actuator, and (2) an explicit characterization of the state-space regions where FDI can be performed under uncertainty and constraints. A switching law is then derived to orchestrate actuator reconfiguration in a way that preserves robust closed-loop stability following FDI. Precise FDI rules and control reconfiguration criteria that account for model reduction errors are derived for the implementation of the FDI-FTC structure on the distributed parameter system. Finally, the results are demonstrated using a tubular reactor example.     

Fault-tolerant control of nonlinear system

The design strategies of fault-tolerant control system (FTCS) are developed, which are categorized into two types: redundant design and fault compensation. In the first type, a certain degree of redundancy is introduced to controller. The resulting closed-loop system is stable not only when all actuators are operational but also only when one actuator experiences fault. In the second type, the online fault-tolerant control (FTC) scheme is developed based on the fuzzy logic system. The closed-loop stability is established based on Lyapunov’s sense. The resulting closed-loop system is stable by using the corrective control law. Compared with the existing results, the fault is accommodated by the fault compensator. The updating control law is so derived that all the parameters of the closed-loop system are bounded. The advantage of redundant design is that it is unnecessary to know the position and magnitude of the fault and is performed without FDI, which reduce the computing time and avoid the false alarms, non-detection and delay due to FDI. The advantage of fault compensation is the dynamics caused by faults that can be accommodated online. Examples of the proposed design indicate that the approaches are effective.     

Fault tolerant control using virtual actuators and set‐separation detection principles

In this paper we combine a set‐separation approach to fault detection and identification (FDI), recently proposed by the authors, with the virtual actuator approach to controller reconfiguration of Steffen and Lunze. The FDI approach is based on the separation of sets that characterize the system operation under different actuator fault situations that can occur in the plant. The derivation of these sets takes into account the closed‐loop system reconfigured by means of the virtual actuator under all considered actuator faults. Analytic conditions in terms of closed‐loop system parameters and bounds on external signals can be deduced from the required set separation which, in turn, guarantees closed‐loop stability, setpoint tracking, and optimal performance properties of the scheme under all considered fault situations. Thus, the main contribution of this paper is twofold. First, it provides an integrated strategy for fault tolerant control by adapting two existing techniques for FDI and for controller reconfiguration to work in combined form. Second, and more importantly, it endows the resulting combined scheme with guaranteed closed‐loop stability, setpoint tracking and optimal performance properties under actuator faults and in the presence of disturbances. Copyright © 2011 John Wiley & Sons, Ltd.     

Integrated design of fault reconstruction and fault-tolerant control against actuator faults using learning observers

This paper addresses the problem of integrated fault reconstruction and fault-tolerant control in linear systems subject to actuator faults via learning observers (LOs). A reconfigurable fault-tolerant controller is designed based on the constructed LO to compensate for the influence of actuator faults by stabilising the closed-loop system. An integrated design of the proposed LO and the fault-tolerant controller is explored such that their performance can be simultaneously considered and their coupling problem can be effectively solved. In addition, such an integrated design is formulated in terms of linear matrix inequalities (LMIs) that can be conveniently solved in a unified framework using LMI optimisation technique. At last, simulation studies on a micro-satellite attitude control system are provided to verify the effectiveness of the proposed approach.     

Fault Accommodation for a Class of Nonlinear Uncertain Systems With Event-Triggered Input

The event-triggered fault accommodation problem for a class of nonlinear uncertain systems is considered in this paper.The control signal transmission from the controller to the system is determined by an event-triggering scheme with relative and constant triggering thresholds.Considering the event-induced control input error and system fault threat,a novel eventtriggered active fault accommodation scheme is designed,which consists of an event-triggered nominal controller for the time period before detecting the occurrence of faults and an adaptive approximation based event-triggered fault accommodation scheme for handling the unknown faults after detecting the occurrence of faults.The closed-loop stability and inter-event time of the proposed fault accommodation scheme are rigorously analyzed.Special cases for the fault accommodation design under constant triggering threshold are also derived.An example is employed to illustrate the effectiveness of the proposed fault accommodation scheme.     

Fault tolerant sliding mode control for T-S fuzzy stochastic time-delay system via a novel sliding mode observer approach

In this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.     

Cascade filter structure for sensor/actuator fault detection and isolation of satellite attitude control system

This paper presents a new scheme for fault detection and isolation in a satellite system. The purpose of this paper is to develop detection, isolation and identification algorithms based on a cascade filter for both total and partial faults in a satellite attitude control system (ACS). The cascade filter consists of a decentralized Kalman filter (DKF) and a bank of interacting multiple model (IMM) filters. The cascade filter is utilized for detection and diagnosis of anticipated sensor and actuator faults in a satellite ACS. Other fault detection and isolation (FDI) schemes are compared with the proposed FDI scheme. The FDI procedure using a cascade filter was developed in three stages. In the first stage, two local filters and a master filter detect sensor faults. In the second stage, the FDI scheme checks sensor residuals to isolate sensor faults, and 11 Extended Kalman filters with actuator fault models detect wherever actuator faults occur. In the third stage of the FDI scheme, four filters identify the fault type, which is either a total or partial fault. An important feature of the proposed FDI scheme is that it can decrease fault isolation time and accomplish not only fault detection and isolation but also fault type identification using a scalar penalty in the conditional density function.     

四旋翼无人机时延模糊自抗扰容错控制

针对四旋翼无人机系统执行器故障问题，为改善飞行控制系统性能，提出一种时延模糊自抗扰容错控制。首先，根据四旋翼无人机系统非线性数学模型和执行器故障模型，选择模糊自抗扰控制器作为基准控制器，在未发生执行器故障的情况下，使飞行控制系统保持稳定；其次，在发生执行器故障的情况下，利用时延控制技术估计故障信息，并与模糊自抗扰控制相结合，实现容错控制；最后，对所研究的容错控制算法进行数值仿真分析，仿真结果表明：把时延控制与模糊自抗扰控制相结合，能有效调节执行器故障，使飞行控制系统对故障产生的干扰具有良好的鲁棒性。     

存在部分解耦扰动的网络化系统容错控制

针对一类存在执行器故障和部分解耦扰动的离散时间网络化控制系统,研究测量数据随机丢失情况下的主动容错控制问题。首先,通过模型转换将原系统化为一个与之等价的状态增广系统;然后在考虑测量数据发生随机丢失情况下,构造未知输入观测器(unknown input observer, UIO)实现对系统状态与故障的联合估计,再基于状态和故障的在线估计值,设计基于信号补偿的容错控制律实现对原系统的主动容错控制。在该容错控制算法中,观测器与控制器增益的存在性条件均可利用李雅普诺夫稳定性理论对误差系统进行随机分析得到,相应的估计器和控制器参数可通过在线求解具有凸约束的矩阵不等式获得。最后,通过一个喷气式发动机模型的仿真算例验证所提出的故障估计与主动容错控制方法的有效性。     

Fault-tolerant control for a class of non-linear systems with dead-zone

In this paper, a fault-tolerant control scheme is proposed for a class of single-input and single-output non-linear systems with the unknown time-varying system fault and the dead-zone. The non-linear state observer is designed for the non-linear system using differential mean value theorem, and the non-linear fault estimator that estimates the unknown time-varying system fault is developed. On the basis of the designed fault estimator, the observer-based fault-tolerant tracking control is then developed using the backstepping technique for non-linear systems with the dead-zone. The stability of the whole closed-loop system is rigorously proved via Lyapunov analysis and the satisfactory tracking control performance is guaranteed in the presence of the unknown time-varying system fault and the dead-zone. Numerical simulation results are presented to illustrate the effectiveness of the proposed backstepping fault-tolerant control scheme for non-linear systems.     

A pulsed plasma thruster fault detection and isolation strategy for formation flying of satellites

The main objective of this paper is to develop a dynamic neural network-based fault detection and isolation (FDI) scheme for pulsed plasma thrusters (PPTs) that are employed in the attitude control subsystem (ACS) of satellites tasked to perform formation flying (FF) missions. A hierarchical methodology is proposed that consists of three fault detection and isolation (FDI) approaches, namely (i) a “low-level” FDI scheme, (ii) a “high-level” FDI scheme, and (iii) an “integrated” FDI scheme. Based on the data from the electrical circuit of the PPTs, the proposed “low-level” FDI scheme can detect and isolate faults in the PPT actuators with a good level of accuracy, however the precision level is poor and below expectations with the misclassification rates as expressed by False Healthy and False Faulty parameters being too high. The proposed “high-level” FDI scheme utilizes data from the relative attitudes of the FF mission. This scheme has good detection capabilities, however its isolation capabilities are not adequate. Finally, the proposed “integrated” FDI scheme takes advantage of the strengths of each of the above two schemes while reducing their individual weaknesses. The results demonstrate a high level of accuracy (99.79%) and precision (99.94%) with a misclassification rates that are quite negligible (less than 1%). Furthermore, the proposed “integrated” FDI scheme provides additional and interesting information related to the effects of faults in the thrust production levels that would not have been available from simply using the low or the high level schemes alone.