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MMST分组的一类MIMO非线性系统执行器故障自适应补偿控制

在多输入多输出(Multiple-input multiple-output,MIMO)非线性系统的执行器故障容错控制问题中,控制器能够处理的执行器故障集合的大小与执行器分组方法有很大关系.为扩大系统可处理的执行器故障集合,本文针对一类具有执行器故障的MIMO非线性最小相位系统,提出基于多模型切换(Multiple model switching and tuning,MMST)执行器分组的自适应补偿控制方法.考虑系统的执行器卡死、部分失效和完全失效故障,在微分几何反馈线性化的基础上,研究基于多模型切换的执行器分组切换指标和切换策略,设计了基于反演控制的自适应补偿跟踪控制律,所设计的控制律能保证系统在执行器故障时闭环稳定,渐近跟踪给定的参考信号,且提出的分组方法扩大了可补偿的执行器故障集合.仿真结果表明了本文设计方法的有效性.     

Integral sliding mode fault‐tolerant control allocation for a class of affine nonlinear system

This paper develops novel fault‐tolerant integral sliding mode control allocation schemes for a class of an overactuated affine nonlinear system. The proposed schemes rely on an existing baseline controller, and the objective is to retain the nominal (fault‐free) closed‐loop performance in the face of actuator faults/failures by effectively utilizing actuator redundancy. The online control allocation reroutes the control effort to healthy actuators using the knowledge of actuator effectiveness level estimates. One of the proposed schemes is tested in simulation using a well‐known high‐fidelity model of a large civil transport aircraft (B747) from the literature. Good simulation results show the efficacy of the scheme.     

A nonlinear model predictive control scheme for sensor fault tolerance in observation processes

This article addresses the problem of designing a sensor fault‐tolerant controller for an observation process where a primary, controlled system observes, through a set of measurements, an exogenous system to estimate the state of this system. We consider sensor faults captured by a change in a set of sensor parameters affecting the measurements. Using this parametrization, we present a nonlinear model predictive control (NMPC) scheme to control the observation process and actively detect and estimate possible sensor faults, with adaptive controller reconfiguration to optimize the use of the remaining sensing capabilities. A key feature of the proposed scheme is the design of observability indices for the NMPC stage cost to improve the observability of both the state of the exogenous system and the sensor fault parameters. The effectiveness of the proposed scheme is illustrated through numerical simulations.     

四旋翼无人机姿态系统的非线性容错控制设计

本文研究了四旋翼无人机执行器发生部分失效时的姿态控制问题.通过分析其动力学特性,将执行器故障以乘性因子加入系统模型,得到执行器故障情况下四旋翼无人机的姿态动力学模型.在同时存在未知外部扰动和执行器故障的情况下,设计了一种基于自适应滑模控制的容错控制器.利用基于Lyapunov的分析方法证明了所设计控制器的渐近稳定性.在四旋翼无人机实验平台上进行了实验,验证了该算法对存在未知外部扰动和执行器部分失效时四旋翼无人机的姿态控制具有较好的鲁棒性.     

基于LMI的磁浮列车悬浮系统被动容错控制

磁浮列车的悬浮系统是具有多传感器、多控制器的复杂非线性系统,其运行环境十分复杂.一旦发生故障或失效就有可能造成人员伤亡或财产损失.为了提高悬浮系统的安全性和可靠性,针对磁浮列车悬浮系统的电磁铁或功率放大器等执行器故障进行了容错控制问题的研究.在建立磁浮列车悬浮控制系统模型的基础上,从被动容错控制角度出发,采用LMI(线性矩阵不等式)方法设计了悬浮控制系统在执行器故障条件下的容错控制器,并以实际对象参数为例进行了仿真分析.仿真结果表明所设计容错控制器可以实现磁浮列车在故障条件下的稳定悬浮与运行,证明了将基于LMI的被动容错控制策略应用于磁浮列车悬浮控制系统的可行性.     

State estimation and nonlinear predictive control of autonomous hybrid system using derivative free state estimators

In this work, we develop a state estimation scheme for nonlinear autonomous hybrid systems, which are subjected to stochastic state disturbances and measurement noise, using derivative free state estimators. In particular, we propose the use of ensemble Kalman filters (EnKF), which belong to the class of particle filters, and unscented Kalman filters (UKF) to carry out estimation of state variables of autonomous hybrid system. We then proceed to develop novel nonlinear model predictive control (NMPC) schemes using these derivative free estimators for better control of autonomous hybrid systems. A salient feature of the proposed NMPC schemes is that the future trajectory predictions are based on stochastic simulations, which explicitly account for the uncertainty in predictions arising from the uncertainties in the initial state and the unmeasured disturbances. The efficacy of the proposed state estimation based control scheme is demonstrated by conducting simulation studies on a benchmark three-tank hybrid system. Analysis of the simulation results reveals that EnKF and UKF based NMPC strategies is well suited for effective control of nonlinear autonomous three-tank hybrid system.     

Novel frameworks for the design of fault‐tolerant control using optimal sliding‐mode control

This paper describes 2 schemes for a fault‐tolerant control using a novel optimal sliding‐mode control, which can also be employed as actuator redundancy management for overactuated uncertain linear systems. By using the effectiveness level of the actuators in the performance indexes, 2 schemes for redistributing the control effort among the remaining (redundant or nonfaulty) set of actuators are constructed based on an ‐based optimal sliding‐mode control. In contrast to the current sliding‐mode fault‐tolerant control design methods, in these new schemes, the level of control effort required to maintain sliding is penalised. The proposed optimal sliding‐mode fault‐tolerant control design schemes are implemented in 2 stages. In the first stage, a state feedback gain is derived using an LMI‐based scheme that can assign a number of the closed‐loop eigenvalues to a known value whilst satisfying performance specifications. The sliding function matrix related to the particular state feedback derived in the first stage is obtained in the second stage. The difference between the 2 schemes proposed for the sliding‐mode fault‐tolerant control is that the second one includes a separate control allocation module, which makes it easier to apply actuator constraints to the problem. Moreover, it will be shown that, with the second scheme, we can deal with actuator faults or even failures without controller reconfiguration. We further discuss the advantages and disadvantages of the 2 schemes in more details. The effectiveness of the proposed schemes are illustrated with numerical examples.     

Fault tolerant control for a class of nonlinear system with actuator faults

In this work, a fault tolerant control scheme is proposed for a class of nonlinear system with actuator faults. In this fault tolerant control strategy, an estimator is designed to estimate both the system states and the fault signal simultaneously. Based on these estimations, the control law is constructed to achieve the fault tolerant control for the nonlinear system considered. It is shown that the estimation error and the system state can be guaranteed to be bounded. The obtained theoretic results have been verified through the simulation examples on the three‐tank system.     

From data to diagnosis and control using generalized orthonormal basis filters. Part II: Model predictive and fault tolerant control

Given a state space model together with the state noise and measurement noise characteristics, there are well established procedures to design a Kalman filter based model predictive control (MPC) and fault diagnosis scheme. In practice, however, such disturbance models relating the true root cause of the unmeasured disturbances with the states/outputs are difficult to develop. To alleviate this difficulty, we reformulate the MPC scheme proposed by K.R. Muske and J.B. Rawlings [Model predictive control with linear models, AIChE J. 39 (1993) 262–287] and the fault tolerant control scheme (FTCS) proposed by J. Prakash, S.C. Patwardhan, and S. Narasimhan [A supervisory approach to fault tolerant control of linear multivariable systems, Ind. Eng. Chem. Res. 41 (2002) 2270–2281] starting from the innovations form of state space model identified using generalized orthonormal basis function (GOBF) parameterization. The efficacy of the proposed MPC scheme and the on-line FTCS is demonstrated by conducting simulation studies on the benchmark shell control problem (SCP) and experimental studies on a laboratory scale continuous stirred tank heater (CSTH) system. The analysis of the simulation and experimental results reveals that the MPC scheme formulated using the identified observers produces superior regulatory performance when compared to the regulatory performance of conventional MPC controller even in the presence of significant plant model mismatch. The FTCS reformulated using the innovations form of state space model is able to isolate sensor as well as actuator faults occurring sequentially in time. In particular, the proposed FTCS is able to eliminate offset between the true value of the measured variable and the setpoint in the presence of sensor biases. Thus, the simulation and experimental study clearly demonstrate the advantages of formulating MPC and generalized likelihood ratio (GLR) based fault diagnosis schemes using the innovations form of state space model identified from input output data.     

Adaptive fault‐tolerant control for a nonlinear flexible aircraft wing system

Fault‐tolerant control problems have been extensively studied in all kinds of control systems. However, there is little work on fault‐tolerant control for distributed parameter systems. In this paper, a novel adaptive fault‐tolerant boundary control scheme is proposed for a nonlinear flexible aircraft wing system against actuator faults. The whole system is regarded as a distributed parameter system, and the dynamic model of the flexible wing system is described by a set of partial differential equations (PDEs) and ordinary differential equations (ODEs). The proposed controller is designed by using the Lyapunov's direct method and adaptive control strategies. Based on the online estimation of actuator faults, the adaptive controller parameters can update automatically to compensate the actuator faults of the system. Besides, a fault‐tolerant controller is also developed for this system in the presence of external disturbances. Differing from existing works about adaptive fault‐tolerant control, the adaptive controller presented in this paper is designed for a distributed parameter system. Finally, numerical simulations are carried out to illustrate the effectiveness of the proposed control scheme.     

一类MISO 最小相位系统的执行器故障自适应容错控制

针对一类具有执行器卡死或/和变执行器故障的多输入单输出(MISO)非线性最小相位系统,提出一种自适应容错跟踪控制方案.采用自适应算法估计系统的不确定性,利用神经网络逼近执行器未知故障函数,以完成执行器组合故障状态下的跟踪控制.所设计的控制律不仅保证了闭环系统稳定,而且所有状态均有界,跟踪误差一致最终有界.仿真结果表明了所提出方法的有效性.     

Dynamic surface active fault tolerant control design for the attitude control systems of UAV with actuator fault

In this paper, an active fault tolerant control (FTC) approach based on transient performance index is proposed for the attitude control systems of unmanned aerial vehicle (UAV) with actuator fault. The nonlinear attitude control system model for UAV with actuator faults is given, which represents the dynamic characteristics of UAV. A fault diagnosis component is used for fault detection and estimation. According to the fault estimation information obtained during the fault diagnosis, the fault tolerant control scheme is developed by adopting the adaptive dynamic surface control technique, which guarantees the asymptotic output tracking and ultimate uniform boundedness of the closed-loop attitude control systems of UAV in actuator faulty case. Further, a prescribed transient performance of the FTC attitude control systems is considered which characterizes the convergence rate and maximum overshoot of the attitude tracking error. Finally, simulation results are shown that the attitude control system states remain bounded and the output tracking errors converge to a neighborhood of zero.     

Event‐triggered fault‐tolerant control and scheduling codesign for nonlinear networked control systems with medium‐access constraint and packet disordering

This paper studies an event‐triggered communication, scheduling, and fault‐tolerant control codesign method for nonlinear networked control systems with medium‐access constraint, delay, and packet disordering using an adaptive approximation method and adaptive technique. By considering nonlinear dynamics and controller reconfiguration, a novel event‐triggering scheme with an adjustable triggering condition and adaptive triggering thresholds is proposed. The stochastic event‐driven actuator scheduling is investigated without the assumption that the controller can access the current modes of the actuators. By considering the Markovian delay and focusing on the transmitter node, a new packet reordering approach is used to cope with packet disordering. This paper proposes an active fault‐tolerant control method, in which the nominal controller is redesigned for the postfault plant by using the fault information provided by an estimator. It is proven that the estimation error of the estimator is uniformly bounded, the reconfigurable controller and event‐trigger ensure the boundedness in probability of the state tracking error before and after the fault occurrence in the presence of medium‐access constraint, delay, and packet disordering while reducing communication load. The effectiveness of the proposed method is demonstrated in the numerical example.     

基于积分滑模的航天器有限时间姿态容错控制

针对存在执行机构故障和外部干扰的刚体航天器姿态稳定系统,本文提出了基于积分滑模的容错控制策略,实现了姿态有限时间稳定.首先,利用齐次系统相关理论,设计了一类饱和有界的基础控制律,保证了不存在执行机构故障和干扰情况下的姿态有限时间稳定.在此基础上,利用积分滑模和自适应技术设计了一种有限时间姿态鲁棒容错控制方案,对执行机构故障和干扰进行有效的补偿;该方案能够快速地实现姿态高精度稳定,并抑制系统抖振现象.最后,将本文提出的姿态容错控制方案进行数值仿真与对比,验证了方案的有效性与优越性.     

Fault‐Tolerant Control Allocation for Overactuated Nonlinear Systems

This paper addresses the problem of fault‐tolerant control allocation for input affine nonlinear systems. The proposed scheme is divided in three main tasks: fault detection and estimation using a nonlinear observer, fault isolation through a bank of unknown input observers with a resetting policy to reduce the effects of nonlinearities and control reconfiguration based on reduced order allocation. Analytical results regarding the isolability and reconfigurability of actuator faults are derived and a simulation example is used to illustrate the the proposed fault tolerant control methodology.     

模糊非线性奇偶方程故障诊断方法

研究基于模糊模型和奇偶(一致性)方程的非线性系统执行器故障诊断方法.讨论了全 解耦奇偶方程的产生方法,并给出了全解耦奇偶向量存在的条件.由全解耦奇偶方程产生的残 差仅对特定执行器故障敏感,而与系统状态、扰动输入和其它执行器输入无关.用T-S模糊模型 描述非线性系统,并与全解耦奇偶方程相结合得到了模糊奇偶方程,解决了奇偶方程在非线性 系统中的应用问题.将执行器故障模型用刻度因子和偏差表示,用模糊奇偶方程产生残差,从而 可以估计故障模型的参数.文章给出了某飞机非线性模型的仿真实例.     

Multirate sliding mode disturbance compensation for model predictive control

In this paper, a novel hierarchical multirate control scheme for nonlinear discrete‐time systems is presented, consisting of a robust nonlinear model predictive controller (NMPC) and a multirate sliding mode disturbance compensator (MSMDC). The proposed MSMDC acts at a faster rate than the NMPC in order to keep the system as close as possible to the nominal trajectory predicted by NMPC despite model uncertainties and external disturbances. The a priori disturbance compensation turns out to be very useful in order to improve the robustness of the NMPC controller. A dynamic input allocation between MSMDC and NMPC allows to maximize the benefits of the proposed scheme that unites the advantages of sliding mode control (strong reduction of matched disturbances, low computational burden) to those of NMPC (optimality, constraints handling). Sufficient conditions required to guarantee input‐to‐state stability and constraints satisfaction by the overall scheme are also provided. Copyright © 2014 John Wiley & Sons, Ltd.     

A Recurrent Neural-Network-Based Sensor and Actuator Fault Detection and Isolation for Nonlinear Systems With Application to the Satellite's Attitude Control Subsystem

This paper presents a robust fault detection and isolation (FDI) scheme for a general class of nonlinear systems using a neural-network-based observer strategy. Both actuator and sensor faults are considered. The nonlinear system considered is subject to both state and sensor uncertainties and disturbances. Two recurrent neural networks are employed to identify general unknown actuator and sensor faults, respectively. The neural network weights are updated according to a modified backpropagation scheme. Unlike many previous methods developed in the literature, our proposed FDI scheme does not rely on availability of full state measurements. The stability of the overall FDI scheme in presence of unknown sensor and actuator faults as well as plant and sensor noise and uncertainties is shown by using the Lyapunov's direct method. The stability analysis developed requires no restrictive assumptions on the system and/or the FDI algorithm. Magnetorquer-type actuators and magnetometer-type sensors that are commonly employed in the attitude control subsystem (ACS) of low-Earth orbit (LEO) satellites for attitude determination and control are considered in our case studies. The effectiveness and capabilities of our proposed fault diagnosis strategy are demonstrated and validated through extensive simulation studies.