Modeling,diagnosis and estimation of actuator faults in vehicle suspensions

This paper deals with the modeling, diagnosis and estimation of faults in automotive Semi-Active (SA) dampers, particularly oil leakages in the actuator. An experimental multiplicative fault model is proposed and statistically validated with an index error of 15% for damper leakage. The fault model is used as design basis for two Fault Detection and Isolation (FDI) frameworks. The Frequency-based Fault Estimator (FFE) is based on the effect of the damper fault in the frequency domain and the Robust Parity Space (RPS) consists in a residual generator sensitive to the fault in the time domain. The model-based FDI systems were experimentally validated in a 1:5 scaled vehicle, fully instrumented and equipped with SA dampers. The experimental results show that, while both approaches represent suitable options for commercial applications, the RPS estimator has the fastest detection time and proportionality to the fault level. In addition, the RPS approach has better robustness to vehicle mass uncertainties. On the other hand, the FFE presents lower sensitivity to road profile and semi-active damper input variations. Additionally, this estimator requires a lower number of sensors and has a lower computational overhead.     

Robust reliable tracking controller design against actuator faults for LPV systems

A robust reliable tracking controller design method is developed against actuator faults for linear parameter varying (LPV) systems under a passive control framework. This method is based on a newly proposed stability condition for LPV systems, which is a more general condition than the existing results. An important contribution of this method is that it could handle relatively wider range of actuator faults due to the extra freedom degree introduced by a new slack variable in the stability condition. Numerical example shows the effectiveness and superiority of our method. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Adaptive estimation of component faults and actuator faults for nonlinear one‐sided Lipschitz systems

Fault estimation for classical nonlinear Lipschitz systems has been subject to several research works. So far, much less interest has been given to the more generalized class of systems, namely, one‐sided Lipchitz systems. Dealing with component faults and actuator faults, only very few works have been done to reconstruct these types of faults for this new class of systems. A major limitation of the previous works is that the fault vector to be estimated there does not give any information about the actual faulty physical parameters of the system, so component faults and actuator faults are not distinguishable. In this paper, a set of possible faulty parameters in the system is estimated. Component faults and actuator faults are separated and distinguished. The effectiveness of the proposed method is shown through simulations for a numerical example.     

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.     

A fault tolerant tracking control for a quadrotor UAV subject to simultaneous actuator faults and exogenous disturbances

ABSTRACT

An observer-based robust adaptive Fault Tolerant Control approach is proposed in this paper to tackle the problem of trajectory tracking for a quadrotor unmanned aerial vehicle (UAV) suffering simultaneous actuator faults, exogenous disturbances and actuator saturation limits. An adaptive fuzzy state observer is proposed to estimate the immeasurable states by using fuzzy logic systems to approximate the unknown nonlinear functions of the uncertain system model. Based on the estimates of the fuzzy observer, an Integral Terminal Sliding Mode Controller that guarantees finite time convergence of the states to a small neighbourhood of zero, even under impaired conditions, is developed. Stability analysis was carried over using the Lyapunov method. The proposed approach was implemented to a quadrotor UAV and its performance was assessed under nominal conditions, and by subjecting the quadrotor to disturbances, simultaneously occurring actuator faults and input saturation limits. Excellent tracking performance and robustness even under worst-case scenarios are among the positive features of the proposed approach.     

Adaptive diagnosis and compensation for hypersonic flight vehicle with multisensor faults

This study proposes an improved adaptive fault diagnosis and compensation scheme for multisensor faults of hypersonic flight vehicles (HFVs). The faults are detected and isolated through a series of sensor output residuals and thresholds that consider observation error and disturbances. Via an adaptive augmented observer, the faults are estimated accurately and a time‐varying disturbance is handled by an additional differential part. Sensor faults are compensated on the basis of estimation results, and disturbances are considered in the fault‐tolerant control (FTC) design, thereby improving the tracking accuracy of the altitude and velocity and robustness with respect to external disturbances for HFVs. The stability of diagnosis and FTC is analyzed by Lyapunov theory. Numerical simulation results explain the validity of the proposed diagnosis and compensation methods.     

具有执行器故障的四旋翼无人机有限时间容错控制

本文主要研究了四旋翼无人机在外部干扰、执行器存在部分失效和偏置故障并发情况下有限时间轨迹跟踪的控制问题. 通过分析四旋翼无人机动力学特性, 构建了带有外部干扰、执行器机构故障的动力学模型. 基于鲁棒全局快速终端滑模控制算法, 设计了一种有限时间容错控制器, 提高了系统对故障的响应速度. 其次, 针对常值/时变故障和干扰,在控制器设计中采用改进的连续函数进行补偿, 减少了由切换函数引起的系统抖振, 并基于Lyapunov函数对控制器的稳定性进行了分析. 最后, 通过仿真实验验证了所设计控制器的有效性和可靠性, 同时存在执行器故障和外部干扰的情况下, 无人机能够实现较好的轨迹跟踪性能.     

Stability analysis and saturation control for nonlinear positive Markovian jump systems with randomly occurring actuator faults

This article investigates the stability analysis and control design of a class of nonlinear positive Markovian jump systems with randomly occurring actuator faults and saturation. It is assumed that the actuator faults of each subsystem are varying and governed by a Markovian process. The nonlinear term is located in a sector. First, sufficient conditions for stochastic stability of the underlying systems are established using a stochastic copositive Lyapunov function. Then, a family of reliable L₁‐gain controller is proposed for nonlinear positive Markovian jump systems with actuator faults and saturation in terms of a matrix decomposition technique. Under the designed controllers, the closed‐loop systems are positive and stochastically stable with an L₁‐gain performance. An optimization method is presented to estimate the maximum domain of attraction. Furthermore, the obtained results are developed for general Markovian jump systems. Finally, numerical examples are given to illustrate the effectiveness of the proposed techniques.     

Non-fragile reliable control of nonlinear positive semi-Markovian jump systems with nonlinear actuator faults

This paper investigates the non-fragile reliable control of nonlinear positive semi-Markovian jump systems with nonlinear actuator faults. First, a novel fault model consisting of linear and nonlinear terms is established for the systems. By constructing a stochastic co-positive Lyapunov function, the non-fragile reliable controller is designed for the systems with additive gain perturbations using matrix decomposition technique. Then, the proposed design is extended for dealing with multiplicative gain perturbations and variable gain perturbations. Under the designed controllers, the resulting closed-loop systems are positive and stochastically stable. All presented conditions are solvable in terms of linear programming. Finally, two illustrative examples are provided to verify the effectiveness of the theoretical results.     

Observer-based adaptive control of uncertain time-delay switched systems with stuck actuator faults

This paper concerns the observer-based adaptive control problem of uncertain time-delay switched systems with stuck actuator faults. Under the case where the original controller cannot stabilize the faulty system, multiple adaptive controllers are designed and a suitable switching logic is incorporated to ensure the closed-loop system stability and state tracking. New delay-independent sufficient conditions for asymptotic stability are obtained in terms of linear matrix inequalities based on piecewise Lyapunov stability theory. On the other hand, adaptive laws for on-line updating of some of the controller parameters are also designed to compensate the effect of stuck failures. Finally, simulation results for reference [1] model show that the design is feasible and efficient.     

多故障的奇偶方程-参数估计诊断方法

提出一种将奇偶方程与参数估计相结合的多故障诊断方法。构造了一种新的奇俩方程，其产生的残差仅对一个传感器故障和一个执行器故障敏感。将传感器和执行器故障模型表示成刘度因子和偏差的形式，应用卡尔曼滤没方法对各故障模型参数进行估计。某型号飞机控制系统的仿真结果表明，新方法能对传感器故障和执行器故障同时存在的线性系统进行诊断，有效地估计出各故障的模型参数。     

A virtual actuator and sensor approach for fault tolerant control of LPV systems

In this paper, a fault tolerant control (FTC) strategy using virtual actuators and sensors for linear parameter varying (LPV) systems is proposed. The main idea of this FTC method, initially developed for LTI systems, is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator/sensor is modified adding the virtual actuator/sensor block that masks the actuator/sensor fault. The suggested technique is an active FTC strategy that reconfigures the virtual actuator/sensor on-line taking into account faults and operating point changes. The stability of the reconfigured control loop is guaranteed if the faulty plant is stabilizable/detectable. The LPV virtual actuator/sensor is designed using polytopic LPV techniques and linear matrix inequalities (LMIs). A two-tank system simulator is used to assess the performance of the proposed method. In particular, it is shown that the application of the proposed technique results in an improvement, in terms of performance, with respect to the LTI counterpart.     

Fault detection and diagnosis in synchronous motors using hidden Markov model-based semi-nonparametric approach

Early detection and diagnosis of faults in industrial machines would reduce the maintenance cost and also increase the overall equipment effectiveness by increasing the availability of the machinery systems. In this paper, a semi-nonparametric approach based on hidden Markov model is introduced for fault detection and diagnosis in synchronous motors. In this approach, after training the hidden Markov model classifiers (parametric stage), two matrices named probabilistic transition frequency profile and average probabilistic emission are computed based on the hidden Markov models for each signature (nonparametric stage) using probabilistic inference. These matrices are later used in forming a similarity scoring function, which is the basis of the classification in this approach. Moreover, a preprocessing method, named squeezing and stretching is proposed which rectifies the difficulty of dealing with various operating speeds in the classification process. Finally, the experimental results are provided and compared. Further investigations are carried out, providing sensitivity analysis on the length of signatures, the number of hidden state values, as well as statistical performance evaluation and comparison with conventional hidden Markov model-based fault diagnosis approach. Results indicate that implementation of the proposed preprocessing, which unifies the signatures from various operating speeds, increases the classification accuracy by nearly 21% and moreover utilization of the proposed semi-nonparametric approach improves the accuracy further by nearly 6%.     

Adaptive fuzzy fault-tolerant output feedback control of uncertain nonlinear systems with actuator faults

This article develops an adaptive fuzzy control method for accommodating actuator faults in a class of unknown nonlinear systems with unmeasured states. The considered faults are modelled as both loss of effectiveness and lock-in-place (stuck at unknown place). With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive observer is developed for estimating the unmeasured states. Combining the backstepping technique with the nonlinear tolerant-fault control theory, a novel adaptive fuzzy faults-tolerant control approach is constructed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded and the tracking error between the system output and the reference signal converges to a small neighbourhood of zero by appropriate choice of the design parameters. Simulation results are provided to show the effectiveness of the control approach.     

Self adaptive growing neural network classifier for faults detection and diagnosis

Fault detection and diagnosis have gained widespread industrial interest in machine monitoring due to their potential advantage that results from reducing maintenance costs, improving productivity and increasing machine availability. This article develops an adaptive intelligent technique based on artificial neural networks combined with advanced signal processing methods for systematic detection and diagnosis of faults in industrial systems based on a classification method. It uses discrete wavelet transform and training techniques based on locating and adjusting the Gaussian neurons in activation zones of training data. The learning (1) provides minimization in the number of neurons depending on cost error function and other stopping criterions; (2) offers rapid training and testing processes; (3) provides accuracy in classification as confirmed by the results on real signals. The method is applied to classify mechanical faults of rotary elements and to detect and isolate disturbances for a chemical process. Obtained results are analyzed, explained and compared with various methods that have been widely investigated for fault diagnosis.     

LMI approach to reliable guaranteed cost control with multiple criteria constraints: The actuator faults case

Based on the multi‐objective optimization strategy and linear matrix inequality approach, the problem of reliable guaranteed cost control with multiple criteria constraints is investigated for a class of uncertain discrete‐time systems subject to actuator faults. A fault model in actuators, which considers outage or partial degradation in independent actuators, is adopted. The quadratic stability is proved to be independent of the disturbance and the upper bound of a quadratic cost index is improved. The reliable feedback controller is designed to minimize the upper bound of the quadratic cost index, place all the closed‐loop poles in a specified disk, constrain the H_∞ norm level of the disturbance attenuation into a given range and guarantee the magnitudes of control inputs less than the given bound, as well. Thus, the resulting closed‐loop system can provide satisfactory stability, transient behavior, disturbance rejection level and optimized upper bound of the quadratic cost performance despite possible actuator faults. Copyright © 2008 John Wiley & Sons, Ltd.     

Robust parameter-dependent fault-tolerant control for actuator and sensor faults

In this article, we study a robust fault-tolerant control (FTC) problem for linear systems subject to time-varying actuator and sensor faults. The faults under consideration are loss of effectiveness in actuators and sensors. Based on the estimated faults from a fault detection and isolation scheme, robust parameter-dependent FTC will be designed to stabilise the faulty system under all possible fault scenarios. The synthesis condition of such an FTC control law will be formulated in terms of linear matrix inequalities (LMIs) and can be solved efficiently by semi-definite programming. The proposed FTC approach will be demonstrated on a simple faulty system with different fault levels and fault estimation error bounds.     

Vague故障诊断方法在振动故障诊断中的应用

提出模糊数据[hij]化成Vague数据[hij]的转化公式：[Ki(hj)=hij=[tij,1-fij]=(hij)2,(hij)1/2],以及Vague集[H]和[G]之间的相似度量公式：[Mm(H,G)=1ni=1n3-f(m)hi-f(m)gi-c(m)hi-c(m)gi-d(m)hi-d(m)gi3+f(m)hi-f(m)gi+c(m)hi-c(m)gi+d(m)hi-d(m)gi]。应用Vague故障诊断方法,进行汽轮发电机组的振动故障诊断,其效果是理想的。