Operator-Based Robust Nonlinear Free Vibration Control of a Flexible Plate With Unknown Input Nonlinearity

In this paper,a robust nonlinear free vibration control design using an operator based robust right coprime factorization approach is considered for a flexible plate with unknown input nonlinearity.With considering the effect of unknown input nonlinearity from the piezoelectric actuator,operator based controllers are designed to guarantee the robust stability of the nonlinear free vibration control system.Simultaneously,for ensuring the desired tracking performance and reducing the effect of unknown input nonlinearity,operator based tracking compensator and estimation structure are given,respectively.Finally,both simulation and experimental results are shown to verify the effectiveness of the proposed control scheme.     

Robust fault detection filter design for a class of time-delay systems via equivalent transformation

This paper is concerned with the robust fault detection filter (RFDF) design for a class of linear timeinvariant systems (LTISs) with output state time delays. Although existing results in literatures study the RFDF for timedelay systems, few is concerned with the output state time-delay systems. The basic idea of our study is to eliminate the time delays of system and transform it to a delay-free system (i.e., a linear time-invariant system without time delays) by the bicausal change of coordinates approach. Then, we design the RFDF for the delay-free LTIS, which is equivalent to the original system with time delays. We first introduce a class of systems with output state time delays, whose fault can be detected by using the RFDF design approach for delay-free systems. Then, since the RFDF design problem can be formulated as a standard H-infinity-model matching problem, it is solved by using H-infinity-optimization LMI techniques. In the last, the adaptive threshold of fault detection is chosen and an illustrative design example is used to demonstrate the validity of the design approach.     

Design of a bilinear fault detection observer for singular bilinear systems

A bilinear fault detection observer is proposed for a class of continuous time singular bilinear systems subject to unknown input disturbance and fault. By singular value decomposition on the original system, a bilinear fault detection observer is proposed for the decomposed system via an algebraic Riccati equation, and the domain of attraction of the state estimation error is estimated. A design procedure is presented to determine the fault detection threshold. A model of flexible joint robot is used to demonstrate the effectiveness of the proposed method.     

A Model-free Approach to Fault Detection of Continuous-time Systems Based on Time Domain Data

In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.     

A nonsmooth IMC method for mechanical systems with backlash

This paper proposes a discrete-time nonsmooth internal model control （NSIMC） approach for mechanical transmission systems described by so-called sandwich system with backlash. In this method, a dynamic compensator is introduced to compensate for the effect of the input linear subsystem. Thus, the sandwich systems with backlash can be simplified as a pseudo-Hammerstein system with backlash. The corresponding NSIMC strategy is designed to control this system. The design procedure of the controller is presented based on the analysis on the robust stability by considering the model errors involved with the effect of backlash as well as the compensated error of the input linear subsystem. Moreover, as the model is switched among the different operating zones, the robust filters are proposed to guarantee the robust stability and satisfactory control performance of the system.     

Combination of model-based observer and support vector machines for fault detection of wind turbines

Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontalaxis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions,generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state(which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind     

Robust fault diagnosis for non-Gaussian stochastic systems based on the rational square-root approximation model

The task of robust fault detection and diagnosis of stochastic distribution control （SDC） systems with uncertainties is to use the measured input and the system output PDFs to still obtain possible faults information of the system. Using the rational square-root B-spline model to represent the dynamics between the output PDF and the input, in this paper, a robust nonlinear adaptive observer-based fault diagnosis algorithm is presented to diagnose the fault in the dynamic part of such systems with model uncertainties. When certain conditions are satisfied, the weight vector of the rational square-root B-spline model proves to be bounded. Conver- gency analysis is performed for the error dynamic system raised from robust fault detection and fault diagnosis phase. Computer simulations are given to demon- strate the effectiveness of the proposed algorithm.     

Robust fault detection in linear systems based on full-order state observers

A parametric approach to robust fault detection in linear systems with unknown disturbances is presented. The residual is generated using full-order state observers （FSO）. Based on an analytical solution to a type of Sylvester matrix equations, the parameterization of the observer gain matrix is given. In terms of the design degrees of freedom provided by the parametric observer design and a group of introduced parameter vectors, a sufficient and necessary condition for fullorder state observer design with disturbance decoupling is then established. By properly constraining the design parameters according to this proposed condition, the effect of the disturbance on the residual signal is also decoupled, and a simple algorithm is developed. The presented approach offers all the degrees of design freedom. Finally, a numerical example illustrates the effect of the proposed approach.     

An output delay approach to fault estimation for sampled-data systems

The problem of fault estimation for a class of non-uniformly sampled-data systems is investigated from the time delay point of view in this paper.Firstly,the output delay approach is employed to model the sampled-data system as a continuous-time one with time-varying delay output.Then,based on the analysis of the inapplicability of the adaptive fault diagnosis observer in such class of time-delay systems,a novel augmented fault estimation observer design method is proposed to guarantee the exponential convergence of the estimation errors.Furthermore,an extension to the case of time varying fault estimation for the noisy sampled-data systems is studied.Finally,simulation results of a flight control system are presented to demonstrate the effectiveness of the proposed method.     

Multimodel-based flight control system reconfiguration control in the presence of input constraints

In this paper, an active fault accommodate strategy is proposed for the plant in the presence of actuator fault and input constraints, which is a combination of a direct adaptive control algorithm with multiple model switching. The μ-modification is introduced in the model reference architecture to construct the adaptive controller. The proof of stability is based on the candidate Lyapunov function, while appropriate switching of multiple models guarantees asymptotic tracking of the system states and the boundedness of all signals. Simulation results illustrate the efficiency of the proposed method.     

一种鲁棒故障检测与分离的参数化方法

针对具有未知干扰输入的多变量线性系统,提出一种鲁棒故障检测与分离的完全参数化方法。利用最近的结果,基于Luenberger未知输入观测器矩阵的特征值及一组自由参数向量,分别给出了系统干扰解耦和故障分离的充要条件。通过适当选择满足一些约束的自由参数,仅使用单一观测器实现了鲁棒故障检测与分离设计。该方法提供了所有设计自由度。一个数值例子证明了该方法的有效性。     

Stable robust feedback control system design for unstable plants with input constraints using robust right coprime factorization

A stable robust control system design problem for unstable plants with input constraints is considered using robust right coprime factorization of nonlinear operator. For obtaining strong stability of the closed‐loop system of unstable plants with input constraints, a design scheme of robust nonhyphen‐linear control system is given based on robust right coprime factorization. Some conditions for the robustness and system output tracking of the unstable plant with input constraints are derived. Numerical examples are given to demonstrate the validity of the theoretical results. Copyright © 2007 John Wiley & Sons, Ltd.     

Robust Unknown Input Observer Design for Linear Uncertain Time Delay Systems with Application to Fault Detection

In this paper, a novel approach is proposed to design a robust fault detection observer for uncertain linear time delay systems. The system is composed of both norm‐bounded uncertainties and exogenous signals (noise, disturbance, and fault) which are considered to be unknown. The main contribution of this paper is to present unknown input observer (UIO)‐based fault detection system which shows the maximum sensitivity to fault signals and the minimum sensitivity to other signals. Since the system contains uncertainty terms, an H_∞ model‐matching approach is used in design procedure. The reference residual signal generator system is designed so that the fault signal has maximum sensitivity while the exogenous signals have minimum sensitivity on the residual signal. Then, the fault detection system is designed by minimizing the estimation error between the reference residual signal and the UIO residual signal in the sense of H_∞ norm. A sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities (LMIs). Application of the proposed method in a numerical example and an engineering process are simulated to demonstrate the effectiveness of the proposed algorithm. Simulation results show the validity of the proposed approach to detect the occurrence of faults in the presence of modeling errors, disturbances, and noise.     

Delta算子描述的离散系统故障检测滤波器

研究基于Delta算子模型的离散时间系统故障检测问题.推导了Delta算子系统的故障可检测和可分离条件,给出了Delta算子模型的故障检测滤波器设计方法.研究表明,在采样周期很小时,Delta算子故障检测趋近于连续模型的相应结果,可统一处理连续系统和离散系统故障检测的相关问题.仿真实例验证了该方法的有效性.     

一种新的时滞系统鲁棒故障诊断滤波器设计方法

研究具有扰动不确定的状态时滞系统鲁棒故障诊断滤波器的设计问题.通过对系统传递函数输入输出通道的组合变换,引入一种能够同时体现残差对扰动信号鲁棒性和对故障信号灵敏性的性能指标,将基于状态观测器的鲁棒故障诊断滤波器设计问题转化为H∞优化设计问题,应用线性矩阵不等式(LMI)技术,给出并证明了该设计问题解存在的条件和求解方法.最后,通过一个仿真算例来验证本方法的有效性.     

Guidance Laws With Input Constraints and Actuator Failures

A novel three‐dimensional fault‐tolerant control guidance law is proposed for interception of maneuvering targets in the presence of external disturbances, actuator failures, and control input constraints. The input‐to‐state stability (ISS) method is introduced to design the fault‐tolerant control guidance law to guarantee robust tracking of a maneuvering target. Then, a saturated fault‐tolerant control guidance law is constructed using a modified saturation function to ensure the resulting control signal will never incur input constraints, and the convergence to a small neighborhood of origin is ensured in theory. Simulation results show that the presented approach is effective in achieving a successful interception against target maneuvers, external disturbances, actuator failures, and control input constraints.     

Unknown Input Fault Detection and Isolation Observer Design for Neutral Systems

This paper deals with actuator fault diagnosis of neutral delayed systems with multiple time delays using an unknown input observer. The main purpose is to design an observer that guarantees the asymptotic stability of the estimate error dynamics and the actuator fault detection. The existence conditions for such an observer are established. The main problem studied in this paper aims at designing observer‐based fault detection and isolation. The designed observer enhances the robust diagnosis performance, including rapidity and accuracy, and generates residuals that enjoy perfect decoupling properties among faults. Based on Lyapunov stability theory, the design of the observer is formulated in terms of linear matrix inequalities, and the diagnosis scheme is based on a bank of unknown input observers for residual generation that guarantees fault detection and isolation in the presence of external disturbances. A numerical example is presented to illustrate the efficiency of the proposed approach.     

基于混杂系统方法的一类采样数据系统鲁棒故障检测

针对具有连续时间过程噪声和离散时间测量噪声的采样数据系统, 提出了一种新的鲁棒故障检测直接设计方法. 首先利用具有有限跳变的线性系统作为残差产生器, 采样数据系统的鲁棒故障检测设计问题被描述成采样数据滤波问题, 然后给出有限跳变线性系统有界实引理的线性矩阵不等式(LMI)表达形式, 基于此, 推导出采样数据系统鲁棒故障检测滤波器的存在条件及设计参数, 并将所提方法推广到具有结构不确定性的采样数据系统上. 所设计的滤波器能够保证残差与故障之间误差最小, 并对过程噪声、测量噪声、结构不确定性等因素鲁棒. 最后, 通过数值仿真对所提方法的可行性进行了验证.     

Robust adaptive fault‐tolerant quantized control of nonlinear systems with constraints on system behaviors and states

In this work, we develop a robust adaptive fault‐tolerant tracking control scheme for a class of input‐quantized strict‐feedback nonlinear systems in the presence of error/state constraints and actuation faults. The problem is rather complicated yet challenging if nonparametric uncertainties and unknown quantization parameters as well as time‐varying yet completely undetectable actuation faults are involved in the considered systems. Compared with the most existing approaches in the literature, the proposed control exhibits several attractive advantages: (1) upon using a nonlinear decomposition for quantized input and employing the robust technique for actuation fault, not only the exact knowledge of quantization parameters are not required, but also the actuation fault can be easily compensated since neither fault detection and diagnosis/fault detection and identification nor controller reconfiguration is needed; (2) based on the error/state‐dependent unified nonlinear function, the constraints on tracking error and system states are directly handled and the cases with or without constraints can also be addressed in a unified manner without changing the control structure; and (3) the utilization of unified nonlinear function‐based dynamic surface control not only avoids the problem of the explosion of complexity in traditional backstepping design, but also bypasses the demanding feasibility conditions of virtual controllers. Furthermore, by using the Lyapunov analysis, it is ensured that all signals in the closed‐loop systems are uniformly ultimately bounded. The effectiveness of the developed control algorithm is confirmed by numerical simulations.