LPV鲁棒故障观测器设计

针对线性参数变化（Linear Parameter Varying,LPV）系统的故障检测问题,采用H_- / H_∞混合优化方法,对基于LPV模型的鲁棒故障观测器（RFDO）进行设计,基于离散的参数依赖李亚普诺夫函数,得到了系统的LPV鲁棒故障观测器的综合条件,经过转化,观测器的设计问题被转化为一组线性矩阵不等式的求解问题;利用LMI工具求解线性矩阵不等式,得到了系统的LPV鲁棒故障观测器。最后,通过在一点上对故障输入的非线性仿真,验证了该方法的有效性。     

基于鲁棒自适应滑模观测器的多故障重构

针对一类不确定非线性系统, 基于滑模观测器研究执行器和传感器同时故障时的鲁棒重构问题. 引入线性变换矩阵并添加后置滤波器构建增维系统, 综合??_∞ 控制将鲁棒滑模观测器增益矩阵设计方法, 转化为LMI 约束下的多目标凸优化问题. 在滑模增益中添加了自适应律, 确保状态估计误差渐近稳定, 同时滑模运动经有限时间到达滑模面, 在此基础上给出执行器和传感器故障同时重构算法. 最后通过数值算例表明了所提出方法的有效性.

     

A robust fault detection approach for nonlinear systems

In this paper, we study the robust fault detection problem of nonlinear systems. Based on the Lyapunov method, a robust fault detection approach for a general class of nonlinear systems is proposed. A nonlinear observer is first provided, and a sufficient condition is given to make the observer locally stable. Then, a practical algorithm is presented to facilitate the realization of the proposed observer for robust fault detection. Finally, a numerical example is provided to show the effectiveness of the proposed approach.     

On the robust fault detection via a sliding mode disturbance observer

This paper deals with robust fault detection for non-linear systems. This problem is usually solved by designing an observable subsystem which is only affected by the fault and not by the control and disturbance inputs. However, such a subsystem may not exist so that the so-called fundamental problem of residual generation (FPRG) is not solvable. The aim of the present paper is to design a fault detection filter when the conditions for the existence of a solution to the non-linear FPRG are not satisfied. Our approach is made in a geometric context. Under some decoupling assumptions, the design of sliding mode observers allows us to reconstruct the disturbance inputs and then to generate an effective residual. An illustrative example is given throughout the paper.     

Adaptive observer design for robust fault estimation

In this article, fault diagnosis for a class of linear systems based on adaptive observer is investigated. Linear systems without model uncertainty are first considered, and two adaptive observers are designed for fault identification. The first one uses optimal design for minimizing the estimation error. The second one can achieve asymptotic fault estimation. The general situation where the system is subjected to either model errors or external disturbance is then discussed. Robust adaptive control techniques are applied to guarantee the convergence to a bounded set. Simulation of sensor fault diagnosis for an induction motor is presented to verify the effectiveness of the proposed method.     

基于奇异观测器的连续系统传感器故障估计

研究连续系统的传感器故障估计问题,提出一种奇异观测器来进行故障估计,所提方法不需要假设故障、故障导数和干扰的上界已知.通过HB∞性能指标抑制了干扰对故障估计的影响;采用线性矩阵不等式来获得奇异观测器的增益阵;利用Lyapunov泛函得到了观测误差动态系统的鲁棒渐近稳定性;最后通过飞行器仿真实例验证了所提方法的有效性.     

一种基于鲁棒自适应观测器的故障区分方法

设计了一种鲁棒自适应观测器,通过其输出残差对传感器故障信息敏感性很高,而对系统故障信息敏感性很低的特点,实现了故障区分.设计了一套故障区分控制系统和检测策略,用以区分两类故障,以免发生误判现象.举例说明了该策略的可行性和有效性.     

Design and analysis of robust fault detection filter using LMI tools

In this paper, the robust fault detection filter design problem for linear time invariant (LTI) systems with unknown inputs and modeling uncertainties is studied. The basic idea of our study is to formulate the robust fault detection filter design as a H_∞ model-matching problem. A solution of the optimal problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the formulation of robust fault detection filter design problems, the derivation of a sufficient condition for the existence of a robust fault detection filter and construction of a robust fault detection filter based on the iterative of LMI algorithm.     

Nonlinear robust observer design using an invariant manifold approach

This paper presents a method to design a reduced order observer using an invariant manifold approach. The main advantages of this method are that it enables a systematic design approach, and (unlike most nonlinear observer design methods), it can be generalized over a larger class of nonlinear systems. The method uses specific mapping functions in a way that minimizes the error dynamics close to zero. Another important aspect is the robustness property which is due to the manifold attractivity: an important feature when an observer is used in a closed loop control system. A two degree-of-freedom system is used as an example. The observer design is validated using numerical simulation. Then experimental validation is carried out using hardware-in-the-loop testing. The proposed observer is then compared with a very well known nonlinear observer based on the off-line solution of the Riccati equation for systems with Lipschitz type nonlinearity. In all cases, the performance of the proposed observer is shown to be very high.     

Nonlinear robust fault reconstruction and estimation using a sliding mode observer

This paper considers fault detection and estimation issues for a class of nonlinear systems with uncertainty, using an equivalent output error injection approach. A particular design of sliding mode observer is presented for which the parameters can be obtained using LMI techniques. A fault estimation approach is presented to estimate the fault and the estimation error is dependent on the bounds on the uncertainty. For a special class of uncertainty, a fault reconstruction scheme is presented where the reconstructed signal can approximate the fault signal to any accuracy. The proposed fault estimation/reconstruction signals are only based on the available plant input/ouput information and can be calculated on-line. Finally, a simulation study on a robotic arm system is presented to show the effectiveness of the scheme.     

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 neuro-fuzzy multiple-model observer approach to robust fault diagnosis based on the DAMADICS benchmark problem

This paper presents a new framework for fault detection and isolation (FDI) based on neuro-fuzzy multiple modelling together with robust optimal de-coupling of observers. This new paradigm is called the ‘Neuro-Fuzzy and De-coupling Fault Diagnosis Scheme’ (NFDFDS). Multiple operating points are taken care of through the NF modelling framework. The structure also provides residuals that are de-coupled to ‘unknown inputs’, making use of the earlier research on unknown input de-coupling. The NF paradigm exploits the combined abilities of neural networks and fuzzy logic and is an efficient modelling tool for non-linear dynamic systems because of its approximation and reasoning capabilities. The paper also provides a comparative study of NFDFDS with the Extended Unknown Input Observer (EUIO) for FDI, using the DAMADICS benchmark example.     

New approach to robust observer design

This paper shows that based on the recent development of observer design solution, an observer pole selection method can be formulated to minimize the observer gain to the system input. It is proved that this method is a deterministic approach to the recovery of the loop transfer function and robustness of direct state feedback systems.     

Exact,almost and delayed fault detection: an observer based approach

This paper considers the problem of fault detection and isolation in continuous- and discrete-time systems while using zero or almost zero threshold. A number of different fault detection and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability conditions are given for the formulated design problems together with methods for appropriate design of observer based fault detectors. The 𝓁-step delayed fault detection problem is also considered for discrete-time systems. Moreover, certain indirect fault detection methods such as unknown input observers, eigenstructure assignment, factorization, and parity equation approaches are generalized by including the almost estimation methods in addition to exact estimation methods. Copyright © 1999 John Wiley & Sons, Ltd.