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Active fault detection facilitates determination of the fault characteristics by injecting proper auxiliary input signals into the system. This article proposes an observer‐based on‐line active fault detection method for discrete‐time systems with bounded uncertainties. First, the output including disturbances, measurement noise and interval uncertainties at each sample time is enclosed in a zonotope. In order to reduce the conservativeness in the fault detection process, a zonotopic observer is designed to estimate the system states allowing to generate the output zonotopes. Then, a proper auxiliary input signal is designed to separate the output zonotopes of the faulty model from the healthy model that is injected into the system to facilitate the detection of small fault . Since the auxiliary input signal generation leads to a nonconvex optimization problem, it is transformed into a mixed integer quadratic programming problem. Finally, a case study based on a DC motor is used to show the effectiveness of the proposed method. 相似文献
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This article aims to design an optimal interval observer for discrete linear time‐invariant systems. Particularly, the proposed design method first transforms the interval observer into a zonotopic set‐valued observer by establishing an explicit mathematical relationship between the interval observer and the zonoptopic set‐valued observer. Then, based on the established mathematical relationship, a locally optimal observer gain is designed for the interval observer via the equivalent zonotopic set‐valued observer structure and the Frobenious norm‐based size of zonotopes. Third, considering that the dynamics of the optimal interval observer becomes a discrete linear time‐varying system due to the designed time‐varying optimal gain, an optimization problem to obtain a coordinate transformation matrix and the locally optimal observer gain for the interval observer is formulated and handled. Finally, a theoretic comparison on the conservatism of the interval observer and the zonotopic set‐valued observer is made. At the end of this article, a microbial growth bioprocess is used to illustrate the effectiveness of the proposed method. 相似文献
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Feng Xu Junbo Tan Xueqian Wang Vicenç Puig Bin Liang Bo Yuan Houde Liu 《国际强度与非线性控制杂志
》2017,27(17):3812-3832
》2017,27(17):3812-3832
This paper proposes to design an unknown input observer (UIO) for the linear‐parameter‐varying (LPV) system on the basis of the set theory, which is named as the set‐theoretic UIO (SUIO). The advantage of the SUIO consists in that it combines active and passive approaches to obtain robustness in state estimation (SE) and fault detection (FD). The active approach is based on the use of UIO to decouple unknown inputs, while the passive approach is based on the set theory to bound uncertain factors that cannot be actively decoupled. As a result, the effect of both unknown inputs (process disturbances, modeling errors, etc.) and measurement noises can be appropriately handled in the residual signals compared with the standard UIO‐based SE and FD approaches. The design of SUIO can overcome the limitations of the traditional UIO design conditions, which can significantly broaden the application of the UIO‐based SE and FD theory. Moreover, this paper proposes a generalized framework that can provide more flexibility in the design of SUIO guaranteeing their stability by means of a group of matrix inequalities. Because the LPV system uses a collection of online obtainable scheduling variables to embed nonlinearities, the design of SUIO for the LPV system can be used to address the SE and FD problems of nonlinear systems. At the end of this paper, two case studies are used to illustrate the effectiveness of the proposed approach. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
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在非线性模型参数失配下,直接采用滤波算法很难获到理想的估计状态.本文基于扩展集员估计方法,在状态估计中引入参数的不确定信息,提出一种参数失配有界下的状态估计方法.该方法应用区间或集合运算的法则,计算由参数失配引起的偏差范围,并将其用椭球集外包.在状态估计的预测步,通过该偏差椭球集与先验椭球区间的并运算,得到预测椭球区间;在状态估计的更新步,利用观测椭球集对预测椭球区间进行更新,从而得到后验椭球集合以及状态估计值.最后,在数值仿真和发酵模型中的仿真应用验证了算法的有效性. 相似文献
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污水处理厂配备许多传感器用于监测出水水质.传感器的正常工作与否对保证出水水质至关重要.给出了一种污水处理出水变量传感器故障检测方法.该方法根据入水和出水数据,采用径向基函数神经网络构造出水变量预测模型;使用参数线性集员辨识算法得到网络输出权值的集合描述,从而使预测模型能够给出出水变量的置信区间;以此置信区间为基础获得传... 相似文献
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针对具有传感器故障和未知扰动与测量噪声的线性离散系统, 提出了一种传感器故障区间估计方法. 将传感器故障视为增广状态, 原始系统转化为一个等效的广义系统. 为了得到故障的点估计同时抑制扰动和噪声的影响, 基于有界实引理设计了一个针对广义系统的鲁棒状态观测器. 然后, 通过中心对称多胞体技术实现对故障的区间估计并基于鲁棒正不变集给出了一种降低区间估计计算量的方法. 最后, 通过一个垂直起降(Vertical take-off and landing, VTOL)飞行器线性化模型的仿真算例验证了所提出方法的有效性与优越性. 相似文献
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This paper addresses the problem of interval observer design for unknown input estimation in linear time-invariant systems. Although the problem of unknown input estimation has been widely studied in the literature, the design of joint state and unknown input observers has not been considered within a set-membership context. While conventional interval observers could be used to propagate with some additional conservatism, unknown inputs by considering them as disturbances, the proposed approach allows their estimation. Under the assumption that the measurement noise and the disturbances are bounded, lower and upper bounds for the unmeasured state and unknown inputs are computed. Numerical simulations are presented to show the efficiency of the proposed approach. 相似文献
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Masoud Pourasghar Vicenç Puig Carlos Ocampo-Martinez 《International journal of systems science》2019,50(3):495-516
This paper addresses the characterisation of the minimum detectable fault (MDF) by means of residual sensitivity integrated with the set-invariance theory when using an interval observer-based approach as a fault detection (FD) scheme. Uncertainties (disturbances and noise) are considered as of unknown but bounded nature (i.e. in the set-membership framework). A zonotopic-set representation towards reducing set operations to simple matrix calculations is utilised to bound the state/output estimations provided by the interval observer-based approach. In order to show the connection between sensitivity and set-invariance analyses, mathematical expressions of the MDF are derived when considering different types of faults. Finally, a simulation case study based on a quadruple-tank system is employed to both illustrate and discuss the effectiveness of the proposed approach. The interval observer-based FD scheme is used to test the MDF obtained from the integration of both residual sensitivity analysis and set-invariance theory in the considered case study. 相似文献
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A guaranteed estimator for a general class of nonlinear systems and on‐line usage is developed and analysed. This filter bounds the linearization error, then applies a linear set‐membership filter such that stability guarantees hold for nonlinear systems. A tight bound on the linearization error is found using interval analysis. This filter recursively estimates an ellipsoidal set in which the true state lies. General assumptions include the use of bounded noises and twice continuously differentiable dynamics. When the system is uniformly observable, it is proven that the nonlinear set‐membership filter is stable. In addition, if no noise is present and the initial error is small, the error between the centre of the estimated set and the true value converges to zero. The result is an estimator which is computationally attractive and can be implemented robustly in real‐time. The proposed method is applied to a two‐state example to demonstrate the theoretical results. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
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Majid Ghaniee Zarch Javad Poshtan Mahdi Aliyari Shoorehdeli 《International journal of systems science》2018,49(7):1445-1462
This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the viability constraints characterisation of dynamic evolutions of complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behaviour by using simple sets that approximate the exact set of possible behaviour (in the parameter or state space). In this paper, FDI is based on checking for an inconsistency between the measured and predicted behaviours using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach. 相似文献
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针对基于迭代学习的故障估计器方法,提出一种基于扩张状态观测器(ESO)思想的迭代学习算法,以提高虚拟故障的收敛速度。该算法将ESO的输出误差非线性反馈机制用于迭代学习过程,利用故障估计器当前输出残差的非线性函数修正下次迭代时的虚拟故障值。对所建立的故障估计器的收敛性进行理论分析,并在此基础上进行了仿真实验。仿真结果表明,所提出的算法具有良好的收敛速度和故障估计精度。 相似文献
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集员辨识理论发展及算法综述 总被引：2，自引：0，他引：2
基于UBB噪声假设下的集员辨识是一种新型的系统辨识方法,与传统辨识方法相比具有较强的鲁棒性.本文以参数线性模型为例介绍了集员辨识理论的发展历程和相关算法. 相似文献
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针对带有有界的噪声和参数的非线性离散时间系统, 提出了一种改进的全对称多胞形集员状态估计算法.在算法的时间更新过程中, 采用区间算术的方法计算一个包含系统轨迹的全对称多胞形.在算法的量测更新过程中, 则要首先在状态空间中给出一个集合作为与量测输出相一致的区域的外界描述, 然后计算一个具有最小容积的全对称多胞形作为时间更新全对称多胞形与此集合的交集的外界描述.由于此集合可表示为多个带的交集, 所以需要研究全对称多胞形与带的交集的外界描述方法.在提出改进的外界描述方法之前, 指出了原始外界描述方法的保守性.改进的外界描述方法给出了新的包含二者交集的全对称多胞形族, 然后找到具有最小容积的全对称多胞形作为二者交集的外界描述. 此后证明了改进外界描述方法得到的全对称多胞形不会比原始方法大. 最后, 采用仿真实验来检验不同噪声分布对算法性能的影响.仿真结果表明了改进算法得到的状态估计的均方误差和全对称多胞形的容积比原始算法小, 而且当存在重尾分布噪声时此优势更加明显. 相似文献
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This paper addresses model‐based predictive regulation for a linear discrete‐time system in the presence of unknown but bounded disturbances, partial state information and state/control constraints. The proposed nonlinear dynamic compensator uses a set‐valued estimator, which recursively updates the membership set of the plant state, along with a receding‐horizon regulator which selects on‐line the control variable depending upon the current state membership set. It is shown that the overall scheme preserves feasibility if this is assumed from the outset, and hence guarantees closed‐loop stability and constraint fulfilment. These properties rely on exact set‐membership estimation. A simple approximation scheme which avoids set‐membership estimation but preserves stability is also proposed and the relative performance/complexity tradeoffs are discussed. Simulation results demonstrate the effectiveness of the proposed method. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献