A parameter-varying fault detection filter design approach for polytopic uncertain linear systems

This paper is concerned with the robust fault detection (FD) problem for a class of polytopic uncertain linear systems driven by a Wiener process. It is assumed that the state matrix is affinely depending on unknown but bounded time-varying parameters. A switching mechanism is introduced to construct the robust FD filter with variable gains and to improve the FD performances which are inherent in the traditional FD filter with fixed gains. Finally, the filter design problem is formulated as a feasibility problem in terms of solving linear matrix inequalities (LMIs), and an example is presented to illustrate the proposed methodology.     

Output feedback preview control for polytopic uncertain discrete‐time systems with time‐varying delay

This paper considers the preview tracking control problem of polytopic uncertain discrete‐time systems with a time‐varying delay subject to a previewable reference signal. First, a model transformation is employed and a discrete‐time system with a time‐invariant delay and an external disturbance is obtained. The difference operator method can be extended to derive an augmented error system that includes future information on the reference signal. Then, a previewable reference signal is fully utilized through reformulation of the output equation while considering the output feedback. Based on the small gain theorem, a static output feedback controller with preview actions is designed such that the output can asymptotically track the reference signal. Finally, numerical simulation examples also illustrate the superiority of the desired preview controller for the uncertain system in the paper.     

Robust filter design for piecewise discrete‐time systems with time‐varying delays

A novel delay‐dependent filtering design approach is developed for a class of linear piecewise discrete‐time systems with convex‐bounded parametric uncertainties and time‐varying delays. The time‐delays appear in the state as well as the output and measurement channels. The filter has a linear full‐order structure and guarantees the desired estimation accuracy over the entire uncertainty polytope. The desired accuracy is assessed in terms of either ??_∞‐performance or ??₂–??_∞ criteria. A new parametrization procedure based on a combined Finsler's Lemma and piecewise Lyapunov–Krasovskii functional is established to yield sufficient conditions for delay‐dependent filter feasibility. The filter gains are determined by solving a convex optimization problem over linear matrix inequalities. In comparison to the existing design methods, the developed methodology yields the least conservative measures since all previous overdesign limitations are almost eliminated. By means of simulation examples, the advantages of the developed technique are readily demonstrated. Copyright © 2009 John Wiley & Sons, Ltd.     

Asynchronous fault detection filter design approach for discrete‐time switched linear systems

This paper is concerned with the problem of the fault detection filter design for discrete‐time switched linear systems with average dwell‐time. The designed fault detection filters are also switched systems, which are assumed to be asynchronously switched with the original switched systems. Improved results on the weighted l₂ performance and the H _? performance are first given, and the multiple Lyaounov‐like functions during matched period and unmatched period for the running time of one subsystem are used. By the aid of multiple Lyapunov‐like functions combined with Projection Lemma, the FD filters are designed such that the augmented systems under asynchronous switching are exponentially stable, and the residual signal generated by the filters achieves the weighted l₂‐gain for disturbances and guarantees the H _? performance for faults. Sufficient conditions are formulated by linear matrix inequalities, and the filter gains are characterized in terms of the solution of a convex optimization problem. Finally, examples are provided to demonstrate the effectiveness of the proposed design method. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust multiple‐fault detection filter

A new robust multiple‐fault detection and identification algorithm is determined. Different from other algorithms which explicitly force the geometric structure by using eigenstructure assignment or geometric theory, this algorithm is derived from solving an optimization problem. The output error is divided into several subspaces. For each subspace, the transmission from one fault, denoted the associated target fault, is maximized while the transmission from other faults, denoted the associated nuisance fault, is minimized. Therefore, each projected residual of the robust multiple‐fault detection filter is affected primarily by one fault and minimally by other faults. The transmission from process and sensor noises is also minimized so that the filter is robust with respect to these disturbances. It is shown that, in the limit where the weighting on each associated nuisance fault transmission goes to infinity, the filter recovers the geometric structure of the restricted diagonal detection filter of which the Beard–Jones detection filter and unknown input observer are special cases. Filter designs can be obtained for both time‐invariant and time‐varying systems. Copyright © 2002 John Wiley & Sons, Ltd.     

Robust non‐minimal order filter and smoother design for discrete‐time uncertain systems

This paper is concerned with the design of robust non‐minimal order H_∞ filters for uncertain discrete‐time linear systems. The uncertainty is assumed to be time‐invariant and to belong to a polytope. The novelty is that a convex filtering design procedure with Linear Matrix Inequality constraints is proposed to synthesize guaranteed‐cost filters with order greater than the order of the system. An H_∞‐norm bound for the transfer‐function from the system input to the filtering error is adopted as performance criterion. The non‐minimal order filters proposed generalize other existing filters with augmented structures from the literature and can provide better performance. An extension to the problem of robust smoothing is proposed as well. The procedure is illustrated by a numerical example. Copyright © 2016 John Wiley & Sons, Ltd.     

Active fault detection based on set‐membership approach for uncertain discrete‐time systems

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.     

Robust fault detection filter design for uncertain LTI systems based on new bounded real lemma

This paper concerns the problem of robust fault detection filter design for uncertain linear time-invariant (LTI) systems with both model uncertainty and disturbances. Firstly, the fault detection filter design is formulated to H _∞ model-matching problem. Secondly, based on a new bounded real lemma, a sufficient condition for the existence of the robust fault detection filter is constructed in term of linear matrix inequalities (LMIs). Owing on the introduction of the tuning parameter and slack variables in obtained LMI condition, the proposed design method can provide higher fault detection sensitivity performance than the existing one. Finally, an illustrative example is employed to demonstrate the effectiveness of the proposed approach. Recommended by Editorial Board member Bin Jiang under the direction of Editor Jae Weon Choi. This work was supported by Postdoctoral Fundation of Jiangsu Province under grant 0901026c and Key Laboratory of Education Ministry for Image Processing and Intelligent Control under grant 200805. Tao Li received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a postdoctoral researcher with the same university. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Lingyao Wu received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Xinjiang Wei was born in Dongying, China, in 1977. He received the B.S. degrees from Yantai Normal University, China in 1999, M.S. degrees from Bohai University in 2002, and the Ph.D. degree in Department of Information from Northeastern University in 2005. From 2006 to Present, he was with Ludong University as an Associate Professor. From 2006 to 2009, he was a Postdoctoral Fellow at Southeast University. His research interests include robust control, nonlinear control, and fuzzy control.     

Asynchronous fault detection observer design for discrete‐time piecewise linear systems

This paper studies the problem of asynchronous fault detection (FD) observer design for piecewise linear systems. Considering that the states of the FD observer and the system may stay at different regions of the state space, asynchronous FD observers are designed at different instants to cope with the challenges incurred by exogenous disturbances and fault signals. By employing new piecewise Lyapunov functions that depend on the different regions where the states are located, it is proved that the proposed asynchronous FD observers ensure the stability and H_∞ performance of the error systems. Three examples are given to show that the new design scheme provides better FD results than the existing design methods.     

Full‐complexity polytopic robust control invariant sets for uncertain linear discrete‐time systems

This paper presents an algorithm for the computation of full‐complexity polytopic robust control invariant (RCI) sets, and the corresponding linear state‐feedback control law. The proposed scheme can be applied for linear discrete‐time systems subject to additive disturbances and structured norm‐bounded or polytopic uncertainties. Output, initial condition, and performance constraints are considered. Arbitrary complexity of the invariant polytope is allowed to enable less conservative inner/outer approximations to the RCI sets whereas the RCI set is assumed to be symmetric around the origin. The nonlinearities associated with the computation of such an RCI set structure are overcome through the application of Farkas' theorem and a corollary of the elimination lemma to obtain an initial polytopic RCI set, which is guaranteed to exist under certain conditions. A Newton‐like update, which is recursively feasible, is then proposed to yield desirable large/small volume RCI sets.     

Explicit improved vertex control for uncertain,time‐varying linear discrete‐time systems with state and control constraints

A technique is presented to compute an explicit state feedback solution to the regulation problem for uncertain and/or time‐varying linear discrete‐time systems with state and control constraints. A piecewise affine control law is provided that not only guarantees recursive feasibility and robust asymptotic stability but is also optimal for a region of the state space containing the origin. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Global finite‐time stabilization via time‐varying output‐feedback for uncertain nonlinear systems with unknown growth rate

This paper considers the global finite‐time output‐feedback stabilization for a class of uncertain nonlinear systems. Comparing with the existing related literature, two essential obstacles exist: On the one hand, the systems in question allow serious parametric unknowns and serious time variations coupling to the unmeasurable states, which is reflected in that the systems have the unmeasurable states dependent growth with the rate being an unknown constant multiplying a known continuous function of time. On the other hand, the systems possess remarkably inherent nonlinearities, whose growth allows to be not only low‐order but especially high‐order with respect to the unmeasurable states. To effectively cope with these obstacles, we established a time‐varying output‐feedback strategy to achieve the finite‐time stabilization for the systems under investigation. First, a time‐varying state‐feedback controller is constructed by adding an integrator method, and by homogeneous domination approach, a time‐varying reduced‐order observer is designed to precisely rebuild the unmeasurable states. Then, by certainty equivalence principle, a desired time‐varying output‐feedback controller is constructed for the systems. It is shown that, as long as the involved time‐varying gain is chosen fast enough to overtake the serious parametric unknowns and the serious time variations, the output‐feedback controller renders that the closed‐loop system states converge to zero in finite time. Copyright © 2017 John Wiley & Sons, Ltd.     

Robust fault detection filter design for networked control systems with delay distribution characterisation

In this article, robust fault detection (RFD) is investigated for networked control systems with delay distribution characterisation. By utilising an observer-based fault detection filter as a residual generator, the RFD of networked control systems with non-uniformly distributed network‐induced time-varying delay is formulated as an H _∞ model-matching problem. Delay-interval-dependent and delay-interval-occurrence-rate-dependent sufficient conditions are obtained by employing the Lyapunov–Krasovskii functional approach. Especially, the robust fault detection filters guarantee strong robustness from residual signal to disturbance as well as high sensitivity to faults. A numerical example is given to illustrate the effectiveness of the proposed design techniques.     

Integrated fault detection system design for linear discrete time‐varying systems with bounded power disturbances

This paper investigates the problem of an integrated fault detection system design for linear discrete time‐varying systems with bounded power disturbances. In the integrated design of residual generator and evaluator, an approximated energy constraint is first imposed on the bounded power disturbances, and then selected by solving a min–max problem to achieve minimal‐size set of undetectable faults under the condition of zero false alarms. To tackle the problem that the computational burden involved in solving the min–max optimization grows with time, the moving horizon method is proposed. The proposed approach in this paper has two advantages: (i) the approximated energy constraint on bounded power disturbances is explicitly selected as a min–max solution in the integrated design to improve fault detection rate; by contrast, when directly applying any existing fault detection method to the case of bounded power disturbances, a predefined approximated energy constraint is implicitly introduced without considering fault detection performance; (ii) the design objective of the proposed approach can choose to consider faults only in the recent time horizon rather than faults in the complete time horizon; this strategy enhances detection performance of recent faults and benefits early fault detection, but has not been considered by existing fault detection methods. Copyright © 2012 John Wiley & Sons, Ltd.     

Real‐time nonlinear moving horizon observer with pre‐estimation for aircraft sensor fault detection and estimation

This paper presents a real‐time nonlinear moving horizon observer (MHO) with pre‐estimation and its application to aircraft sensor fault detection and estimation. An MHO determines the state estimates by minimizing the output estimation errors online, considering a finite sequence of current and past measured data and the available system model. To achieve the real‐time implementability of such an online optimization–based observer, 2 particular strategies are adopted. First, a pre‐estimating observer is embedded to compensate for model uncertainties so that the calculation of disturbance estimates in a standard MHO can be avoided without losing much estimation performance. This strategy significantly reduces the online computational complexity. Second, a real‐time iteration scheme is proposed by performing only 1 iteration of sequential quadratic programming with local Gauss‐Newton approximation to the nonlinear optimization problem. Since existing stability analyses of real‐time moving horizon observers cannot address the incorporation of the pre‐estimating observer, a new stability analysis is performed in the presence of bounded disturbances and noises. Using a nonlinear passenger aircraft benchmark simulator, the simulation results show that the proposed approach achieves a good compromise between estimation performance and computational complexity compared with the extended Kalman filtering and 2 other moving horizon observers.     

带有无穷分布时滞的不确定系统的鲁棒H_∞滤波器设计

针对一类在系统的状态方程与可测输出中都包含有非线性无穷分布时滞的参数不确定系统,提出一种新颖的鲁棒H∞滤波器的设计方法.设计的鲁棒H∞滤波器可以保证对于带有时变且范数有界的参数不确定性的滤波误差系统是渐近稳定的,并且满足所给定的H∞性能指标.鲁棒H∞滤波器可以通过线性矩阵不等式方法获得.通过一个数值的例子验证了该方法的有效性.     

Delay‐dependent robust control for singular discrete‐time Markovian jump systems with time‐varying delay

The problem of delay‐dependent robust stabilization for uncertain singular discrete‐time systems with Markovian jumping parameters and time‐varying delay is investigated. In terms of free‐weighting‐matrix approach and linear matrix inequalities, a delay‐dependent condition is presented to ensure a singular discrete‐time system to be regular, causal and stochastically stable based on which the stability analysis and robust stabilization problem are studied. An explicit expression for the desired state‐feedback controller is also given. Some numerical examples are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust fusion time‐varying Kalman estimators for multisensor networked systems with mixed uncertainties

This paper addresses the problem of designing robust fusion time‐varying Kalman estimators for a class of multisensor networked systems with mixed uncertainties including multiplicative noises, missing measurements, packet dropouts, and uncertain‐variance linearly correlated measurement and process white noises. By the augmented approach, the original system is converted into a stochastic parameter system with uncertain noise variances. Furthermore, applying the fictitious noise approach, the original system is converted into one with constant parameters and uncertain noise variances. According to the minimax robust estimation principle, based on the worst‐case system with the conservative upper bounds of the noise variances, the five robust fusion time‐varying Kalman estimators (predictor, filter, and smoother) are presented by using a unified design approach that the robust filter and smoother are designed based on the robust Kalman predictor, which include three robust weighted state fusion estimators with matrix weights, diagonal matrix weights, and scalar weights, a modified robust covariance intersection fusion estimator, and robust centralized fusion estimator. Their robustness is proved by using a combination method, which consists of Lyapunov equation approach, augmented noise approach, and decomposition approach of nonnegative definite matrix, such that their actual estimation error variances are guaranteed to have the corresponding minimal upper bounds for all admissible uncertainties. The accuracy relations among the robust local and fused time‐varying Kalman estimators are proved. A simulation example is shown with application to the continuous stirred tank reactor system to show the effectiveness and correctness of the proposed results.