Fault detection for a class of uncertain nonlinear Markovian jump stochastic systems with mode-dependent time delays and sensor saturation

This paper considers the problem of robust H_∞ fault detection for a class of uncertain nonlinear Markovian jump stochastic systems with mode-dependent time delays and sensor saturation. We aim to design a linear mode-dependent H_∞ fault detection filter that ensures, the fault detection system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed H_∞-norm level for all admissible uncertainties. By using the Lyapunov stability theory and generalised Itô formula, some novel delay-dependent sufficient conditions in terms of linear matrix inequality are proposed to guarantee the existence of the desired fault detection filter. Explicit expression of the desired mode-dependent linear filter parameters is characterised by matrix decomposition, congruence transformation and convex optimisation technique. Sector condition method is utilised to deal with sensor saturation, a definite relation of sector condition parameters with fault detection system robustness against disturbances and sensitivity to faults is put forward, and weighting fault signal approach is employed to improve the performance of the fault detection system. A simulation example and an industrial nonisothermal continuous stirred tank reactor system are utilised to verify the effectiveness and usefulness of the proposed method.     

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.     

Robust fault detection for Markovian jump systems with unreliable communication links

This article addresses the problem of robust fault detection for Markovian jump linear systems with unreliable communication links. In the network communication channel, the effects of signal quantisation and measurement missing, which appears typically in a network environment, are taken into consideration simultaneously. A stochastic variable satisfying the Bernoulli random binary distribution is utilised to model the phenomenon of the measurements missing. The aim is to design a fault detection filter such that, for all unknown input and incomplete measurements, the error between the residual and weighted faults is made as small as possible. A sufficient condition for the existence of the desired fault detection filter is established in terms of a set of linear matrix inequalities. A simulation example is provided to illustrate the effectiveness and applicability of the proposed techniques.     

AN ITERATIVE LMI APPROACH TO RFDF FOR LINEAR SYSTEM WITH TIME‐VARYING DELAYS

This paper deals with robust fault detection filter (RFDF) problem for a class of linear uncertain systems with time‐varying delays and model uncertainties. The RFDF design problem is formulated as an optimization problem by using L₂‐induced norm to represent the robustness of residual to unknown inputs and modelling errors, and the sensitivity to faults. A sufficient condition to the solvability of formulated problem is established in terms of certain matrix inequalities, which can be solved with the aid of an iterative linear matrix inequality (ILMI) algorithm. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.     

Robust fault detection for networked control systems with nonlinear disturbances and imperfect measurements

In this article, the robust fault detection (FD) problem is investigated for networked control systems with nonlinear disturbances and imperfect measurements. Under the consideration of packet-dropout compensation, a new measurement model is proposed to take the time-varying delay, random packet dropout and quantisation effect into account simultaneously. After properly augmenting the states of the original system and the FD filter, the robust FD problem is formulated as an auxiliary H _∞ filtering problem for a stochastic parameter system with time-varying delays and uncertainties. A sufficient condition for the existence of the robust FD filter is derived in terms of linear matrix inequalities, which depends on both the network status and the quantisation density. A numerical example is provided to illustrate the effectiveness of the proposed method.     

Robust H∞ Filtering For Uncertain Stochastic Time‐Delay Systems

This paper deals with the problem of robust H_∞ filtering for uncertain stochastic systems. The system under consideration is subject to time‐varying norm‐bounded parameter uncertainties and unknown time delays in both the state and measurement equations. The problem we address is the design of a stable filter that ensures the robust stochastic stability and a prescribed H_∞ performance level for the filtering error system irrespective of all admissible uncertainties and time delays. A suffient condition for the solvability of this problem is proposed and a linear matrix inequality approach is developed for the design of the robust H_∞ filters. An illustrative example is provided to demonstrate the effctiveness of the proposed approach.     

Fault detection for a class of networked nonlinear systems subject to imperfect measurements

This paper addresses the problem of fault detection (FD) for discrete-time networked systems with global Lipschitz conditions and imperfect measurements. By using Bernoulli stochastic variables and a switching signal, a unified model is proposed to describe four kinds of imperfect measurements, that is, access constraints, time delays, packet dropouts, and signal quantization. We aim to design a fault detection filter (FDF) such that, for all external disturbances and imperfect measurements, the error between the residual and fault is made as small as possible. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem for discrete-time stochastic switched systems with multiple time-varying delays. By applying Lyapunov-Krasovskii approach, a sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterized. A numerical example is exploited to show the effectiveness of the results obtained.     

Fault detection for a class of discrete‐time nonlinear systems subject to network‐induced uncertainties

This paper addresses the problem of fault detection (FD) for discrete‐time systems with global Lipschitz conditions and network‐induced uncertainties. By utilizing Bernoulli stochastic variables and a switching signal, a unified measurement model is proposed to describe three kinds of network‐induced uncertainties, that is, access constraints, time delays, and packet dropouts. We aim to design a mode‐dependent fault detection filter (FDF) such that, for all external disturbances and the above uncertainties, the error between the residual and fault is made as small as possible. The addressed FD problem is then converted into an auxiliary H_∞ filtering problem for discrete‐time stochastic system with multiple time‐varying delays. By applying the Lyapunov‐Krasovskii approach, a sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMI). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterized. A numerical example is exploited to show the effectiveness of the results obtained. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

H∞ fault detection with randomly occurring nonlinearities and channel fadings

In this paper, the H_∞ fault detection problem is investigated for a class of discrete-time stochastic systems with both channel fadings and randomly occurring nonlinearities. Due to Doppler effect and multi-path delays, channel fadings are inevitable and also cause unpredictable dynamic behaviour. The Lth Rice fadings model, which is accounted for both channel fadings and time delays, can be employed to describe this phenomenon. Meanwhile, by using a Bernoulli distributed white sequence, a kind of non-linear disturbance appearing in a random way is also considered in the H_∞ fault detection issue. The purpose of the addressed problem is to design a fault detection filter such that, in the presence of channel fadings, the overall fault detection dynamics is stochastically stable and, at the same time, the error between the residual (generated by the fault detection filter) and the fault signal is made as small as possible. By utilising the Lyapunov stability theory associated with the intensive stochastic analysis techniques, sufficient conditions are established under which the addressed H_∞ fault detection problem is recast as solving a convex optimisation problem via the semi-definite programme method. Finally, a simulation example is exploited to show the effectiveness of the method proposed in this paper.     

An LMI approach to design robust fault detection filter for uncertain LTI systems

In this paper, the robust fault detection filter design problem for uncertain linear time-invariant (LTI) systems with both unknown inputs and modelling errors is studied. The basic idea of our study is to use an optimal residual generator (assuming no modelling errors) as the reference residual model of the robust fault detection filter design for uncertain LTI systems with modelling errors and, based on it, to formulate the robust fault detection filter design as an H_∞ model-matching problem. By using some recent results of H_∞ optimization, a solution of the optimization problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the development of an optimal reference residual model, the formulation of robust fault detection filter design problem, the derivation of a sufficient condition for the existence of a robust fault detection filter and a construction of it based on the LMI solution parameters, the determination of adaptive threshold for fault detection. An illustrative design example is employed to demonstrate the effectiveness of the proposed approach.