Robust Fault Detection for Singular Stochastic Systems

2011 ◽  
Vol 128-129 ◽  
pp. 276-279 ◽  
Author(s):  
Ai Qing Zhang

-This paper deals with the problem of fault detection filter (FDF) design for singular stochastic systems . By using an observer-based FDF as a residual generator,the robust fault detection is formulated as a filtering problem. Based on linear matrix inequalities (LMIS) techniques and stability theory of stochastic differential equations, stochastic Lyapunov function method is adopted to design a FDF such that, the filter residual system is sensitive to the fault but robust to the exogenous disturbance.Sufficient conditions are proposed to guarantee the stochastically mean-square stablility with an performance for the faulty detection system. The existence of a FDF for the system under consideration is achieved in terms of LMIS . Moreover, the expressions of desired fault detection filter are given.

2012 ◽  
Vol 503-504 ◽  
pp. 1389-1392
Author(s):  
Li Min Chen

A robust fault detection approach for network-based system is discussed in this paper. The fault detection problem is converted into fault detection filter design. The network-induced delay is assumed to have both the upper bound and the lower bound, which is more general compared with only considering the upper bound. The Lyapunov-Krasovskii functional and the linear matrix inequality (LMI)-based procedure are adopted to design the filter. And the filter can guarantee that the estimation error satisfies the H∞ constraint. Fault detection filter is designed for a flight control system and the effectiveness is verified by the simulation results.


2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Liyuan Hou ◽  
Shouming Zhong ◽  
Hong Zhu ◽  
Yong Zeng ◽  
Lin Shi

This paper purposes the design of a fault detection filter for stochastic systems with mixed time-delays and parameter uncertainties. The main idea is to construct some new Lyapunov functional for the fault detection dynamics. A new robustly asymptotically stable criterion for the systems is derived through linear matrix inequality (LMI) by introducing a comprehensive different Lyapunov-Krasovskii functional. Then, the fault detection filter is designed in terms of linear matrix inequalities (LMIs) which can be easily checked in practice. At the same time, the error between the residual signal and the fault signal is made as small as possible. Finally, an example is given to illustrate the effectiveness and advantages of the proposed results.


2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Bingyong Yan ◽  
Huazhong Wang ◽  
Huifeng Wang

A novel distributed fault detection strategy for a class of nonlinear stochastic systems is presented. Different from the existing design procedures for fault detection, a novel fault detection observer, which consists of a nonlinear fault detection filter and a consensus filter, is proposed to detect the nonlinear stochastic systems faults. Firstly, the outputs of the nonlinear stochastic systems act as inputs of a consensus filter. Secondly, a nonlinear fault detection filter is constructed to provide estimation of unmeasurable system states and residual signals using outputs of the consensus filter. Stability analysis of the consensus filter is rigorously investigated. Meanwhile, the design procedures of the nonlinear fault detection filter are given in terms of linear matrix inequalities (LMIs). Taking the influence of the system stochastic noises into consideration, an outstanding feature of the proposed scheme is that false alarms can be reduced dramatically. Finally, simulation results are provided to show the feasibility and effectiveness of the proposed fault detection approach.


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