Robust fault detection filter design for multiple model systems via nonsmooth optimization approach

2014 ◽  
Author(s):  
Jingwen Yang ◽  
Frederic Hamelin ◽  
Dominique Sauter ◽  
Didier Theilliol
Keyword(s):  
Fault Detection ◽  
Nonsmooth Optimization ◽  
Filter Design ◽  
Model Systems ◽  
Optimization Approach ◽  
Multiple Model ◽  
Fault Detection Filter ◽  
Robust Fault Detection ◽  
Detection Filter

Robust Fault Detection for Network-Based System with Time-Varying Bounded Delay

2012 ◽  
Vol 503-504 ◽  
pp. 1389-1392
Author(s):  
Li Min Chen
Keyword(s):  
Fault Detection ◽  
Flight Control ◽  
Upper Bound ◽  
Filter Design ◽  
Estimation Error ◽  
Linear Matrix ◽  
Fault Detection Filter ◽  
Detection Approach ◽  
Robust Fault Detection ◽  
Detection Filter

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.

scholarly journals Observer-Based Robust Fault Detection Filter Design and Optimization for Networked Control Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Weilai Jiang ◽  
Chaoyang Dong ◽  
Erzhuo Niu ◽  
Qing Wang
Keyword(s):  
Fault Detection ◽  
Control Systems ◽  
Networked Control Systems ◽  
Networked Control ◽  
Optimization Approach ◽  
Design And Optimization ◽  
Fault Detection Filter ◽  
Random Delays ◽  
Robust Fault Detection ◽  
Detection Filter

The problem of robust fault detection filter (FDF) design and optimization is investigated for a class of networked control systems (NCSs) with random delays. The NCSs are modeled as Markovian jump systems (MJSs) by assuming that the random delays obey a Markov chain. Based on the model, an observer-based residual generator is constructed and the corresponding fault detection problem is formulated as anH∞filtering problem by which the error between the residual signal and the fault is made as small as possible. A sufficient condition for the existence of the desired FDF is derived in terms of linear matrix inequalities (LMIs). Furthermore, to improve the performance of the robust fault detection systems, a time domain optimization approach is proposed. The solution of the optimization problem is given in the form of Moore-Penrose inverse of matrix. A numerical example is provided to illustrate the effectiveness and potential of the proposed approach.

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