A fault detection and isolation filter design method for Markov jump linear parameter-varying systems

2011 ◽  
Vol 26 (3) ◽  
pp. 241-257 ◽  
Author(s):  
Gianfranco Gagliardi ◽  
Alessandro Casavola ◽  
Domenico Famularo
Keyword(s):  
Fault Detection ◽  
Filter Design ◽  
Design Method ◽  
Fault Detection And Isolation ◽  
Linear Parameter ◽  
Markov Jump ◽  
Linear Parameter Varying ◽  
Linear Parameter Varying Systems ◽  
Parameter Varying ◽  
Filter Design Method

A fault-detection, filter-design method for linear parameter-varying systems

2007 ◽  
Vol 221 (6) ◽  
pp. 865-874 ◽  
Author(s):  
A Casavola ◽  
D Famularo ◽  
G Franzè ◽  
M Sorbara
Keyword(s):  
Fault Detection ◽  
Filter Design ◽  
Design Method ◽  
Linear Matrix ◽  
False Alarms ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Luenberger Observer ◽  
Parameter Varying ◽  
Filter Design Method

In this paper a fault-detection (FD), filter-design method has been proposed for linear parameter-varying (LPV) systems. The FD filter is an optimal H∞ Luenberger observer synthesized by minimizing frequency conditions that ensure guaranteed levels of disturbance rejection and fault detection. Via the bounded real lemma (BRL) and the separation principle the design method is formulated as a convex linear matrix inequality (LMI) optimization problem. The resulting residual generator is parameter-dependent and uses the plant parameter assumed measurable online. Finally, an FD threshold logic is proposed in order to reduce the generation of false alarms. The effectiveness of the design technique is illustrated via a numerical example.

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