Fractional order unknown input filter design for fault detection of discrete linear systems

Author(s):  
Jafar Zarei ◽  
Mahmood Tabatabaei ◽  
Roozbeh Razavi-Far ◽  
Mehrdad Saif
Automatica ◽  
2014 ◽  
Vol 50 (11) ◽  
pp. 2835-2839 ◽  
Author(s):  
Behnam Allahverdi Charandabi ◽  
Horacio J. Marquez

2018 ◽  
Vol 40 (16) ◽  
pp. 4321-4329 ◽  
Author(s):  
Jafar Zarei ◽  
Mahmood Tabatabaei

In this study, a new method is introduced to design an estimator for discrete-time linear fractional order systems, which are affected by unknown disturbances. The main goal of this study is decoupling disturbance and uncertainties from the true states for discrete fractional order systems in noisy environment. The fractional Kalman filter framework is exploited to develop a robust estimator against unknown inputs (UIs) in noisy environment. The proposed filter is exploited to detect faults in fractional order systems. Simulation results illustrate the advantages of this robust filter for state estimation and fault detection of fractional order model of ultra-capacitor (UC). The robustness of the designed filter is shown in the sense of disturbance decoupling in the presence of noise.


2000 ◽  
Vol 33 (11) ◽  
pp. 387-392
Author(s):  
Ferenc Szigeti ◽  
Addison Ríos ◽  
Rocco Tarantino

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