Functional unknown input reconstruction of descriptor systems: Application to fault detection

Automatica ◽  
2015 ◽  
Vol 57 ◽  
pp. 145-151 ◽  
Author(s):  
Francisco Javier Bejarano
Keyword(s):  
Fault Detection ◽  
Descriptor Systems ◽  
Unknown Input ◽  
Input Reconstruction

scholarly journals Actuator Fault Detection for Discrete-Time Descriptor Systems via a Convex Unknown Input Observer with Unknown Scheduling Variables

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Javier Martinez ◽  
Braulio Aguiar ◽  
Víctor Estrada-Manzo ◽  
Miguel Bernal
Keyword(s):  
Fault Detection ◽  
Discrete Time ◽  
Estimation Error ◽  
Mean Value ◽  
Descriptor Systems ◽  
Mean Value Theorem ◽  
Linear Matrix ◽  
Unknown Input ◽  
Actuator Fault ◽  
And Performance

This paper presents actuator fault detection of discrete-time nonlinear descriptor systems by means of nonlinear unknown input observers. The approach is based on the exact factorization of the estimation error in order to overcome the well-known problem of unmeasurable scheduling variables within the observation of convex models, thus avoiding the use of Lipschitz constants, differential mean value theorem, or robust techniques. As a result, the designing conditions are cast in terms of linear matrix inequalities and efficiently solved via commercially available software. Numerical as well as academic setups are provided to illustrate the advantages and performance of the proposal.

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