Observer Design for Unknown Input Nonlinear Descriptor Systems via Convex Optimization

2006 ◽  
Vol 51 (6) ◽  
pp. 1047-1052 ◽  
Author(s):  
D. Koenig
Keyword(s):  
Convex Optimization ◽  
Observer Design ◽  
Descriptor Systems ◽  
Unknown Input

Unknown input observer design for a class of Takagi-Sugeno descriptor systems

2016 ◽  
Vol 4 ◽  
pp. 477-492 ◽  
Author(s):  
Karim Bouassem ◽  
Jalal Soulami ◽  
Abdellatif El Assoudi ◽  
El Hassane El Yaagoubi
Keyword(s):  
Observer Design ◽  
Descriptor Systems ◽  
Unknown Input ◽  
Unknown Input Observer ◽  
Takagi Sugeno

Reduced-Order Observer Design for Discrete-Time Descriptor Systems With Unknown Inputs: An Linear Matrix Inequality Approach

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Shenghui Guo ◽  
Fanglai Zhu
Keyword(s):  
Linear Matrix Inequality ◽  
Discrete Time ◽  
Observer Design ◽  
Descriptor Systems ◽  
Linear Matrix ◽  
Unknown Input ◽  
Matrix Inequality ◽  
Reduced Order ◽  
Unknown Inputs ◽  
Reduced Order Observer

Reduced-order observer design methods for both linear and nonlinear discrete-time descriptor systems based on the linear matrix inequality (LMI) approach are investigated. We conclude that the conditions under which a full-order observer exists can also guarantee the existence of a reduced-order observer. By choosing a special reduced-order observer gain matrix, a reduced-order unknown input observer is proposed for linear system with unknown inputs, and then an unknown input reconstruction is provided for some special cases. We also extend above results to the cases of nonlinear systems. Finally, three numerical comparative simulation examples are given to illustrate the effectiveness and merits of proposed methods.

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