Model reduction of two-dimensional discrete systems

1986 ◽  
Vol 33 (5) ◽  
pp. 558-562 ◽  
Author(s):  
E. Jury ◽  
K. Premaratne
Keyword(s):  
Model Reduction ◽  
Discrete Systems ◽  
Two Dimensional

ℋ∞ model reduction for uncertain two-dimensional discrete systems

2005 ◽  
Vol 26 (4) ◽  
pp. 199-227 ◽  
Author(s):  
Huijun Gao ◽  
James Lam ◽  
Changhong Wang ◽  
Shengyuan Xu
Keyword(s):  
Model Reduction ◽  
Discrete Systems ◽  
Two Dimensional

Model reduction of Takagi-Sugeno fuzzy two-dimensional systems: FM LSS model case

2021 ◽  
Author(s):  
Abderrahim El-Amrani ◽  
Rachid Naoual ◽  
Khaddouj Ben Meziane ◽  
Ismail Boumhidi
Keyword(s):  
Model Reduction ◽  
Two Dimensional ◽  
Model Case ◽  
Takagi Sugeno

Model reduction for two-dimensional systems

2003 ◽  
Author(s):  
M.R. Azimi-Sadjadi ◽  
K. Khorasani
Keyword(s):  
Model Reduction ◽  
Two Dimensional

Parameter-dependent robust H∞ filtering for uncertain two-dimensional discrete systems in the FM second model

2020 ◽  
Vol 37 (4) ◽  
pp. 1114-1132
Author(s):  
Khalid Badie ◽  
Mohammed Alfidi ◽  
Mohamed Oubaidi ◽  
Zakaria Chalh
Keyword(s):  
Asymptotic Stability ◽  
Lyapunov Function ◽  
Discrete Systems ◽  
Performance Criterion ◽  
Linear Matrix ◽  
Two Dimensional ◽  
Matrix Inequalities ◽  
Parameter Uncertainties ◽  
Error System ◽  
Parameter Dependent

Abstract This paper deals with the problem of robust $H_{\infty }$ filtering for uncertain two-dimensional discrete systems in the Fornasini–Marchesini second model with polytopic parameter uncertainties. Firstly, a new $H_{\infty }$ performance criterion is derived by exploiting a new structure of the parameter-dependent Lyapunov function. Secondly, based on the criterion obtained, a new condition for the existence of a robust $H_{\infty }$ filter that ensures asymptotic stability, and a prescribed $H_{\infty }$ performance level of the filtering error system, for all admissible uncertainties is established in terms of linear matrix inequalities. Finally, two examples are given to illustrate the effectiveness and advantage of the proposed method.

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