A model-reduction method for nonlinear discrete-time skew-product dynamical systems in the presence of model uncertainty

2010 ◽  
Vol 62 (3) ◽  
pp. 521-534 ◽  
Author(s):  
Nikolaos Kazantzis
Keyword(s):  
Dynamical Systems ◽  
Model Reduction ◽  
Discrete Time ◽  
Model Uncertainty ◽  
Reduction Method ◽  
Skew Product

A new model reduction method for nonlinear dynamical systems

2009 ◽  
Vol 59 (1-2) ◽  
pp. 183-194 ◽  
Author(s):  
Nikolaos Kazantzis ◽  
Costas Kravaris ◽  
Lemonia Syrou
Keyword(s):  
Dynamical Systems ◽  
Model Reduction ◽  
Reduction Method ◽  
Nonlinear Dynamical Systems ◽  
Nonlinear Dynamical ◽  
New Model

Schur Decomposition Model Reduction Algorithm of Discrete-Time Singular Dynamical Systems

2012 ◽  
Vol 468-471 ◽  
pp. 1334-1338
Author(s):  
Lian Hua Hu ◽  
Yan Fei Qiao ◽  
Xiao Feng Yang ◽  
Gui Jing Mei
Keyword(s):  
Dynamical Systems ◽  
Model Reduction ◽  
Discrete Time ◽  
Singular Systems ◽  
Singular Values ◽  
Reduction Algorithm ◽  
Schur Decomposition ◽  
Hankel Singular Values ◽  
Reduction Problem ◽  
Controllability And Observability

In this paper, a model reduction for discrete-time singular dynamical systems is investigated. First, by transforming the original systems, the singular systems of impulse models are decomposed into the casual subsystems and the non-casual subsystems, and the reduction problem becomes merely a simplification of the non-casual subsystems reduction. Based on the Schur decomposition and apply Matlab to reorder the Schur forms, the degree of the systems state controllability and observability is scaled by Hankel singular values, and the results show that the controllability and observability of the states which are corresponding to the smaller Hankel singular values are weaker. Based on it, a new model reduction algorithm of discrete-time singular systems is given. Finally, a numerical simulation illustrates the effectiveness of the proposed algorithm.

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