Dimensionless systems identification and model order reduction

2013 ◽  
pp. 51-78
Author(s):  
Romero ◽  
Alfaro ◽  
Arrieta
Keyword(s):  
Model Order Reduction ◽  
Order Reduction ◽  
Model Order ◽  
Systems Identification

scholarly journals MixedLpEstimators Variety for Model Order Reduction in Control Oriented System Identification

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Christophe Corbier ◽  
Jean-Claude Carmona
Keyword(s):  
Model Order Reduction ◽  
Degrees Of Freedom ◽  
Linear Models ◽  
Order Reduction ◽  
Model Complexity ◽  
Model Order ◽  
New Family ◽  
Systems Identification ◽  
Consistency Properties ◽  
Oriented System

A new family of MLE typeLpestimators for model order reduction in dynamical systems identification is presented in this paper. A family ofLpdistributions proposed in this work combinesLp2(1<p2<2) andLp1(0<p1<1) distributions which are quantified by four parameters. The main purpose is to show that these parameters add degrees of freedom (DOF) in the estimation criterion and reduce the estimated model complexity. Convergence consistency properties of the estimator are analysed and the model order reduction is established. Experimental results are presented and discussed on a real vibration complex dynamical system and pseudo-linear models are considered.

THE NEW ALGORITHM OF SOLVING HARMONIC BALANCE EQUATIONS

2019 ◽  
Author(s):  
Vladimir Lantsov ◽  
A. Papulina
Keyword(s):  
Harmonic Balance ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Balance Equations ◽  
Model Order ◽  
Cad Systems ◽  
Computational Costs ◽  
Reduction Methods ◽  
Model Equations

The new algorithm of solving harmonic balance equations which used in electronic CAD systems is presented. The new algorithm is based on implementation to harmonic balance equations the ideas of model order reduction methods. This algorithm allows significantly reduce the size of memory for storing of model equations and reduce of computational costs.

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