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.

scholarly journals A comparison of second-order model order reduction methods for an artificial fishtail

2019 ◽  
Vol 67 (8) ◽  
pp. 648-667 ◽  
Author(s):  
Jens Saak ◽  
Dirk Siebelts ◽  
Steffen W. R. Werner
Keyword(s):  
Model Order Reduction ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Order Reduction ◽  
Second Order ◽  
Scale Model ◽  
Order Model ◽  
Model Order ◽  
Reduction Methods ◽  
Second Order Model

Abstract In order to apply control theory in small autonomous vehicles, mathematical models with small numbers of states are required for using the limited computational power in embedded programming. In this paper, we consider an artificial fishtail as an example for a complex mechanical system with a second-order large-scale model, which is derived by using the finite element method. To meet the above limitations, the several hundreds of thousands of degrees of freedom need to be reduced to merely a handful of surrogate degrees of freedom. We seek to achieve this task by various second-order model order reduction methods. All methods are applied on the fishtail’s matrices and their results are evaluated and compared in the frequency domain as well as in the time domain.

Discussion of “Dynamic Modeling and Projection-Based Reduction Methods for Bladed Disks With Nonlinear Frictional and Intermittent Contact Interfaces” (Mitra, M., Epureanu, B. I., 2018, ASME Appl. Mech. Rev., 71(5), p. 050803)

2019 ◽  
Vol 71 (5) ◽  
Author(s):  
Jörg Wallaschek ◽  
Sebastian Willeke ◽  
Lars Panning-von Scheidt
Keyword(s):  
Model Order Reduction ◽  
Degrees Of Freedom ◽  
Turbine Blades ◽  
Computational Cost ◽  
Order Reduction ◽  
Bladed Disks ◽  
Model Order ◽  
Advantages And Disadvantages ◽  
Reduction Methods ◽  
Intermittent Contact

Abstract Mitra and Epureanu have written a very good and complete overview on nonlinear vibrations of turbine blades. Nonlinearities due to friction and contact mechanics are the main focus. Questions related to modeling and model reduction are particularly addressed. This paper begins with an investigation of the vibration behavior of cyclic linear structures, in which a variety of considerations about the occurrence of standing and propagating waves play an important role. Subsequently, several methods of model-order reduction are presented, where cyclic sectors of tuned bladed disks are assumed. The classification of the linear vibration modes according to their nodal diameters (NDs) is explained in detail. Large models with a high number of degrees-of-freedom (DOF) occurring in the field of turbomachinery dynamics lead to very high computational cost. In this context, the authors consider model-order reduction with projection-based methods to be of particular interest. They give an overview of modern projection-based methods and compare them with regard to their respective advantages and disadvantages in the context of bladed disks with nonlinear friction and intermittent contact.

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.

Sign in / Sign up

Export Citation Format

Share Document