scholarly journals Parametric space-frequency reduction for second-order system models

2018 ◽  
Author(s):  
Vanessa Cool ◽  
Frank Naets ◽  
Ward Rottiers ◽  
Wim Desmet
Keyword(s):  
Frequency Response ◽  
Cost Reduction ◽  
Frequency Response Function ◽  
Performance Metrics ◽  
Computational Cost ◽  
Order System ◽  
Model Parameters ◽  
Frequency Content ◽  
Space Frequency ◽  
Set Up

This research focusses on the computational cost reduction of frequency domain simulations in many-query applications with varying model parameters. These analyses are often encountered during the design of mechanical structures, where frequency response function (FRF) amplitudes are still one of the key performance metrics to be considered. Moreover, often inputs (number and frequency content) can vary broadly, which makes it all the more challenging to set up the reduced model.

Semi-empirical model for a hydraulic servo-solenoid valve

2002 ◽  
Vol 216 (3) ◽  
pp. 237-248 ◽  
Author(s):  
J A Ferreira ◽  
F Gomes de Almeida ◽  
M R Quintas
Keyword(s):  
Frequency Response ◽  
High Performance ◽  
Closed Loop ◽  
Optimization Techniques ◽  
Order System ◽  
Model Parameters ◽  
Empirical Modelling ◽  
Non Linear ◽  
Spool Valves ◽  
Semi Empirical

High-performance proportional valves, also called servo-solenoid valves, can be used today in closed-loop applications that previously were only possible with servo-valves. The valve spool motion is controlled in a closed loop with a dedicated hardware controller that enhances the valve frequency response and minimizes some non-linear effects. Owing to their lower cost and maintenance requirements as well as increasing performance they can compete with servo-valves in a large number of applications. This paper describes a new semi-empirical modelling approach for hydraulic proportional spool valves to be used in hardware-in-the-loop simulation experiments. The developed models use either data sheet or experimental values to fit the model parameters in order to reproduce both static (pressure gain, leakage flowrate and flow gain) and dynamic (frequency response) valve characteristics. Valve behaviour is divided into two parts: the static behaviour and the dynamic behaviour. A parameter decoupled model, with a variable equation structure, and a flexible model, with a fixed equation structure, are proposed for the static part. Spool dynamics are modelled by a non-linear second-order system, with limited velocity and acceleration, the parameters being adjusted using optimization techniques.

Identifying parametric variation in second-order system from frequency response measurement

2016 ◽  
Vol 24 (5) ◽  
pp. 879-891 ◽  
Author(s):  
A Hegde ◽  
J Tang
Keyword(s):  
Frequency Response ◽  
Parametric Identification ◽  
Second Order ◽  
Order System ◽  
Model Parameters ◽  
Order Model ◽  
Response Measurement ◽  
Electrical Systems ◽  
Angle Measurements ◽  
Second Order Model

Fundamentally, second-order model is the foundation of describing the dynamic characteristics of many mechanical and electrical systems. This paper investigates a parametric identification scheme for single degree-of-freedom second-order model in which the model parameters are subject to normal variation. By utilizing frequency response magnitude and phase angle measurements, we construct a linear-in-the-parameters model and build a related maximum likelihood estimator for both parametric means as well as variances. The validity of the approach is demonstrated through a collection of case analyses, and the results show considerable levels of accuracy in the presence of sufficient data.

The Study and Application of Electromagnetic Vibration Shaker Finite Element Model Updating and Validation Technology

2010 ◽  
Vol 458 ◽  
pp. 231-236
Author(s):  
Xun Tao Liu ◽  
Zhao Bo Chen ◽  
Li Fu Xu ◽  
Shan Yun Huang
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Model Updating ◽  
Element Model ◽  
Model Parameters ◽  
Electromagnetic Vibration ◽  
Vibration Shaker

Acording to the fact that the finite element model of electromagnetic vibration shaker for virtual experiment is not accurate enough to complete accurately spacecraft test, made a correlation analysis of the finite element output frequency response function and the measured frequency response function by their correlation coefficients. Analyzed the sensitivity of the materials for FRF and screened the parameters to update, made the correlation coefficient error of electromagnetic vibration shaker finite element model frequency response function and the measured as the optimization objective, the optimization and modification of shaker finite element model parameters were completed by iteration method. The frequency response function of the modified finite element model approximately agreed with the experimental frequency response function. It met the virtual experiments of electromagnetic vibration shaker.

The anti-oscillator model parameters linked to the apparent mass frequency response function

2008 ◽  
Vol 312 (4-5) ◽  
pp. 630-643 ◽  
Author(s):  
E. Jacquelin ◽  
J.-P. Lainé ◽  
A. Bennani ◽  
M. Massenzio
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Oscillator Model ◽  
Model Parameters ◽  
Apparent Mass

scholarly journals A scheme for comprehensive computational cost reduction in proper orthogonal decomposition

2018 ◽  
Vol 69 (4) ◽  
pp. 279-285 ◽  
Author(s):  
Satyavir Singh ◽  
M Abid Bazaz ◽  
Shahkar Ahmad Nahvi
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Cost Reduction ◽  
Nonlinear Dynamical Systems ◽  
Nonlinear Dynamical System ◽  
Computational Cost ◽  
Nonlinear Function ◽  
Orthogonal Decomposition ◽  
Order System ◽  
Nonlinear Dynamical ◽  
Proper Orthogonal

Abstract This paper addresses the issue of offline and online computational cost reduction of the proper orthogonal decomposition (POD) which is a popular nonlinear model order reduction (MOR) technique. Online computational cost is reduced by using the discrete empirical interpolation method (DEIM), which reduces the complexity of evaluating the nonlinear term of the reduced model to a cost proportional to the number of reduced variables obtained by POD: this is the POD-DEIM approach. Offline computational cost is reduced by generating an approximate snapshot-ensemble of the nonlinear dynamical system, consequently, completely avoiding the need to simulate the full-order system. Two snapshot ensembles: one of the states and the other of the nonlinear function are obtained by simulating the successive linearization of the original nonlinear system. The proposed technique is applied to two benchmark large-scale nonlinear dynamical systems and clearly demonstrates comprehensive savings in computational cost and time with insignificant or no deterioration in performance.

Topology and Frequency Response Function Analysis Applied to Structural Parts Aiming Mass and Cost Reduction

2015 ◽  
Author(s):  
Lincoln Lima ◽  
Andre Pereira ◽  
Jose Lincoln Cavalcanti ◽  
Mauricio Kawano ◽  
Roberto Ferreira
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Cost Reduction ◽  
Frequency Response Function ◽  
Function Analysis ◽  
Structural Parts

Fuel Cell Frequency Response Function Modeling for Control Applications

2010 ◽  
Author(s):  
Thomas C. H. Roberts ◽  
Patrick J. Cunningham
Keyword(s):  
Fuel Cells ◽  
Fuel Cell ◽  
Transfer Function ◽  
Frequency Response ◽  
Response Function ◽  
Time Constant ◽  
Frequency Response Function ◽  
Model Parameters ◽  
Order Model ◽  
First Order

This paper provides the framework for first-order transfer function modeling of a fuel cell for controls use. It is shown that under specific conditions a fuel cell can be modeled as a first-order system. With a first order model, it is possible to determine how the fuel cell responds dynamically on a systems level before incorporating it into a larger more complex system. Current data sheets for fuel cells provide limited information of the output of the fuel cell, and a polarization curve based on static operation. This is vital information, but gives no insight into how the fuel cell responds under dynamic conditions. Dynamic responses are important when incorporating fuel cells as a power source in larger systems, such as automobiles, as loads and conditions are constantly changing. The modeling technique used in this research is the frequency response function. In this approach an experimental frequency response, or Bode plot, is computed from a frequency rich input signal and corresponding output signal. Here the controlled input is the Hydrogen flow and the output is the fuel cell voltage. During these tests, the fuel cell was connected to a constant resistance load. Using the frequency response function approach, a family of first-order transfer function models was created for a fuel cell at different operating temperatures and reactant relative humidity. These models are validated through comparison to experimental step responses. From this family of models the variations in the first-order model parameters of static gain and time constant are quantified. Static gain varied from 0.675 to 0.961 and the time constant ranged between 4.5 seconds and 10.5 seconds.

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