scholarly journals Instantaneous Characteristics of Nonlinear Torsion Pendulum and Its Application in Parameter Estimation of Nonlinear System

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yan Zhao ◽  
Baofeng Zhang ◽  
Fangfang Han ◽  
Huan Tian ◽  
Xiao Yu ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Model ◽  
Estimation Method ◽  
Nonlinear Damping ◽  
Torsion Pendulum ◽  
Damping Force ◽  
Restoring Force ◽  
Pendulum System ◽  
The Moment ◽  
The Relationship

The nonlinear model of torsion pendulum is presented by considering the nonlinear damping force and nonlinear restoring force. The analytic solution of the nonlinear model is calculated to analyze the relationship between the characteristics of torsion pendulum and the nonlinear factors. The instantaneous characteristics of nonlinear torsion pendulum are analyzed by instantaneous undamped natural frequency and instantaneous damping coefficient. The instantaneous characteristics can be used for the parameter estimation of nonlinear torsion pendulum system. The nonlinear characteristics of the torsion pendulum are validated by the torsion pendulum based on the air-hovered turntable. The parameter estimation method based on the instantaneous characteristics is validated by the moment of inertia measurement system based on the torsion pendulum.

scholarly journals MODEL DECOMPOSITION BASED ABNORMAL PARAMETER ESTIMATION FOR DISTILLATION COLUMN

2018 ◽  
Vol 48 (2) ◽  
pp. 81-87
Author(s):  
W. D. TIAN ◽  
S. L. SUN
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Model ◽  
Distillation Column ◽  
Estimation Method ◽  
Matrix Analysis ◽  
Physical Parameters ◽  
Time Saving ◽  
Model Decomposition ◽  
Parameter Estimation Method ◽  
Occurrence Matrix

Parameter estimation method can produce useful physical parameters in finding abnormal causes, but nonlinear model makes this method computationally intensive and non-robust for distillation scenario. In this paper, we propose a model decomposition based parameter estimation method for distillation column diagnosis purposes. Nonlinear first principles dynamic model is divided into some disjoint submodels through occurrence matrix analysis. The whole model is used to monitor distillation process and the submodel that gives the highest contribution to the generated residual is selected to perform abnormal parameter estimation. Application results from stripping tower in the popular Tennessee Eastman challenge problem show that the model decomposition based diagnosis scheme is more time-saving and robust than pure nonlinear model based scheme.

Dynamic Property Analysis of Damping Rubber in Rail Fastenings under Different Deformation Condition

2014 ◽  
Vol 494-495 ◽  
pp. 706-710
Author(s):  
Bin Zhang ◽  
Yan Yun Luo ◽  
Zhi Nan Shi
Keyword(s):  
Mechanical Model ◽  
Dynamic Stiffness ◽  
Excitation Frequency ◽  
Nonlinear Damping ◽  
Deformation Condition ◽  
Damping Force ◽  
Restoring Force ◽  
Dynamic Mechanical ◽  
Large Distortion ◽  
Hydraulic Servo

This paper studies the experimental research on dynamic characteristics of the damping rubber in high elastic fastening by the electro-hydraulic servo movement tester. Based on a hypothesis superposition theory of nonlinear elastic restoring force and nonlinear damping force, a non-linear dynamic mechanical model is proposed. The dynamic stiffness and damping parameters of the rubber are obtained in different deformation conditions based on the dynamic mechanical model. The dynamic stiffness is analyzed, and the results show that dynamic stiffness is closely related to excitation frequency and amplitude. Furthermore the dynamic stiffness is analyzed under different free surface of rubber components by using FEM. That also reveals the changeable characteristics and affected factors of the damping rubber of the high elastic fastenings in large distortion condition.

Application of a Hilbert Transform-Based Algorithm for Parameter Estimation of a Nonlinear Ocean System Roll Model

1997 ◽  
Vol 119 (4) ◽  
pp. 239-243 ◽  
Author(s):  
O. Gottlieb ◽  
M. Feldman
Keyword(s):  
Parameter Estimation ◽  
Nonlinear Model ◽  
Hilbert Transform ◽  
Random Noise ◽  
Nonlinear Damping ◽  
Model System ◽  
Field Calibration ◽  
Calibration Test ◽  
Fishing Boat ◽  
Backbone Curves

We combine an averaging procedure with a Hilbert transform-based algorithm for parameter estimation of a nonlinear ocean system roll model. System backbone curves obtained from data are compared to those obtained analytically and are found to be accurate. Sensitivity of the results is tested by introducing random noise to a nonlinear model describing roll response of a small fishing boat. An example field calibration test of a small semisubmersible exhibiting nonlinear damping is also considered.

scholarly journals Likelihood and its use in Parameter Estimation and Model Comparison

2016 ◽  
Vol 37 (3) ◽  
pp. 63-98 ◽  
Author(s):  
Denis Cousineau ◽  
Teresa A. Allan
Keyword(s):  
Parameter Estimation ◽  
Model Comparison ◽  
Regression Line ◽  
Model Fitting ◽  
Estimation Method ◽  
Test Statistics ◽  
Likelihood Methods ◽  
Student’S T ◽  
The Relationship ◽  
Student’S T Test

Parameter estimation and model fitting underlie many statistical procedures. Whether the objective is to examine central tendency or the slope of a regression line, an estimation method must be used. Likelihood is the basis for parameter estimation, for determining the best relative fit among several statistical models, and for significance testing. In this review, the concept of Likelihood is explained and applied computation examples are given. The examples provided serve to illustrate how likelihood is relevant, and related to, the most frequently applied test statistics (Student’s t-test, ANOVA). Additional examples illustrate the computation of Likelihood(s) using common population model assumptions (e.g., normality) and alternative assumptions for cases where data are non-normal. To further describe the interconnectedness of Likelihood and the Likelihood Ratio with modern test statistics, the relationship between Likelihood, Least Squares Modeling, and Bayesian Inference are discussed. Finally, the advantages and limitations of Likelihood methods are listed, alternatives to Likelihood are briefly reviewed, and R code to compute each of the examples in the text is provided.

scholarly journals Estimation of VECM Parameter Using Bayesian Approach: An Application to Analysis of Macroeconomic Variables

2020 ◽  
Vol 9 (6) ◽  
pp. 113
Author(s):  
Meilina Retno Hapsari ◽  
Suci Astutik ◽  
Loekito Adi Soehono
Keyword(s):  
Parameter Estimation ◽  
Exchange Rate ◽  
Interest Rates ◽  
Money Supply ◽  
Bayesian Approach ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Macroeconomic Variables ◽  
Us Dollar ◽  
The Relationship

This study uses Bayesian approach to estimate Vector Error Correction Model (VECM). The aims of this study is to analyze the relationship between macroeconomic variables in Indonesia. To analyze the best method to influence government targets or policies on economic growth by studying the relationships of many macroeconomic variables. Previous studies in analyzing the relationship between macroeconomic variables with VECM analysis, using the Maximum Likelihood Estimation. However this estimation method cannot solve the problem of overparameterization in VECM model. The variables used in this study are six macroeconomic variables in Indonesia in 2010 quarter 1 to 2019 quarter 4 are GDP, the money supply, exchange rate of rupiah to US dollar, exports, imports and interest rates. The number of data in this study is less than the number of estimated parameters causing overparameterization problems. Therefore, this study uses the Bayesian parameter estimation method to avoid overparameterization problems in economic data. The model obtained from this study is the BVECM(3) and it has been proven that the model is suitable (the model diagnostic test). Based on the parameter estimation results of BVECM(3), the significant variables affecting GDP are GDP itself, the money supply, exchange rate of rupiah to US Dollar, exports, imports and the interest rate for Bank Indonesia Certificates. In addition, there is a two-way relationship that affects each other, namely the relationship between GDP and the money supply, exports and imports, exports and interest rates, and between imports and interest rates.

A Study of the Roll Motion by Means of a Free Decay Test

2010 ◽  
Vol 132 (3) ◽  
Author(s):  
Hamid Zeraatgar ◽  
Mohsen Asghari ◽  
Firooz Bakhtiari-Nejad
Keyword(s):  
Damping Ratio ◽  
Nonlinear Damping ◽  
Damping Coefficient ◽  
Roll Motion ◽  
Damping Force ◽  
Restoring Force ◽  
Cubic Form ◽  
Damping Coefficients ◽  
Decay Test ◽  
Nonlinear Form

In this study, a method for the extraction of damping by tracing free roll decay is presented. For this purpose, in calm waters, a bulk carrier model is given a large initial roll angle and then released. Consequently, the roll motion is recorded. Restoring coefficients and virtual moments of inertia for the model are determined by means of an inclining test and recording the damped period, respectively. The linear damping coefficient is evaluated by using the damping ratio. Four different forms of combinations of restoring moment and damping coefficient are assumed in order to determine the nonlinear form of the roll motion. These equations are numerically solved for various damping coefficients and results are compared with the experimental data. By virtue of this comparison, the damping coefficients are determined for each case. It may be concluded that the use of the nonlinear restoring moment, which is an odd polynomial of the fifth order, and the cubic form for the nonlinear damping moment best fits the roll behavior for the ship model. The amount of energy dissipated by the damping moments is also calculated in the time domain. The energy method also confirms that the nonlinear form of restoring force in conjunction with the cubic form of the damping force is the best solution of the roll motion for small to large angles.

Theoretical, methodological and practical issues of choice models

2018 ◽  
Vol 1 (1) ◽  
pp. 21-37
Author(s):  
Bharat P. Bhatta
Keyword(s):  
Discrete Choice ◽  
Model Building ◽  
Estimation Method ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Decision Makers ◽  
Model Formulation ◽  
Random Utility Maximization ◽  
The Relationship ◽  
Method Model

This paper analyzes and synthesizes the fundamentals of discrete choice models. This paper alsodiscusses the basic concept and theory underlying the econometrics of discrete choice, specific choicemodels, estimation method, model building and tests, and applications of discrete choice models. Thiswork highlights the relationship between economic theory and discrete choice models: how economictheory contributes to choice modeling and vice versa. Keywords: Discrete choice models; Random utility maximization; Decision makers; Utility function;Model formulation

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

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