scholarly journals DETERMINATION OF FORMAL SIGNS FOR INDICATORS OF EFFICIENCY EVALUATION OF CONTROLLED SYSTEMS OPERATIONS

2017 ◽  
Vol 5 ◽  
pp. 57-64
Author(s):  
Olga Serdiuk
Keyword(s):  
General Model ◽  
Economic Effect ◽  
Practical Importance ◽  
Model Parameters ◽  
Controlled System ◽  
Operational Process ◽  
Controlled Systems ◽  
Input And Output ◽  
Program Designer

Research connected with studying of efficiency assessment possibility of system operation simple model using its general model parameters and establishing of operation general model objects as efficiency formula`s formal signs is presented in the article. To conduct research, model of controlled system was created, structure of which is implemented as software product. Peculiarity of this model is possibility of carrying out experimental study, as result of which it is possible to detect changes in parameters of number of system operations under different control regimes. As result of research, it was established that it is impossible to make comparative assessment between operations, which conducted in different control regimes, applying quantitative characteristics of input and output operational process parameters. During creation of converting class system model structure, concept of operation reduction to its simple general model has been used. Model of program designer provides integration of cost parameters of input and output products by means of which, opportunity for efficiency determination of operations, functioning at different control modes is investigated. Analysis of operational process estimation results has shown that operation general model objects are formal signs of operations efficiency formula. Different modes of optimum control to which have pointed extrema of several indicators have revealed absence problem systemically reasonable verification method of applied estimated indicators regarding their use as optimization criterion. Practical importance of this research is that using presented program designer of controlled system and cybernetic approach allow apply results of research on all types of controlled systems. It promotes the optimization issue solution in finding of optimum mode of executive systems functioning and obtaining maximum economic effect of enterprise.

Experience with the IMMa tyre test bench for the determination of tyre model parameters using genetic techniques

2005 ◽  
Vol 43 (sup1) ◽  
pp. 253-266 ◽  
Author(s):  
J. A. Cabrera ◽  
A. Ortiz ◽  
E. Carabias ◽  
A. Simón
Keyword(s):  
Test Bench ◽  
Model Parameters ◽  
Tyre Model ◽  
Genetic Techniques

Reliability of nonlinear stochastic controlled systems considering the dynamics of sensors and actuators

2021 ◽  
pp. 107754632110037
Author(s):  
Sun Jiaojiao ◽  
Xia Lei ◽  
Ying Zuguang ◽  
Huan Ronghua ◽  
Zhu Weiqiu
Keyword(s):  
Closed Loop ◽  
First Passage Time ◽  
Hamiltonian Function ◽  
Small Time ◽  
Kolmogorov Equation ◽  
Sensors And Actuators ◽  
First Passage ◽  
Controlled System ◽  
Main Structure ◽  
Controlled Systems

A closed-loop controlled system usually consists of the main structure, sensors, and actuators. The dynamics of sensors and actuators may influence the motion of the main structure. This article presents an analytical study on the first-passage reliability of a nonlinear stochastic controlled system under the consideration of the dynamics of sensors and actuators. The coupled dynamic equations of the controlled systems with sensors and actuators are first given, which are further integrated into a controlled, randomly excited, dissipated Hamiltonian system. By applying the stochastic averaging method for quasi-Hamiltonian systems, a one-dimensional averaged differential equation for the Hamiltonian function is obtained. The backward Kolmogorov equation associated with the averaged equation is then derived for the first-passage reliability analysis, from which the approximate reliability function and probability density of first-passage time are obtained. The accuracy of the proposed procedure is demonstrated by an example. A comparative analysis of the reliability of the system with/without sensors and actuators is carried out, which indicates that ignoring sensors and actuators will make underestimation of the reliability of the closed-loop system with small time. However, when time increases, there appears the opposite trend. Our findings provide a reference for control strategy design.

scholarly journals Maximum Likelihood Estimation of the VAR(1) Model Parameters with Missing Observations

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Helena Mouriño ◽  
Maria Isabel Barão
Keyword(s):  
Stochastic Process ◽  
Missing Data ◽  
Maximum Likelihood ◽  
Moving Average ◽  
Practical Importance ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Missing Observations ◽  
Data Set ◽  
The Impact

Missing-data problems are extremely common in practice. To achieve reliable inferential results, we need to take into account this feature of the data. Suppose that the univariate data set under analysis has missing observations. This paper examines the impact of selecting an auxiliary complete data set—whose underlying stochastic process is to some extent interdependent with the former—to improve the efficiency of the estimators for the relevant parameters of the model. The Vector AutoRegressive (VAR) Model has revealed to be an extremely useful tool in capturing the dynamics of bivariate time series. We propose maximum likelihood estimators for the parameters of the VAR(1) Model based on monotone missing data pattern. Estimators’ precision is also derived. Afterwards, we compare the bivariate modelling scheme with its univariate counterpart. More precisely, the univariate data set with missing observations will be modelled by an AutoRegressive Moving Average (ARMA(2,1)) Model. We will also analyse the behaviour of the AutoRegressive Model of order one, AR(1), due to its practical importance. We focus on the mean value of the main stochastic process. By simulation studies, we conclude that the estimator based on the VAR(1) Model is preferable to those derived from the univariate context.

scholarly journals The seven sisters DANCe

2018 ◽  
Vol 612 ◽  
pp. A70 ◽  
Author(s):  
J. Olivares ◽  
E. Moraux ◽  
L. M. Sarro ◽  
H. Bouy ◽  
A. Berihuete ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Model Comparison ◽  
Precise Determination ◽  
Model Parameters ◽  
Data Sets ◽  
Adequate Model ◽  
Comparison Results ◽  
Bayesian Evidence ◽  
Mass Segregation

Context. Membership analyses of the DANCe and Tycho + DANCe data sets provide the largest and least contaminated sample of Pleiades candidate members to date. Aims. We aim at reassessing the different proposals for the number surface density of the Pleiades in the light of the new and most complete list of candidate members, and inferring the parameters of the most adequate model. Methods. We compute the Bayesian evidence and Bayes Factors for variations of the classical radial models. These include elliptical symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions for each set of model parameters. Results. We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon King’s model, although the Generalised King model introduced here has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band is strongly supported in all our models. Conclusions. We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such a study will allow for more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.

scholarly journals Junction Parameter Extraction for Electronic Device Characterization

2004 ◽  
Vol 27 (2) ◽  
pp. 61-67
Author(s):  
S. Dib ◽  
C. Salame ◽  
N. Toufik ◽  
A. Khoury ◽  
F. Pélanchon ◽  
...  
Keyword(s):  
Electronic Device ◽  
Control Process ◽  
Parameter Extraction ◽  
Exponential Model ◽  
Voltage Characteristic ◽  
Model Parameters ◽  
Current Voltage Characteristic ◽  
Device Characterization ◽  
Current Voltage

A new method for the extraction of junction parameters from a description of the current–voltage characteristic is developed. A simulation is performed and a high accuracy is obtained for the determination of the singleexponential model parameters. The method is easy to implement in a control process for device characterization. An application, achieved to observe the degradation of the emitter–base junction of a bipolar transistor during an aging experiment, shows that the evolutions of the single exponential model parameters versus time introduce a means for degradation quantification.

Device Modeling of a-Si:H Alloy Solar Cells: Calibration Procedure for Determination of Model Input Parameters

1998 ◽  
Vol 507 ◽  
Author(s):  
M. Zeman ◽  
R.A.C.M.M. Van Swaaij ◽  
E. Schroten ◽  
L.L.A. Vosteen ◽  
J.W. Metselaar
Keyword(s):  
Solar Cell ◽  
Material Properties ◽  
Calibration Procedure ◽  
Model Parameters ◽  
Model Input ◽  
A Value ◽  
Input Parameters ◽  
Simulated Material ◽  
Good Agreement

ABSTRACTA calibration procedure for determining the model input parameters of standard a-Si:H layers, which comprise a single junction a-Si:H solar cell, is presented. The calibration procedure consists of: i) deposition of the separate layers, ii) measurement of the material properties, iii) fitting the model parameters to match the measured properties, iv) simulation of test devices and comparison with experimental results. The inverse modeling procedure was used to extract values of the most influential model parameters by fitting the simulated material properties to the measured ones. In case of doped layers the extracted values of the characteristic energies of exponentially decaying tail states are much higher than the values reported in literature. Using the extracted values of model parameters a good agreement between the measured and calculated characteristics of a reference solar cell was reached. The presented procedure could not solve directly an important issue concerning a value of the mobility gap in a-Si:H alloys.

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