METHOD OF IDENTIFICATION OF MODELS OF OBJECTS WITH DISTRIBUTED PARAMETERS WITH A SPATIALLY DISTRIBUTED CONTROL BASED ON INTERVAL DATA ANALYSIS
Науковий журнал «Радіоелектроніка, інформатика, управління»
Переглянути архів Інформація| Поле | Співвідношення | |
| ##plugins.schemas.marc.fields.042.name## |
dc |
|
| ##plugins.schemas.marc.fields.245.name## |
METHOD OF IDENTIFICATION OF MODELS OF OBJECTS WITH DISTRIBUTED PARAMETERS WITH A SPATIALLY DISTRIBUTED CONTROL BASED ON INTERVAL DATA ANALYSIS |
|
| ##plugins.schemas.marc.fields.720.name## |
Dyvak, M. P.; Ternopil National Economic University Porplytsya, N. P.; Ternopil National Economic University Maslyiak, Y. B.; Ternopil National Economic University Pukas, A. V.; Ternopil National Economic University Melnyk, A. M.; Ternopil National Economic University |
|
| ##plugins.schemas.marc.fields.653.name## |
Interval data analysis; structure-parametric identification; artificial bee colony algorithm |
|
| ##plugins.schemas.marc.fields.520.name## |
<p>Context. There are developed a number of methods to build models of objects with distributed parameters in the system identification theory. The basis of mathematical models of such objects are the systems of partial differential equations or their difference analogs. Therewith, for the synthesis of difference analog the methods of structural and parametric identification must be used. Mainly, such methods are based on random experimental data and measurement errors are not taken into account. When the measurement errors are taken into account we obtain data in interval form.Recently, for solving the tasks of structure identification of mathematical models the honey bee behavioral models are used, which are called the artificial bee colony algorithms (ABCA) in the literature. At the same time, the cases of structure identification of mathematical models based on interval data analysis when the object with distributed parameters includes spatially distributed control factors are not considered in the literature, but are relevant for the tasks of modeling of spatially distribution of pollutant concentrations in the atmosphere and temperature-controlled drying tasks etc.</p><p>Objective is adaptation of known ABCA methods for solving task of structure and parametric identification of models of objects with distributed parameters with spatially distributed control taken into account in addition.</p><p>Method. Structure and parametric identification has been implemented based on interval data analysis. In proposed method the operators of model structure synthesis, in contrast to existing methods, are built using the swarm intelligence, particularly based on artificial bee colony algorithm.</p><p>Results. An example of applying the method for task of modeling of drywall drying process in the final stage of its production is shown. Two modes of representation of spatially distributed control in kind of temperature field in drying oven were modeled. A mathematical model adequately reflects the humidity distribution in the drywall sheets when implementing its drying process.</p><p>Conclusions. The method for identification of interval models of objects with distributed parameters for the case of spatially distributed control was proposed. The operators of model structure synthesis, in contrast to existing methods, are built using the swarm intelligence. An important feature of the proposed method is its ability to efficiently “bypass” local minima, scilicet reject those sets of structural elements of the model that do not provide its prognostic properties, or lead to very high complexity.</p> |
|
| ##plugins.schemas.marc.fields.260.name## |
Zaporizhzhya National Technical University 2017-11-09 11:20:22 |
|
| ##plugins.schemas.marc.fields.856.name## |
application/pdf http://ric.zntu.edu.ua/article/view/112469 |
|
| ##plugins.schemas.marc.fields.786.name## |
Radio Electronics, Computer Science, Control; No 2 (2017): Radio Electronics, Computer Science, Control |
|
| ##plugins.schemas.marc.fields.546.name## |
uk |
|
| ##plugins.schemas.marc.fields.540.name## |
Copyright (c) 2017 M. P. Dyvak, N. P. Porplytsya ., Y. B. Maslyiak, A. V. Pukas, A. M. Melnyk |
|