Neural network based semi-empirical models for dynamical systems described by differential-algebraic equations
| Autor: | D. S. Kozlov, Yu. V. Tiumentsev |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
General Computer Science
Dynamical systems theory Artificial neural network Computer science Empirical modelling Field (mathematics) 02 engineering and technology Dynamical system 01 natural sciences Electronic Optical and Magnetic Materials Linear dynamical system 010309 optics Nonlinear system 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Applied mathematics 020201 artificial intelligence & image processing Electrical and Electronic Engineering Differential algebraic equation Simulation |
| Zdroj: | Optical Memory and Neural Networks. 24:279-287 |
| ISSN: | 1934-7898 1060-992X |
| DOI: | 10.3103/s1060992x15040049 |
| Popis: | We analyzed the problem of mathematical modeling and computer simulation of nonlinear controlled dynamical systems usually described by differential-algebraic equations. The problem is proposed to be solved in the framework of the semi-empirical approach combining theoretical knowledge for the plant with training tools of artificial neural network field. The results are presented for a semi-empirical model that simulate the reentry hypersonic vehicle and confirm the efficiency of this approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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