Article

Cover

Title

Nejroidentification and nejroprognozirovanie parameters of the ionized plasma on the basis of neural networks with indistinct logic

Author

V.M. Buyankin

Organization

Bauman Moscow State Technical University
Moscow, Russia

Abstract

Article is devoted system engineering of multiple parametre predicted identification of the ionised plasma on the basis of neural networks with indistinct logic. Modern development of a science and technics makes more and more high demands to accuracy of control systems of ionic-plasma installations. The ionised plasma represents multidimensional technical object with nonlinear and indistinct characteristics. Physical processes in the ionised plasma are difficult. Stability and accuracy of an ionic-plasma dusting to some extent influences about 60 interconnected parametres. Many traditional mathematical models of the ionised plasma in many cases are inadequate to real process. The major factors constraining wide introduction of systems of identification of ionised plasma, are the insufficient information about static and dynamic characteristics; low accuracy of the functional dependences describing process of a dusting; absence of methods, techniques and algorithms of management. The offered multiple parametre system nejrodentification with the forecast allows to reach split-hair accuracy of the analysis of nonlinear indistinct static and dynamic parametres and characteristics of the ionised plasma.

Keywords

the ionised plasma, nejrodentification, nonlinear characteristics, fuzzy characteristics

For citing this article

Buyankin V.M. Nejroidentification and nejroprognozirovanie parameters of the ionized plasma on the basis of neural networks with indistinct logic // The Research of the Science City, 2014, no. 4, pp. 28-34.

This Article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).