Residence time regulation in chemical processes: Local optimal control realization by differential neural networks

Tatyana Poznyak, Isaac Chairez, Alexander Poznyak

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

A new method to design local optimal controller for uncertain system governed by continuous flow transformations (CFT) is presented. The on-line solution of the adaptive gains adjusting a linear control form yields the calculus of the sub-optimal controller. A special performance index, oriented to solve the transient evolution of CFT systems, is proposed. The class of systems considered in this study is highly uncertain: some components of chemical reactions are no measurable on line and then, they cannot be used in the controller realization. The recovering of this information was executed by a differential neural network (DNN) structure. The ozonation process of a single contaminant (as the particular example of CFT) is evaluated in detail using the control design proposed here.

Idioma originalInglés
Título de la publicación alojadaAdvances in Neural Networks - ISNN 2018 - 15th International Symposium on Neural Networks, ISNN 2018, Proceedings
EditoresChangyin Sun, Alexander V. Tuzikov, Tingwen Huang, Jiancheng Lv
EditorialSpringer Verlag
Páginas745-756
Número de páginas12
ISBN (versión impresa)9783319925363
DOI
EstadoPublicada - 2018
Evento15th International Symposium on Neural Networks, ISNN 2018 - Minsk, Bielorrusia
Duración: 25 jun. 201828 jun. 2018

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen10878 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia15th International Symposium on Neural Networks, ISNN 2018
País/TerritorioBielorrusia
CiudadMinsk
Período25/06/1828/06/18

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