@inproceedings{db060f14d7ce4ac8957b35c29dfb1654,
title = "Residence time regulation in chemical processes: Local optimal control realization by differential neural networks",
abstract = "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.",
keywords = "Differential neural networks, Local optimal control, Ozonation processes, Uncertain systems",
author = "Tatyana Poznyak and Isaac Chairez and Alexander Poznyak",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 15th International Symposium on Neural Networks, ISNN 2018 ; Conference date: 25-06-2018 Through 28-06-2018",
year = "2018",
doi = "10.1007/978-3-319-92537-0_85",
language = "Ingl{\'e}s",
isbn = "9783319925363",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "745--756",
editor = "Changyin Sun and Tuzikov, {Alexander V.} and Tingwen Huang and Jiancheng Lv",
booktitle = "Advances in Neural Networks - ISNN 2018 - 15th International Symposium on Neural Networks, ISNN 2018, Proceedings",
address = "Alemania",
}