SYNTHESIS OF NEURO-FUZZY NETWORK FOR STABILIZING TEMPERATURE IN PROCESS OF CONTINUOUS STERILIZATION

To synthesize a neuro-fuzzy network of stabilizing temperature there is a view on the development of a base of rules for a fuzzy controller taking into account the optimal object management and training of a hybrid neural network. The optimal trajectory was accepted as the performance-optimal (detec...

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Bibliographic Details
Main Author: Elena Valerievna Lubentsova
Format: Article
Language:Russian
Published: North Caucasus Federal University 2022-05-01
Series:Вестник Северо-Кавказского федерального университета
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Online Access:https://vestnikskfu.elpub.ru/jour/article/view/1688
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Summary:To synthesize a neuro-fuzzy network of stabilizing temperature there is a view on the development of a base of rules for a fuzzy controller taking into account the optimal object management and training of a hybrid neural network. The optimal trajectory was accepted as the performance-optimal (detected by the maximum principle) management for a closed loop system for automatic management. There has been a transition made from the temporary area where the optimal management has been found, to the phase plane of the system, which allowed a direct use of the solution to develop a rule base for a fuzzy controller. There has been a neuro-fuzzy network (Adaptive-Network-Based Fuzzy Inference System - ANFIS) employed to develop a temperature stabilization system for sterilization with two management influences.
ISSN:2307-907X