Adaptive system for regulating the drying process of cotton in drum dryers

This study addresses the formulation of self-adjusting control mechanisms for sustaining precise operational parameters throughout cotton fiber dehydration procedures. Key influential factors within the drying environment are systematically identified, with their mathematical relationships expressed through discrete transfer function formulations. An integrated adaptive monitoring system is designed, featuring autonomous parameter calibration capabilities that effectively counteract interactive disturbances among processing variables. The research proposes an innovative estimation algorithm based on recursive stochastic approximation principles, capable of managing additive measurement disturbances encountered in real-time monitoring applications. System parameters are derived through comprehensive energy and mass balance calculations performed at nominal operating conditions. Additionally, a sophisticated methodology for developing adaptive mathematical representations of cotton drying dynamics is established, facilitating accurate prediction of complex process behavior characterized by probabilistic variations. The approach implements continuous parameter updating through systematic recalibration of model estimates.

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Publication Details

Published
2025-09-23
DOI
https://doi.org/10.1117/12.3077871
Primary Topic
Textile materials and evaluations
Type
article
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article

Adaptive system for regulating the drying process of cotton in drum dryers

Y. Mamasodikov, Davronbek Khalmatov, Nodira Mamasodikova, Anvarjon R. Boymirzayev et al.
Textile materials and evaluations
article

Adaptive system for regulating the drying process of cotton in drum dryers

Y. Mamasodikov, Davronbek Khalmatov, Nodira Mamasodikova, Anvarjon R. Boymirzayev, Umida Y. Xusanova
article en

Abstract

This study addresses the formulation of self-adjusting control mechanisms for sustaining precise operational parameters throughout cotton fiber dehydration procedures. Key influential factors within the drying environment are systematically identified, with their mathematical relationships expressed through discrete transfer function formulations. An integrated adaptive monitoring system is designed, featuring autonomous parameter calibration capabilities that effectively counteract interactive disturbances among processing variables. The research proposes an innovative estimation algorithm based on recursive stochastic approximation principles, capable of managing additive measurement disturbances encountered in real-time monitoring applications. System parameters are derived through comprehensive energy and mass balance calculations performed at nominal operating conditions. Additionally, a sophisticated methodology for developing adaptive mathematical representations of cotton drying dynamics is established, facilitating accurate prediction of complex process behavior characterized by probabilistic variations. The approach implements continuous parameter updating through systematic recalibration of model estimates.

Ferghana Polytechnical Institute (UZ), Ferghana State University (UZ), Tashkent Institute of Textile and Light Industry (UZ)
Openalex Percentile: Top 77%
Textile materials and evaluations
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