Identification and control of large transport delay temperature process

In this paper different design methods for control of large transport delay systems are considered. Processes with large transport delay often present themselves as challenge for developing adequate and functional control. Due to the nature of these processes it is often not time efficient, nor optimal to project control on the process itself, thus did the authors opt for developing a control on a model and comparing the results with real process. Two popular methods were compared for control of black box system with large transport delay. Up first simple and widespread PID controller and then more complex, but better suited for large transport delay, Smith predictor. Results were compared both in simulation and on process itself.

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Publication Details

Published
2025-08-04
DOI
https://doi.org/10.69994/12ic25007
Primary Topic
Neural Networks and Applications
Type
article
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Identification and control of large transport delay temperature process

Ivan Petrović, Marko Milivojčević, Goran Dikić, Slobodan Drašković et al.
Neural Networks and Applications
article

Identification and control of large transport delay temperature process

Ivan Petrović, Marko Milivojčević, Goran Dikić, Slobodan Drašković, Željko Đurović
article en

Abstract

In this paper different design methods for control of large transport delay systems are considered. Processes with large transport delay often present themselves as challenge for developing adequate and functional control. Due to the nature of these processes it is often not time efficient, nor optimal to project control on the process itself, thus did the authors opt for developing a control on a model and comparing the results with real process. Two popular methods were compared for control of black box system with large transport delay. Up first simple and widespread PID controller and then more complex, but better suited for large transport delay, Smith predictor. Results were compared both in simulation and on process itself.

Openalex Percentile: Top 86%
Neural Networks and Applications
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