LAPSE:2023.35333
Published Article
LAPSE:2023.35333
Predictive Control Strategy for Continuous Production Systems: A Comparative Study with Classical Control Approaches Using Simulation-Based Analysis
April 28, 2023
Due to today’s technological development and information progress, an increasing number of physical systems have become interconnected and linked together through communication networks, thus resulting in Cyber-Physical Systems (CPSs). Continuous manufacturing, which involves the manufacture of products without interruption, has become increasingly important in many industries, including the pharmaceutical and chemical industries. CPSs can be used to control and monitor the production process, which is essential in enabling continuous manufacturing. This paper is focused on the modeling and control of physical systems required in tablet production using dry granulation. Tablets are a type of oral dosage form that is commonly used in the pharmaceutical industry. They are solid, compressed forms of medication that are formulated to release the active ingredients in a manner that allows for optimal absorption and efficacy. Thus, a model predictive control (MPC) strategy is applied to a plant model to test the designed controller and to analyze the obtained performances. The simulation results are compared with those obtained using other control algorithms, linear quadratic regulator (LQR) and proportional-integral-derivative (PID), applied to the same plant model. The results showed that the predictive control strategy performed significantly better than the other two control strategies.
Keywords
continuous manufacturing, cyber-physical system, linear quadratic regulator, Model Predictive Control, proportional-integral-derivative controller
Suggested Citation
Chindrus A, Copot D, Caruntu CF. Predictive Control Strategy for Continuous Production Systems: A Comparative Study with Classical Control Approaches Using Simulation-Based Analysis. (2023). LAPSE:2023.35333
Author Affiliations
Chindrus A: Department of Automatic Control and Applied Informatics, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania
Copot D: Department of Electromechanical, Systems and Metal Engineering, Ghent University, 9000 Ghent, Belgium [ORCID]
Caruntu CF: Department of Automatic Control and Applied Informatics, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania [ORCID]
Journal Name
Processes
Volume
11
Issue
4
First Page
1258
Year
2023
Publication Date
2023-04-19
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr11041258, Publication Type: Journal Article
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LAPSE:2023.35333
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doi:10.3390/pr11041258
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Apr 28, 2023
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