Comparison of Linear Quadratic Regulator and Model Predictive Control Based Algorithms in Continuous Production

The integration of Industry 4.0 into manufacturing processes necessitates the automation of complex, large-scale operations within cyber-physical systems (CPSs). Pharmaceutical manufacturing, in particular, requires a transition from traditional batch processing to continuous manufacturing to achiev...

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Published inBulletin of the Polytechnic Institute of Iași. Electrical Engineering, Power Engineering, Electronics Section Vol. 69; no. 2; pp. 9 - 34
Main Authors Chindruş, Amelia, Copoţ, Dana, Căruntu, Constantin-Florin
Format Journal Article
LanguageEnglish
Published Iasi Sciendo 01.06.2023
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Subjects
continuous manufacturing
Cyber-physical system
Industry 4.0
linear quadratic regulator
model predictive control
Online AccessGet full text
ISSN2537-2726
1223-8139
2537-2726
DOI10.2478/bipie-2023-0007

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Abstract The integration of Industry 4.0 into manufacturing processes necessitates the automation of complex, large-scale operations within cyber-physical systems (CPSs). Pharmaceutical manufacturing, in particular, requires a transition from traditional batch processing to continuous manufacturing to achieve seamless integration with CPSs. This paper explores the comparison between two control strategies for pharmaceutical tablet production: the linear quadratic regulator (LQR) method and an established model predictive control (MPC) algorithm. The LQR method focuses on providing optimal stability and robustness for the plant’s operations, particularly through centralized management of key process units in the dry granulation process. A detailed plant model is utilized to test the performance of the LQR controller, with results benchmarked against those obtained using the MPC algorithm.
AbstractList The integration of Industry 4.0 into manufacturing processes necessitates the automation of complex, large-scale operations within cyber-physical systems (CPSs). Pharmaceutical manufacturing, in particular, requires a transition from traditional batch processing to continuous manufacturing to achieve seamless integration with CPSs. This paper explores the comparison between two control strategies for pharmaceutical tablet production: the linear quadratic regulator (LQR) method and an established model predictive control (MPC) algorithm. The LQR method focuses on providing optimal stability and robustness for the plant’s operations, particularly through centralized management of key process units in the dry granulation process. A detailed plant model is utilized to test the performance of the LQR controller, with results benchmarked against those obtained using the MPC algorithm.
Author Chindruş, Amelia
Copoţ, Dana
Căruntu, Constantin-Florin
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  organization: “Gheorghe Asachi” Technical University of Iași, Romania, Faculty of Automatic Control and Computer Engineering
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SubjectTerms continuous manufacturing
Cyber-physical system
Industry 4.0
linear quadratic regulator
model predictive control
Title Comparison of Linear Quadratic Regulator and Model Predictive Control Based Algorithms in Continuous Production
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