Comparison of Linear Quadratic Regulator and Model Predictive Control Based Algorithms in Continuous Production
Publicado en línea: 30 ago 2024
Páginas: 9 - 34
Recibido: 10 feb 2023
Aceptado: 03 jun 2024
DOI: https://doi.org/10.2478/bipie-2023-0007
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© 2023 Amelia Chindruş et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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.