Internal model control of cumene process using analytical rules and evolutionary computation
Cumene is a precursor for producing many organic chemicals and is thinner in paints and lacquers. Its production process involves one of the large-scale manufacturing processes with complex kinetics. Different classical control strategies have been implemented and compared in this process for the cu...
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| Format: | Article |
| Language: | English |
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Association of the Chemical Engineers of Serbia
2024-01-01
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| Series: | Chemical Industry and Chemical Engineering Quarterly |
| Subjects: | |
| Online Access: | https://doiserbia.nb.rs/img/doi/1451-9372/2024/1451-93722300014M.pdf |
| _version_ | 1827288432388341760 |
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| author | Lakshmanan Vinila Mundakkal Kallingal Aparna Sreekumar Sreepriya |
| author_facet | Lakshmanan Vinila Mundakkal Kallingal Aparna Sreekumar Sreepriya |
| author_sort | Lakshmanan Vinila Mundakkal |
| collection | DOAJ |
| description | Cumene is a precursor for producing many organic chemicals and is thinner in paints and lacquers. Its production process involves one of the large-scale manufacturing processes with complex kinetics. Different classical control strategies have been implemented and compared in this process for the cumene reactor. As a system with large degrees of freedom, a novel approach for extracting the state space model from the COMSOL Multiphysics implementation of the system is adopted here. Internal Modern Control (IMC) based PI and PID controllers are derived for the system. The system is reduced to the FOPDT and SOPDT model structure to derive the controller setting using Skogestad half rules. The integral time is modified for excellent set point tracking and faster disturbance rejection. From the analysis, it can be stated that the PI controller suits more for this specific process. The particle swarm optimization (PSO) algorithm, an evolutionary computation technique, is also used to tune the PI settings. The PI controllers with IMC, Zeigler Nichols, and PSO tuning are compared, and it can be concluded that the PSO PI controller settles at 45 s without any oscillations and settles down faster for the disturbance of magnitude 0.5 applied at t = 800 s. However, it is computationally intensive compared to other controller strategies. |
| first_indexed | 2024-04-24T11:30:49Z |
| format | Article |
| id | doaj.art-483f45b0757a402c8cc1c893121d368a |
| institution | Directory Open Access Journal |
| issn | 1451-9372 2217-7434 |
| language | English |
| last_indexed | 2024-04-24T11:30:49Z |
| publishDate | 2024-01-01 |
| publisher | Association of the Chemical Engineers of Serbia |
| record_format | Article |
| series | Chemical Industry and Chemical Engineering Quarterly |
| spelling | doaj.art-483f45b0757a402c8cc1c893121d368a2024-04-10T10:15:37ZengAssociation of the Chemical Engineers of SerbiaChemical Industry and Chemical Engineering Quarterly1451-93722217-74342024-01-01302899810.2298/CICEQ220711014M1451-93722300014MInternal model control of cumene process using analytical rules and evolutionary computationLakshmanan Vinila Mundakkal0Kallingal Aparna1Sreekumar Sreepriya2Department of Chemical Engineering, National Institute of Technology Calicut, Kozhikode, Kerala, India + Department of Robotics and Automation, Adi Shankara Institute of Engineering and Technology, Kalady, IndiaDepartment of Chemical Engineering, National Institute of Technology Calicut, Kozhikode, Kerala, IndiaDepartment of Chemical Engineering, National Institute of Technology Calicut, Kozhikode, Kerala, India + Department of Robotics and Automation, Adi Shankara Institute of Engineering and Technology, Kalady, IndiaCumene is a precursor for producing many organic chemicals and is thinner in paints and lacquers. Its production process involves one of the large-scale manufacturing processes with complex kinetics. Different classical control strategies have been implemented and compared in this process for the cumene reactor. As a system with large degrees of freedom, a novel approach for extracting the state space model from the COMSOL Multiphysics implementation of the system is adopted here. Internal Modern Control (IMC) based PI and PID controllers are derived for the system. The system is reduced to the FOPDT and SOPDT model structure to derive the controller setting using Skogestad half rules. The integral time is modified for excellent set point tracking and faster disturbance rejection. From the analysis, it can be stated that the PI controller suits more for this specific process. The particle swarm optimization (PSO) algorithm, an evolutionary computation technique, is also used to tune the PI settings. The PI controllers with IMC, Zeigler Nichols, and PSO tuning are compared, and it can be concluded that the PSO PI controller settles at 45 s without any oscillations and settles down faster for the disturbance of magnitude 0.5 applied at t = 800 s. However, it is computationally intensive compared to other controller strategies.https://doiserbia.nb.rs/img/doi/1451-9372/2024/1451-93722300014M.pdfimc piimc pidskogestad half rulezeigler nicholspso pi |
| spellingShingle | Lakshmanan Vinila Mundakkal Kallingal Aparna Sreekumar Sreepriya Internal model control of cumene process using analytical rules and evolutionary computation Chemical Industry and Chemical Engineering Quarterly imc pi imc pid skogestad half rule zeigler nichols pso pi |
| title | Internal model control of cumene process using analytical rules and evolutionary computation |
| title_full | Internal model control of cumene process using analytical rules and evolutionary computation |
| title_fullStr | Internal model control of cumene process using analytical rules and evolutionary computation |
| title_full_unstemmed | Internal model control of cumene process using analytical rules and evolutionary computation |
| title_short | Internal model control of cumene process using analytical rules and evolutionary computation |
| title_sort | internal model control of cumene process using analytical rules and evolutionary computation |
| topic | imc pi imc pid skogestad half rule zeigler nichols pso pi |
| url | https://doiserbia.nb.rs/img/doi/1451-9372/2024/1451-93722300014M.pdf |
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