Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models
Dimethyl ether (DME), derived from methanol, has been issued as an alternative to diesel and LPG. This study will continue the research of an optimized process control design for DME purification plants, specifically the methanol purification process. This way, water can be separated, and the main p...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-10-01
|
| Series: | ChemEngineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2305-7084/5/4/70 |
| _version_ | 1797505882688323584 |
|---|---|
| author | Abdul Wahid Monica Rikimata |
| author_facet | Abdul Wahid Monica Rikimata |
| author_sort | Abdul Wahid |
| collection | DOAJ |
| description | Dimethyl ether (DME), derived from methanol, has been issued as an alternative to diesel and LPG. This study will continue the research of an optimized process control design for DME purification plants, specifically the methanol purification process. This way, water can be separated, and the main product, methanol, can be recycled for DME synthesis. A setpoint-based linear model of a methanol–water purification system has been developed with four controlled variables (CV) with objectives to; maintain a separated liquid water stream in the bottom stage (Stage 30) of the distillation column for methanol–water separation at 11.22%, keep the purified liquid methanol at a condenser at 58.81 °C and 49.96% of level, and the last CV is the cooler in the distillate stream, to keep the purified methanol’s top product at 40.75 °C. To complete the model, a first order plus dead time (FOPDT) disturbance model is created against the inlet temperature and flow rate of the feed, the major cause of disturbances in the industry. Using a traditional proportional integral controller connected to each controlled variable, a multi-loop control system is formed with optimization and compared to the disturbance rejection of multivariable model predictive control (MMPC). The final improvement against the feed temperature and flow for CV1, CV2, CV3, and CV4 is shown by, respectively, Integral Absolute Error (IAE) values of 79.49%, 99.90%, 100%, and 99.99% and Integral Square Error (ISE) values of 97.1%, 100%, 99.99%, and 100%. |
| first_indexed | 2024-03-10T04:24:41Z |
| format | Article |
| id | doaj.art-4bbc8e1ad0ef460d85483c5f6e469a55 |
| institution | Directory Open Access Journal |
| issn | 2305-7084 |
| language | English |
| last_indexed | 2024-03-10T04:24:41Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ChemEngineering |
| spelling | doaj.art-4bbc8e1ad0ef460d85483c5f6e469a552023-11-23T07:40:34ZengMDPI AGChemEngineering2305-70842021-10-01547010.3390/chemengineering5040070Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance ModelsAbdul Wahid0Monica Rikimata1Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 1642, IndonesiaDepartment of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 1642, IndonesiaDimethyl ether (DME), derived from methanol, has been issued as an alternative to diesel and LPG. This study will continue the research of an optimized process control design for DME purification plants, specifically the methanol purification process. This way, water can be separated, and the main product, methanol, can be recycled for DME synthesis. A setpoint-based linear model of a methanol–water purification system has been developed with four controlled variables (CV) with objectives to; maintain a separated liquid water stream in the bottom stage (Stage 30) of the distillation column for methanol–water separation at 11.22%, keep the purified liquid methanol at a condenser at 58.81 °C and 49.96% of level, and the last CV is the cooler in the distillate stream, to keep the purified methanol’s top product at 40.75 °C. To complete the model, a first order plus dead time (FOPDT) disturbance model is created against the inlet temperature and flow rate of the feed, the major cause of disturbances in the industry. Using a traditional proportional integral controller connected to each controlled variable, a multi-loop control system is formed with optimization and compared to the disturbance rejection of multivariable model predictive control (MMPC). The final improvement against the feed temperature and flow for CV1, CV2, CV3, and CV4 is shown by, respectively, Integral Absolute Error (IAE) values of 79.49%, 99.90%, 100%, and 99.99% and Integral Square Error (ISE) values of 97.1%, 100%, 99.99%, and 100%.https://www.mdpi.com/2305-7084/5/4/70dimethyl etherdisturbancemethanolmulti-loopPI controller |
| spellingShingle | Abdul Wahid Monica Rikimata Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models ChemEngineering dimethyl ether disturbance methanol multi-loop PI controller |
| title | Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models |
| title_full | Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models |
| title_fullStr | Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models |
| title_full_unstemmed | Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models |
| title_short | Methanol–Water Purification Control Using Multi-Loop PI Controllers Based on Linear Set Point and Disturbance Models |
| title_sort | methanol water purification control using multi loop pi controllers based on linear set point and disturbance models |
| topic | dimethyl ether disturbance methanol multi-loop PI controller |
| url | https://www.mdpi.com/2305-7084/5/4/70 |
| work_keys_str_mv | AT abdulwahid methanolwaterpurificationcontrolusingmultilooppicontrollersbasedonlinearsetpointanddisturbancemodels AT monicarikimata methanolwaterpurificationcontrolusingmultilooppicontrollersbasedonlinearsetpointanddisturbancemodels |