Improved multi-model predictive control to reject very large disturbances on a distillation column
A multi model predictive control and proportional-integral controller switching (MMPCPIS) approach is proposed to control a nonlinear distillation column. The study was implemented on a multivariable nonlinear distillation column (Column A). The setpoint tracking and disturbance rejection performanc...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Engineering Universitas Indonesia
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/74597/1/ArshadAhmad2016_Improvedmulti-modelpredictivecontrol.pdf http://eprints.utm.my/id/eprint/74597/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995421902&doi=10.14716%2fijtech.v7i6.3524&partnerID=40&md5=a11882d1cde721a255948a327ae0e444 |
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| Summary: | A multi model predictive control and proportional-integral controller switching (MMPCPIS) approach is proposed to control a nonlinear distillation column. The study was implemented on a multivariable nonlinear distillation column (Column A). The setpoint tracking and disturbance rejection performances of the proposed MMPCPIS were evaluated and compared to a proportional-integral (PI) controller and the hybrid controller (HC). MMPCPIS developed to overcome the HC's limitation when dealing with very large disturbance changes (50%). MMPCPIS provided improvements by 27% and 31% of the ISE (integral of square error) for feed flow rate and feed composition disturbance changes, respectively, compared with the PI controller, and 24% and 54% of the ISE for feed flow rate and feed composition disturbance change, respectively, compared with HC. |
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