• Vol 7, No 6 (2016)
  • Chemical Engineering

Improved Multi-model Predictive Control to Reject Very Large Disturbances on a Distillation Column

Abdul Wahid, Arshad Ahmad


Publish at : 31 Oct 2016 - 00:00
IJtech : IJtech Vol 7, No 6 (2016)
DOI : https://doi.org/10.14716/ijtech.v7i6.3524

Cite this article as:
Wahid, A.., & Ahmad , A.. 2016. Improved Multi-model Predictive Control to Reject Very Large Disturbances on a Distillation Column. International Journal of Technology. Volume 7(6), pp.962-971
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Abdul Wahid Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Arshad Ahmad Department of Chemical Engineering, Faculty of Chemical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia Center of Hydrogen Energy, Institute of Future Energy, Universit
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Abstract

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.

Distillation; Multi-model; Predictive; Very large disturbance