Improved Multi-model Predictive Control to Reject Very Large Disturbances on a Distillation Column
Published at : 29 Oct 2016
Volume : IJtech
Vol 7, No 6 (2016)
DOI : https://doi.org/10.14716/ijtech.v7i6.3524
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
| 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 |
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