Multivariable system identification and generic model control of a laboratory scale packed distillation column

In this study, multivariable generic model control (MGMC) structure has been proposed to control of the packed distillation column. Top and bottom product temperatures of the packed distillation column were selected as controlled variables and reflux ratio and reboiler heat duty as manipulated variables, respectively. Regulator problem was considered for experimental control studies. Feed mole fraction and feed temperature were chosen as load variables. Two types black box models, which were linear and non-linear was used for generic model control to control of packed distillation. A multivariable non-linear autoregressive moving average with eXternal input and auto-recursive extensive models were used for the linear black box model. The system identification toolbox in MATLAB was applied to estimate of the discrete models. Non-linear black box model for MGMC has better performance over linear black box model in the case of load disturbances.