Multivariable generalized predictive control of reactive distillation column process for biodiesel production

Most industrial control systems consist of a significant number loops. Generally, large processes are divided into many interconnected subsystems affecting each other, thus creating multivariable known as multiple–input multiple–output (MIMO) process. Generalized Predictive Control (GPC) based algorithm is most suitable for MIMO systems. In this study, multivariate nonlinear (NL) GPC and discrete–time PID calcium oxide catalyst–packed reactive distillation (RD) column used biodiesel production from waste cooking oil were investigated. Temperatures reaction reboiler sections controlled by using non–decoupled decoupled NLGPC algorithms. Feed flow rate with constant molar ratio heat duty parameters selected manipulating variables. All recommended methods, except non-decoupled NLGPC, have been found to perform satisfactorily reference tracking disturbance rejection in RD column. Consequently, the best results obtained NLGPC.