Design and Development of Model Predictive Controller for Binary Distillation Column

Model Predictive Control (MPC) is an advanced process control technique used in process related industries that can predict the future behavior of the process state/output over the finite time horizon by predicting the change in the dependent variables of the modeled system that will be caused by changes in the independent variables. It can compute the future input signals at each step by minimizing a cost function under inequality constraints on the manipulated and/or controlled variables. The goal of this paper is to develop a Model Predictive Controller for constrained and unconstrained input/output, on SISO system as well as MIMO system (a non-linear binary distillation column). The objective is to maintain the specification of the product concentration outputs xB and xD (controlled variables) due to disturbance F (feed flow-process disturbance) and xF (feed concentration) with the inputs R and S (manipulated variables). In this paper, performance indices like settling time, overshoot, ISE, IAE and ITAE errors of MPC controller are compared with conventional multi loop PI controller for both SISO and MIMO systems.