Design Of A Model Predictive Control For A Multivariable Process

Abstract

Model Predictive Control is a process control technique that is used in process industries that predict the future behavior of the process state by predicting the change in the dependent variables of the modeled system. It can compute the future input at each step by minimizing a cost function on the manipulated and controlled variables. The main goal of this paper is to design a Model Predictive for a multivariable process. Here, the distillation column is used as a multivariable process. Finally, the settling time, overshoot, ISE, IAE, ITAE errors of MPC controller is compared with PID controller for both SISO and MIMO systems