Design of Simplified Model Predictive Controller

There are a lot of control strategies being derived from model predictive control
(MPC) concept such as Internal Model Control (IMC). In MPC, inverse of process
transfer functions is required in obtaining the control law. However, an exact
inverse transfer function can never be obtained due to certain conditions that lead
to physically unrealizable processes such as dead time, numerator dynamics,
constraints and model mismatch. New technique known as Simplified Model
Predictive Control (SMPC) was developed which solves the problem of acquiring
exact inverse response of a model to predict the future outputs of the
corresponding inputs. SMPC control algorithm is an efficient and simple method
for multivariable control. SMPC algorithm for 2 x 2 system of distillation column
model developed by Saniye and Suleiman (2011) is designed using MATLAB
simulation. This SMPC only concerns for set point tracking of the model.