Abstract:
This thesis investigates the model predictive control (MPC) of an internally heat integrated pressure-swing distillation (IHIPSD) process for bioethanol separation, in order to increase process control performance. The linear state-space model of the IHIPSD process is developed and used as the process model in the MPC. The process simulation is carried out by commercial software.
The methodology is started by developing the linear state space model of the IHIPSD process which is used as the process model in the MPC. Secondly, the model predictive controller is designed, in order to increase process control performance. Thirdly, process control performance is evaluated by applying disturbances into the process using an integral of absolute value of error (IAE).
The simulation results show that MPC gives better overall control performance than conventional control (PID control). In detail, for feed flow step disturbances, conventional control gives slightly better performance than MPC. However, for temperature and feed composition step disturbances, MPC gives better performances than conventional control.