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This study discusses the performance of an MPC controller that was designed based on an FCCU dynamic model previously developed from plant data using PRBS testing. The model describes the concentration of oxygen in flue gas in terms of air flow-rate entering the regenerator, fresh feed entering the FCCU unit, feed temperature and reactor temperature. Set point tracking and regulatory MPC control of the process were accomplished with two manipulated variables. Besides, the impact of the constraints and weight matrices on the process performance will be discussed, as well as the MPC controller ability to reject stochastic disturbances in the feed and reactor temperatures.

For product quality purposes, the drying of some delicate materials is not easily realizable and requires a tight well-designed control scheme. This study presents control results for the drying of a thin fiber sheet moving through an electric infrared dryer. The drying process dynamics is described by a minimum realization linear model that is used to develop a model predictive controller (MPC) and test its performance. The results obtained indicate that the MPC multivariable controller is able to handle process interactions and produced good results for setpoint tracking of the humidity and temperature of the material exiting the dryer and for disturbance rejection of measured and unmeasured disturbances.