Nonlinear model predictive control for batch processes using set-theory
DOI:
https://doi.org/10.33131/24222208.366Keywords:
Conjunto alcanzable, Conjunto controlable, Trayectoria de Referencia Controlable, Conjunto de Trayectorias Controlables, Robustez, Control Predictivo, MPCAbstract
The control problem of Batch Processes presents many challenges. In general, it must deal with the irreversible behaviour of state variables, limited corrective actions, and sensitivity regarding disturbances. In this paper, the Controllable Trajectory Set is applied to a Nonlinear Model Predictive Control to improve the control performance of Batch Processes. The main capability of the proposed controller is to operate over a safe trajectory and away from constraints by incorporating the Controllable Trajectory Set. When the optimization problem solution is feasible, it is possible to ensure the end batch point. Additionally, the Nonlinear Model Predictive Control uses Controllable Reference Trajectory as the desired trajectory to improve robustness. Controller characteristics are illustrated using a semibatch process under a disturbance scenario. The proposed scheme decreases the control indexes under the disturbance scenario, assuring the main control objectives.
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