Hierarchical MPC-based control structure for continuous biodiesel production

Abstract

This paper presents an advanced control strategy for a continuous biodiesel production plant based on a steady-state optimizer and model predictive control (MPC). The proposed control system aims to optimize the production process and maintain product quality within required specifications. First, two steady-state optimizers were developed with the aim of minimizing the steady-state deviations of the manipulated and controlled variables and minimizing the biodiesel production cost. An MPC was then formulated to track the set points imposed by the steady-state optimizers in real time and manipulate the control inputs accordingly. The scope of this work is limited to measured disturbances only. The effectiveness of the proposed control strategy is demonstrated through dynamic simulation studies performed using HYSYS and MATLAB. The results obtained using the proposed control methodology show significant improvements in performance compared to conventional control strategies. Furthermore, it avoids the quality problem reflected in the amount of water in the final product that the original plant presented due to an inadequate design of the control strategy. Overall, the results of this research indicate that the proposed advanced control strategy has the potential to improve the efficiency and profitability of continuous biodiesel production plants.