Banca de DEFESA: IGOR MENDES LIMA PATARO

ADVANCED SIMULATION OF D-RTO ASSOCIATED WITH PREDICTIVE CONTROL STRATEGIES FOR ETHANOL DISTILLATION COLUMNS

Predictive control, processes control, ethanol, alcoholic distillation, simulation.

Alcoholic distillation, one of the main productive stages of the sugar and alcohol industry, still shows timid results in terms of automatic control and optimization. However, advanced control approaches give us good prospects for improving safety, efficiency and productivity in this type of process. In particular, predictive control techniques, widely known as MPC (Model Predictive Control) allow the operation of the distillation columns considering the complexity of the system, such as multiple inputs and outputs and numerous disturbances that can compromise the quality of the products. In addition, strategies based on time compensators, such as the filtered Smith Predictor (FSP), can incorporate formulations that allow to increase the robustness of the closed loop control system. From this perspective, this work presents the application of an advanced control structure in two layers. The first layer consists of implementing a predictive control system. In particular, the infinite horizon (IHMPC), MIMO FSP and DTCGPC were designed, capable of maintaining the alcoholic distillation process under the conditions defined as a reference. For the second layer, a dynamic optimizer in real time was developed, capable of calculating the best operation points of the process using a reliable model, considering economic and productivity conditions. For that, a computational platform was also developed that allows the advanced simulation of the system as well as its dynamic behavior in a Software-in-the-Loop environment as a way to guarantee the fidelity of the results and propose the application of these strategies in a real scenario. OLE (Object Linking and Embedding) Automation integrates Matlab and Aspen Hysys software to simulate practical OPC (Open Platform Communications) scenarios commonly found in the industry. Controllers are evaluated, in simulation scenarios, from control performance indexes (ITAE, ITSE, SSC) and the computational performance of each strategy, as a quantitative metric for comparing the proposed structures. Furthermore, the economic performance of the optimization layer is compared with the classic PID control strategy still applied in the sugar and alcohol industry. This study showed that the dynamic optimization associated with predictive controllers increased the production of the distillation column, showing itself to be more robust and stable compared to the approaches commonly used in the current scenario of ethanol distilleries. In view of the particular benefits of each strategy, this work aims to propose different control solutions for different scenarios of the sugar and alcohol industry, in order to maintain a more efficient, economical and clean production. In addition, it is intended to evolve the practical application of advanced control strategies that take into account the stability of the system, the efficiency of production and the robustness in closed loop.