José Aldemar Muñoz Hernandez

This chapter presents a strategy for controlling the concentration of dissolved oxygen (DO) in the bioreactor of a pilot wastewater plant (WWTP). The control strategy being developed is model-based predictive control (MPC). To apply the control algorithm, the estimation of the oxygen transfer function (KLa) is first performed, then the model and linearization technique are determined and finally the MBPC controller is designed. The results are simulated in MATLAB® and executed in the plant control and supervision system Supervisory Control and Data Acquisition (SCADA) in LabVIEWTM. This chapter is organized as follows: Section 1 presents a brief introduction, and Section 2 determines and describes the model to be used and its respective linearization, as well as the results obtained for the KLa parameter. Finally, Section 3 describes the design methodology of the generalized predictive control (GPC) controller proposed by Clarke, using the Model Predictive Control Toolbox and the EPSAC strategy developed by De Keyser. It should be noted that the simulations in each of the sections were performed in MATLAB® and executed in the control and supervision system with the MATLAB® script interface in LabVIEWTM.

Introduction— Previous reactor models have been used to study the dynamic behavior of bioethanol production systems, however, few have elaborated a comparative study of control strategies that stabilize and control the variables of interest. Objective— The objective of this study is to analyze the stability of a fermentation system to obtain bioethanol, its dynamic behavior, the characterization of equilibrium points and bifurcation points of the mathematical model proposed by Jarzebski in 1992 for a continuous fermentation, taking into account the performance of the reaction in a bioreactor and the application of industrial control techniques for its optimization. Methodology— Review and design methods of quantitative and systematized type were used. Results— The comparison between two control strategies to control bioethanol production, PID control and Fuzzy. Conclusions— This work shows the importance of the stability analysis of a continuous system and how it can define the regions of operational interest, in this case for ethanol production, showing that productivity is inversely proportional to the dilution rate. Finally, it is concluded that a better dynamic behavior of the system is obtained when a Fuzzy controller is used. This work also shows the importance of the stability analysis of a continuous system and how it can define the regions of operational interest, in this case for the production of ethanol.

En el presente trabajo se propone controlar la concentración de oxigeno disuelto (DO) en el bioreactor de la planta piloto de aguas residuales de la Universidad de Ibagué (PTAR), La estrategia de control que se pretende utilizar es el control predictivo basado en modelos (MPC). Para lograrlo primero se realiza la estimación de la función de transferencia de oxigeno (KLa), luego se determina el modelo y la técnica de linealizacion y finalmente se diseña el controlador. Los resultados son simulados en Matlab y ejecutados en el sistema de control y supervisión de la planta (Labview).