Filtro de kalmam estendido para estimativa e controle em um reator Cstr não isotérmico de produção de propileno glicol

Abstract

The most relevant piece of equipment in the chemical industry is the chemical reactor. Those equipments usually demand high amounts of energy during its operation, and considerable costs to install and maintain. That makes necessary a decent knowledge about the operation at any time and the remote monitoring of different variables inside the reactor. Several physical sensors are present in a chemical plant, providing measurements with good precision and low sampling times, with the flow, temperature, level, and others standing out. However, when the measurement of chemical and biochemical variables is desired (e.g. biomass, average particle diameter, and product concentration) several difficulties are present, with the need for offline sampling usually being necessary. In this sense, the present work proposes the construction of a virtual analyzer for inference and concentration control in the production process of Propylene Glycol. The methodology was developed in steps, where it was initially proposed the mathematical modeling of the process, soon after that the process was simulated in steady state and transient in the software Matlab-Simulink®, therefore, the virtual analyzer was carried out with the semi-empirical modeling, Extended Kalman Filter (FKE). The results obtained with the inference were evaluated using performance criteria, mean square error (MSE) and root mean square error (RMSE). The last step of the work consisted in the implementation of an inferential feedback control system for the temperature and reagent concentration in the reactor output stream. The results showed that the concentration and temperature estimates showed similar behavior to the actual process. Finally, it was verified that the inference feedback control of concentration and temperature, using the virtual analyzer through FKE, minimized the effects of inherent disturbances inserted in the process.