Sustainable method using filtering techniques for a fermentation process state estimation

Abstract

Winemaking is concerned about sustainable energy availability that implies new methods for process monitoring and control. The aim of this paper is to realize a comparative analysis of the possibilities offered using estimation techniques, balances, and filtering techniques such as the Kalman filter (KF) and the extended Kalman filter (EKF), to obtain indirect information about the alcoholic fermentation process during winemaking. Thus, an estimation solution of the process variables in the exponential growing phase is proposed, using an extended observer. In addition, two estimation solutions of this process with the EKF and an estimation of the decay phase of the fermentation process are presented. The difference between the two EKF variants consisted of taking into consideration the indicator of the integral of the error norm square for the second EKF, for which the performance criterion was the statistical average of this indicator. Results from the simulation of the estimation programs of the two EKF variants were more than satisfactory. This research provides a basis for using an EKF designed for advanced control of the alcoholic fermentation batch process as a knowledge-based system.