Optimal Control Applied to Oenological Management of Red Wine Fermentative Macerations

The Effects of Pre-Fermentative Addition of Oenological Tannins on Wine Components and Sensorial Qualities of Red Wine.

Today in the wine industry, oenological tannins are widely used to improve wine quality and prevent oxidation in wine aging. With the development of tannin products, new oenological tannins are developed with many specific functions, such as modifying antioxidant effect, colour stabilization and aroma modifications. The aim of this work is to investigate effects of pre-fermentative addition of ...

Nonlinear Optimal Control Techniques Applied to a Launch Vehicle Autopilot

This paper presents an application of the nonlinear optimal control techniques to the design of launch vehicle autopilots. The optimal control is given by the solution to the Hamilton-Jacobi-Bellman (HJB) equation, which in this case cannot be solved explicity. A method based upon Successive Galerkin Approximation (SGA), is used to obtain an approximate optimal solution. Simulation results invo...

Red wine and oenological extracts display antimicrobial effects in an oral bacteria biofilm model.

The antimicrobial effects of red wine and its inherent components on oral microbiota were studied by using a 5-species biofilm model of the supragingival plaque that includes Actinomyces oris, Fusobacterium nucleatum, Streptococcus oralis, Streptococcus mutans and Veillonella dispar. Microbiological analysis (CFU counting and confocal laser scanning microscopy) of the biofilms after the applica...

Comparison Between Effect of Grape Fermentative Product (red wine) and Fresh Red Grape Juice on Antioxidant Biomarkers of Liver Mitochondria Isolated from Rats in vitro

Neural Networks Applied to Optimal Flight Control

This paper presents a method for developing control laws for nonlinear systems based on an optimal control formulation. Due to the nonlinearities of the system, no analytical solution exists. The method proposed here uses the 'black box' structure of a neural network to model a feedback control law. The network is trained with the back-propagation learning method by using examples of optimal co...