(486g) Optimal Control of Biodiesel Production in a Batch Reactor in the Face of Feed Variability

The depletion of the fossil fuel reserves and the increasing environmental concerns encourage engineers and scientists to look for an alternative, clean and renewable fuel that can reduce environmental impact. Biodiesel has been considered as the best candidate of one of these renewable fuels. One of the pathways to biodiesel production is the transesterification reaction of triglycerides from vegetable oils and short-chain alcohols. A batch reactor is employed for production of biodiesel. The flexibility of the process allows to operate the reactor with completely different feed stock and product specifications. This condition becomes challenging for the reactor modeling and control since uncertainty in the feed composition turn into time-dependent uncertainty and requires a batch-process stochastic optimal control. In this work, the uncertainties resulting from the variation of feed stock composition are quantified, characterized and propagated through the model. Generated time-dependent uncertainties are modeled using Ito processes. The optimal control in this reactor involves optimization of the yield of fatty acid methyl esters, well known as biodiesel, under control of reactor temperature and the strategy applied to solve this problem is based on stochastic maximum principal and shooting approach.