Modelling and L1 Adaptive Control of pH in Bioethanol Enzymatic Process

Remus Mihail Prunescu, Mogens Blanke, Gürkan Sin

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Abstract

The enzymatic process is a key step in second generation bioethanol production. Pretreated biomass fibers are liquefied with the help of enzymes to facilitate fermentation. Enzymes are very sensitive to pH and temperature and the main control challenge in the nonlinear process is to ensure minimum deviations from the optimal pH level. This article develops a mathematical model for the pH, which has not been reported earlier for this particular process. The new model embeds flow dynamics and pH calculations and serves both for simulation and control design. Two control strategies are then formulated for pH level regulation: one is a classical PI controller; the other an L1 adaptive output feedback controller. Model-based feed-forward terms are added to the controllers to enhance their performances. A new tuning method of the L1 adaptive controller is also proposed. Further, a new performance function is formulated and tailored to this type of processes and is used to monitor the performances of the process in closed loop. The L1 design is found to outperform the PI controller in all tests.
Original languageEnglish
Title of host publicationProceedings of the 2013 American Control Conference
PublisherIEEE
Publication date2013
Pages1888 - 1895
ISBN (Print)978-1-4799-0177-7
Publication statusPublished - 2013
Event2013 American Control Conference - Washington, United States
Duration: 17 Jun 201319 Jun 2013
http://a2c2.org/conferences/acc2013/

Conference

Conference2013 American Control Conference
CountryUnited States
CityWashington
Period17/06/201319/06/2013
Internet address

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