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연속 에탄올 발효 시스템의 온라인 적응 최적화
On-Line Adaptive Optimization of Continuous Ethanol Fermentation System
HWAHAK KONGHAK, August 1992, 30(4), 397-405(9), NONE
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Abstract
포도당으로부터 에탄올 생산을 위한 효모(Saccharomyces cerevisiae)의 고농도 세포 배양계에 입출력 모델 동정에 기초하는 온라인 적응 최적화법이 시뮬레이션을 통하여 개발ㆍ적용되었다. 모델 시스템은 연속 생물 반응기, 세포재순환을 위한 막여과기, 수송을 위한 펌프등으로 구성되어 있다. 최적화의 목적은 일정한 bleeding ratio에서 희석속도를 제어함으로써 에탄올 생산을 극대화하는 것이다. 대상 시스템의 상태 파악을 위해 도입된 input-output 모델의 매개 변수 추정을 위하여 순차적인 least squres 기법을 사용하였으며 이 추정 결과에 steepest ascent 법을 적용함으로써 해당 시점에서의 최적 희석속도값을 되풀이하여 결정하였다. 에탄올 측정잡음이 없는 경우, 위와 같은 2가지 단계를 포함하는 알고리듬을 사용하여 대상으로 하는 연속 에탄올 반효시스템을 약 250시간만에 최적점에 도달시킬 수 있었다. 일단 최적화가 이루어진 상태에서 공급액 중의 기질농도를 변화시켰을 때 제안된 알고리듬은 이를 인식하여 새로운 최적점을 찾아가는 재최적화 성능을 보였다. 또한 제안된 알고리듬은 우수한 조업 안정성을 보였으며 약 3000시간동안 대상공정을 최적점에 유지시켰다. 에탄올농도 측정시 잡음이 개입되는 상황에 대해서도 시뮬레이션을 수행하였다. 평균 에탄올 생산성은 잡음이 없는 경우와 마찬가지로 최적점에 가깝게 유지될 수 있었으나 전반적으로 잡음이 없는 경우에 비해 불안정한 결과를 보였으며 희석속도의 경우 최적값을 중심으로 상당한 폭의 진동을 보였다.
An on-line adaptive optimization algorithm based on input-output model identification was, in the present simulation study, applied to a high-density cell culture of Saccharomyces cerevisiae for ethanol production from glucose. The model system consisted of a continuous bioreactor, a membrane filter unit for cell recycle, and pumps for transport. The objective of optimization was to maximize the ethanol productiv-ity by manipulating dilution rate at a fixed bleeding ratio. The bilevel forgetting factor(BFF) method was used for the estimation of parameters of the input-output model which was employed for on-line system identification. during the coures of optimization new values of the dilution rate were recurrently determined by using the steepest ascent method based on results of the model parameter estimation. When no ethanol measurement noise was involved the system was driven and maintained closely to the optimum point in about 250 hours by using the proposed algorithm. when the feed glucose concentration was changed while the culture was maintained at the optimum, the proposed algorithm could recognize the change and drove the culture to a new optimum point. The algorithm also showed a good operational stability which could stably maintain the culture at its optimum for about 3000 hours. Even when the measured concentrations were influenced by noises, the average value of the ethanol productivity was maintained closely to its optimum although the overall performance was relatively unstable and the dilution rate showed significant fluctuations.
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