Research Initiation Award: A Novel Approach to the Control of Bioreactors

研究启动奖：生物反应器控制的新方法

基本信息

批准号：
8707928
负责人：
Ka-yiu San
金额：
$ 6万
依托单位：
William Marsh Rice University
依托单位国家：
美国
项目类别：
Continuing grant
财政年份：
1987
资助国家：
美国
起止时间：
1987-06-01 至 1990-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=8707928&HistoricalAwards=false
关键词：
Research Initiation Award Novel Approach

项目摘要

Narrative: The control of biological reactors is complicated by the fact that microbial or tissue cells are extremely sensitive to small changes in their growth environment. In addition, there is little detailed knowledge about biological system process dynamics thus making the design and implementation of effective control strategies a difficult if not impossible task. Another frustrating problem is the lack of appropriate sensors to monitor important process variables, such as pH, temperature, nutrient concentration, and by-product concentration. To help overcome these inherent problems this research proposes to use a hybrid control scheme; incorporating one level of conventional control and a second superimposed "expert system" with factual, as well as intuitive, uncertain, and judgemental knowledge for extended control action. It is proposed that both a model-based and a model- free expert system be investigated. The butanol/acetone fermentation has been chosen as the model system because of a strong data base in the literature; the system can produce various products with variable yields and selectivities under different environmental conditions, and the investigators have had previous experience with this system. It is intended that results from this study will enhance the control of bioprocesses and therefore, increase their reliability and productivity.

叙述：微生物或组织细胞对其生长环境的微小变化极其敏感，因此生物反应器的控制变得复杂。此外，关于生物系统过程动力学的详细知识很少，因此使得有效控制策略的设计和实施成为一项困难的任务，甚至是不可能的任务。另一个令人沮丧的问题是缺乏合适的传感器来监测重要的过程变量，例如 pH、温度、营养物浓度和副产品浓度。为了帮助克服这些固有问题，本研究建议使用混合控制方案；将一层常规控制和第二层叠加的“专家系统”结合起来，具有事实的、直观的、不确定的和判断性的知识，以扩展控制行动。建议研究基于模型和无模型的专家系统。由于文献中有强大的数据库，因此选择丁醇/丙酮发酵作为模型系统；该系统可以在不同的环境条件下生产具有不同收率和选择性的各种产品，并且研究人员以前有过使用该系统的经验。这项研究的结果旨在加强对生物过程的控制，从而提高其可靠性和生产率。