Optimal Operation of Fed-Batch Antibiotic Fermentations

生物过程的优化运行是极其重要的 因为这些方法使用昂贵的原材料， 需要大型资本密集型工厂和产出产品 低浓度的。 由于固有的 生物系统的复杂性，可靠的数学 优化和控制所需的模型， 发酵很少可用。 任何变化 会改变模型， 离线计算的最佳喂养策略可能不会 最适合于精确的过程。 因此，尽管 动态优化理论的有效性 和控制，已经取得了非常有限的成功， 在实验中实现这些理论， 发酵 本研究将发展线上最佳化的概念 对于分批和补料分批生物工艺， 考虑到不断变化的环境条件 和未建模的细胞内事件， 具有时变参数的过程描述。 一 计划将开发估计模型 参数在线计算和更新的最佳 发酵过程中的补料策略。 的 工作将具体解决直接应用 提出的优化概念，以工业 一个重要的过程，即头孢菌素发酵， 并将尝试验证结果， 实验

Optimal operation of bioprocesses is extremely important because these processes utilize expensive raw materials, require large capital-intensive plants and yield products that are low in concentration. Due to the inherent complexity of biological systems, reliable mathematical models needed for optimization and control of the fermentations are seldom available. Any change occurring in the environment would alter the model and thus the optimal feeding strategy calculated off-line may not be optimal for the exact process. Thus, in spite of the availability of elegant theories on dynamic optimization and control, there has been very limited success in implementing these theories experimentally in fermentations. This study will develop a concept of on-line optimization for batch and fed-batch bioprocesses that takes into account the continually changing environmental conditions and unmodeled intracellular events using a mathematical process description with time-varying parameters. A scheme will be developed which estimates the model parameters on-line and computes and updates the optimal feeding policy while the fermentation is in progress. The work will address specifically the direct application of the proposed optimization concept to an industrially significant process, namely cephalosporin fermentation, and will try to validate the results through experimentation.