Institute of System Engineering and Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria.
Bioprocess Biosyst Eng. 2011 Mar;34(3):367-74. doi: 10.1007/s00449-010-0479-6. Epub 2010 Nov 11.
This study proposes two adaptive control algorithms for the fed-batch production of α-amylase. The first one uses online information from hardware measuring glucose. Online information of both biomass and glucose concentrations measured with different frequency is used in the second algorithm. Hardware measuring variables are inputs for software sensors of glucose concentration and (specific) glucose consumption rate. Either of the algorithms do not require any kinetic coefficients. This is a benefit, because the kinetic coefficients can vary during cultivation and between cultivations, leading to low process reproducibility and the non-stationary state of the bioprocess. The results of simulation investigations show good performance of the proposed control schemes.
本研究提出了两种用于分批生产α-淀粉酶的自适应控制算法。第一种算法使用来自硬件测量葡萄糖的在线信息。第二种算法使用不同频率测量的生物量和葡萄糖浓度的在线信息。硬件测量变量是葡萄糖浓度和（比）葡萄糖消耗率的软件传感器的输入。这两种算法都不需要任何动力学系数。这是一个优点，因为动力学系数在培养过程中以及在不同培养物之间可能会发生变化，从而导致低过程重现性和生物过程的非稳态。仿真研究结果表明，所提出的控制方案具有良好的性能。
