Soons Zita I T A, van Straten Gerrit, van der Pol Leo A, van Boxtel Anton J B
Systems and Control Group, Wageningen University, Wageningen, The Netherlands.
Bioprocess Biosyst Eng. 2008 Aug;31(5):453-67. doi: 10.1007/s00449-007-0182-4. Epub 2007 Dec 21.
Performance of controllers applied in biotechnological production is often below expectation. Online automatic tuning has the capability to improve control performance by adjusting control parameters. This work presents automatic tuning approaches for model reference specific growth rate control during fed-batch cultivation. The approaches are direct methods that use the error between observed specific growth rate and its set point; systematic perturbations of the cultivation are not necessary. Two automatic tuning methods proved to be efficient, in which the adaptation rate is based on a combination of the error, squared error and integral error. These methods are relatively simple and robust against disturbances, parameter uncertainties, and initialization errors. Application of the specific growth rate controller yields a stable system. The controller and automatic tuning methods are qualified by simulations and laboratory experiments with Bordetella pertussis.
应用于生物技术生产中的控制器性能往往低于预期。在线自动调谐有能力通过调整控制参数来提高控制性能。本文介绍了分批补料培养过程中模型参考比生长速率控制的自动调谐方法。这些方法是直接方法，利用观测到的比生长速率与其设定值之间的误差；无需对培养进行系统扰动。两种自动调谐方法被证明是有效的，其中自适应速率基于误差、平方误差和积分误差的组合。这些方法相对简单，对干扰、参数不确定性和初始化误差具有鲁棒性。比生长速率控制器的应用产生了一个稳定的系统。通过对百日咳博德特氏菌的模拟和实验室实验验证了该控制器和自动调谐方法。
