Advanced control and monitoring of bioprocesses are dependent on accurate state and parameter information. At the same time, bioprocesses are well known for their time-varying behavior and difficulty of obtaining online measurements of the important process states. The selection and the tuning of the estimation algorithms is therefore crucial to the design of reliable monitoring tools. In this work we discuss the design of several Moving Horizon Estimation schemes for a class of bioprocesses. We compare the algorithms in terms of the arrival cost computation and address the implementation of a multi-rate measurement structure. The tuning of the estimators and further details are illustrated using a cell culture case study, where we show that not all the estimators under investigation can cope equally well with process uncertainty and multi-rate measurements. As an outcome of the comparative study, we provide a set of guidelines for selecting an appropriate estimator for bioprocess applications.

生物过程的高级控制和监视取决于准确的状态和参数信息。同时，生物过程因其随时间变化的行为以及难以获得重要过程状态的在线测量值而闻名。因此，估计算法的选择和调整对于可靠监控工具的设计至关重要。在这项工作中，我们讨论了针对一类生物过程的几种“移动视界估计”方案的设计。我们比较了到达成本计算方面的算法，并讨论了多速率测量结构的实现。使用细胞培养案例研究说明估算器的调整和更多细节，在这里，我们表明并非所有正在调查的估算器都能很好地应对过程不确定性和多速率测量。作为比较研究的结果，我们提供了一组指导原则，用于为生物过程应用选择合适的估计量。