摘要：AbstractMicrobial fermentation processes are most often described by nonlinear time-varying dynamics, which require the implementation of nonlinear state estimators to infer unmeasured metabolites in the cultivation broth. Among the various nonlinear available estimator strategies, the Moving Horizon Estimator (MHE) is anon-lineoptimization approach that easily allows to enforce hard constraints, an important feature that helps to avoid unfeasible concentrations. In this work we implemented an MHE by using experimental data from a fed-batch cultivation process ofCorynebacterium glutamicum.Available real-time measurements of biomass and CO2 formation were used to infer sugar concentrations by combining the available measurements with a simple Monod model. We found that the MHE was able to estimate all the three variables of interest, including the unmeasured sugar concentrations, during the entire fed-batch cultivation process. Moreover, we show that the estimates are accurate in comparison to the referenceofflinesamples. This work demonstrates the benefits of MHE as a soft sensor that can monitor bioprocesses in real-time.
关键词：KeywordsEstimationcontrol in biological systemsParameterstate estimationMonitoringOptimization
