Biopolymers are a promising alternative to petroleum-based plastic raw materials. They are bio-based, non-toxic and degradable under environmental conditions. In addition to the homopolymer poly(3-hydroxybutyrate) (PHB), there are a number of co-polymers that have a broad range of applications and are easier to process in comparison to PHB. The most prominent representative from this group of bio-copolymers is poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). In this article, we show a new kinetic model that describes the PHBV production from fructose and propionic acid in Cupriavidus necator (C. necator). The developed model is used to analyze the effects of process parameter variations such as the CO${}_2$ amount in the exhaust gas and the feed rate. The presented model is a valuable tool to improve the microbial PHBV production process. Due to the coupling of CO${}_2$ online measurements in the exhaust gas to the biomass production, the model has the potential to predict the composition and the current yield of PHBV in the ongoing process.

Chiral amines are key building blocks in producing active pharmaceutical ingredients and can be synthesized via the amine transaminase pathway under mild conditions with eco‐friendly solvents. For model‐based design and control, mathematical models can be utilized. This requires reliable parameterization of the model. In this study, a model for the production of (S)‐(3 methoxyphenyl)‐ethylamine is presented. Parameter identifiability is analyzed using the method of profile likelihoods. The parameter identifiability is then tested in two different batch operation scenarios by using moving horizon estimation, which can be applied for on‐line model adaption and control purposes. In a batch process, identifiability decreases over time. A repetitive batch strategy improves parameter identifiability.

The production of goods in particulate form is important in many industries such as the chemical, pharmaceutical and food industry. For the subsequent use, specific particle properties determine the quality of the product. In order toensure high quality and furthermore a constant production rate, process control methods can be applied. Here we present discrepancy-based control for a generic agglomeration process with additional particle breakage. The advantage of this control approach is the direct and simple control design using the nonlinear and infinite-dimensional system descriptionas well as guaranteed stability for the chosen process variables. Two practically relevant scenarios are investigated. First, it is shown that control laws for two moments of the particle size distribution ensure the production of agglomerates with a constant Sauter mean diameter. Then, control laws for the production rate are designed. The resulting closed-loop behavior is investigated by means of dynamic simulation. It is shown that the control laws improve systems convergence speed for both set point tracking and disturbance rejection and achieve zero steady state error even under the occurrence of non-vanishing disturbances.