Search

This work considers robust moisture content and activity control in a continuous convective drying for particulate bio-materials. The major process uncertainty is in the kinetics of the second (falling-rate) drying period. Robust feedback controllers in the multi-variable and de-central case are designed to guarantee desired product specifications. The advantages of the robust controllers are discussed in comparison with a conventional PI controller. The case study presented is the drying of baker's yeast in a fluidized bed dryer. The results show constant performances concerning the uncertainty of the drying kinetics and disturbance rejection at different operating points. • Robust multivariable controller design for convective drying. • Constant controller performance concerning various process uncertainties and operating points. • Baker's yeast in fluidized bed dryer as case study. [ABSTRACT FROM AUTHOR]

[Display omitted] • Population balance modeling of continuously operated fluidized bed spray agglomeration process. • Model adaption to experimental data and analysis of model parameter inference. • Identification of functional dependencies of agglomeration kernel on process parameters from experimental data. Fluidized bed spray agglomeration is an important industrial particle formation process. In particular, the continuous operation mode is able to provide a constant stream of product particles with constant quality in terms of particle properties. Mathematical process modeling represents a valuable tool for a thorough analysis of the involved mechanistic processes and can further be used for process intensification and control. Sophisticated models describing the quantitative effect of process conditions on particle properties are particularly important. Therefore, in this contribution the influence of the seven most important operational parameters on the particle size distribution is modeled, including fluidization and binder properties. To this end, a population balance process model with the three-parametric Kapur kernel is fitted to experimental data. The first main result of this contribution is the quantitative description of the dependency between the agglomeration rate and the process conditions by multidimensional paraboloids. The second main result is the introduction of a general method by which this quantitative formulation is obtained. [ABSTRACT FROM AUTHOR]

Many particulate processes in process and bioprocess engineering can be described with multi-dimensional population balances. Approximate moment methods are frequently used for their solution. In the present paper a new approach is presented, which is particular efficient when the number of internal coordinates is high. It combines the direct quadrature method of moments with monomial cubatures. With the new method the computational effort increases only polynomially, in the simplest case even only linearly with the number of internal coordinates, compared to an exponential increase for the well known Gausssian cubatures. The technique is evaluated for a five dimensional benchmark problem describing virus replication in continuous cell cultures. Furthermore, the algorithm is applied to analyze influenza virus replication in genetically modified cell lines. [ABSTRACT FROM AUTHOR]

Continuous fluidised bed layering with internal product separation is known to possess unstable steady-states, yielding sustained nonlinear oscillations in the particle size distribution, the key product parameter. In this work, the well-known framework of constrained linear model predictive control is applied to stabilise corresponding unstable steady-states. Performance of the controllers is discussed with respect to design parameters and process constraints, as is robustness to overspray generation and size of formed overspray particles. [ABSTRACT FROM AUTHOR]

Particle shape plays an important role in many industrial applications since it can have significant impact on both, processability of particles as well as the properties of the final product. For this reason modeling of the corresponding production process is crucial for developing efficient process optimization and control strategies. The shape evolution of crystals on the process scale can be described conveniently within the framework of morphological population balance modeling. In order of being a reliable tool for the prediction of the crystal shape distribution during the production process as well as for the design of suitable control and optimal production strategies, the models require the estimation of several parameters characterizing the growth rates of the different crystal facets. This is particularly challenging due to the infinite dimensional state space of the models. In this contribution online parameter estimation for the growth rates of L-glutamic acid cooling crystallization is presented. Using a Lyapunov-based approach the parameter adaption laws are computed directly from the infinite dimensional problem formulation. It will be shown that a reasonably fast convergence of the parameter estimates can be achieved even in the presence of measurement noise using appropriate filters. [ABSTRACT FROM AUTHOR]

• Multiscale modeling of microbial production of poly(3-hydroxybutyrate) using carbon sources common in organic waste feed-stocks. • Modeling of poly(3-hydroxybutyrate) production yields and chain length dynamics in dependency of the dissolved oxygen level. • Optimal carbon to ammonium ratios are related to the dissolved oxygen level. Polyhydroxyalkanoates are a promising material for a broad range of plastic products. Due to the high production costs, the proportion of industrial produced polyhydroxyalkanoates is low compared to conventional plastics. One possibility to reduce the costs is to reduce the price of the substrates using organic carbon-rich wastes streams. Using mathematical modeling, the microbial production process can be optimized by adjusting process conditions like the oxygen supply or initial substrate ratios. This contribution outlines a multiscale model for the poly(3-hydroxybutyrate) production in Cupriavidus necator using the carbon-sources fructose and acetate. The model comprises a hybrid cybernetic model to describe the macroscopic dynamics and a polymerization model which describes the chain length dynamics. The multiscale model is used to analyze the effects of different initial carbon to ammonium ratios and dissolved oxygen levels on the poly(3-hydroxybutyrate) concentration and chain length distribution. [ABSTRACT FROM AUTHOR]

Highlights • Continuous convective drying of particulate materials is considered. • Parametric uncertainties in the second drying period are addressed. • Feedback controller providing robust stability and performance are designed. • Application is exemplified for drying of baker's yeast pellets in fluidised beds. • Very good performance in view of kinetic uncertainty and operating point. Abstract This work considers robust control of continuous convective drying of particulate solids where the major process uncertainty lies in the kinetics of the second (falling-rate) drying period. Using the concept of normalised drying curve, for arbitrary shape of the curve, the steady state particle moisture content is derived. Applying appropriate uncertainty models, a robust feedback controller is designed to guarantee desired product moisture. Advantages of this approach are discussed in comparison to convential PI and LQ-optimal control. The approach is exemplified for the case of fluidised bed drying of baker's yeast particles. Results show very good performance with respect to parametric uncertainty and disturbance rejection even at non-nominal steady-states. [ABSTRACT FROM AUTHOR]

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 to ensure 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 description as 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. • Control of a particle formation population balance with aggregation and breakage. • Design of discrepancy-based MIMO-control laws. • Control of particle size and particle production rate. • Validation of controller performance and robustness in a simulation study. [ABSTRACT FROM AUTHOR]