During the model development phase, scientists have to cope with numerous challenges, e.g., limited knowledge about the underlying mechanisms, lack or exorbitance of dynamic or static experimental data, large experimental and process variability. However, this approach requires realistic, predictive mathematical models. Identification and Calibration, Modelling Uncertainties and Stochastic SystemsĪbstract: The use of mathematical models for analysing complex processes is a powerful tool to gain a deep system understanding.
Keywords: Model Based Design of Experiments: Where to go?, Fitting Models to Real Processes, incl. Model-Based Design of Experiments: Where to Go? MS: Model Based Design of Experiments: Where to Go? The processing time is compared with classical industrial strategy to emphasize on the outcomes. This time-optimal strategy is found analytically and is validated using experiments, where lactose is concentrated and concentration of salt is reduced. The estimated flow-rate models are used to formulate an optimal control problem (OCP) which minimizes the batch time using diluant addition rate as the control input. Parameters of the flow-rate model are estimated by solving a dynamic optimization problem that minimizes the difference between experimental and simulated system outputs. in Bratislava, SlovakiaĪbstract: In this paper, a time-optimal strategy is implemented for batch membrane separation of lactose-salt solution. Finally, in the context of enhancing microalgae productivity by reducing light absorption by microalgae, we conclude our work by studying the influence of the chlorophyll-carbon quota on the maximal productivity.Įxperimental Validation and Comparison of Time-Optimal and Industrial Strategy for Membrane Separation Process We also show that in optimal conditions there is a minimal initial microalgal concentration (and we give a simple expression to determine it) to guarantee the persistence of the population. In this work based on a simple model of light-limited growth, we determine optimal values for the dilution rate and the incident light intensity in order to maximize the steady-state microalgal surface productivity in a continuous culture. However, most of the mathematical works do not consider incident light as a parameter to be optimized. Keywords: Mathematical Modelling and Control of Bio-Chemical Processes, Bio-Technical, Bio-Chemical and Chemical Engineering, Processes and Process Engineering, ODE, DAE, SODE, SDAE SystemsĪbstract: Light supply is one of the most important parameters to be considered for enhancing microalgae growth in photobioreactors (PBR) with artificial light.
Mathmod 2018 software#
Lastly, the advantages and limitations of this software are discussed.įirst Results of Optimal Control of Average Biogas Production for the Chemostat Over an Infinite Horizon The design of the software and its main modules are discussed and the user-friendliness of the software is demonstrated with the help of tutorial examples for each problem class. It uses orthogonal collocation technique to solve the dynamic optimization problems and efficient third-party solvers are employed to solve the resulting nonlinear programs. Pomodoro is implemented in Python and utilizes CasADi as a backbone to formulate the problem. It also introduces the framework for multiobjective problems, model predictive control and state estimation. Keywords: Mathematical Modelling and Control of Bio-Chemical ProcessesĪbstract: This paper presents the software package Pomodoro which includes a collection of algorithms and tools for dynamic optimization.
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