V.G Ryckaert

Model-based temperature control in ovens

The performance of an oven cavity is improved by implementing more advanced control algorithms to the unit. This improvement is necessary to cope with the more stringent requirements of the food market. It is shown with experimental results that the dynamic behavior of the oven cavity is modified significantly through the implementation of a model-based tuned P.I.D. controller. For this purpose, a mathematical model representing the main temperature dynamics of the oven cavity, is identified and validated. Afterwards, this mathematical model is used for tuning of the controller parameters, which allows a fast, safe and inexpensive off-line search for the optimal parameter set. In addition, the effect of practical constraints such as bounds and discretization effects can be examined quite easily. The model-based tuning approach for temperature control of an oven cavity is found to be successful. The application also illustrates the use of advanced measurement and control hardware and software.

Modeling the competition between floc-forming and filamentous bacteria in activated sludge waste water treatment systems—I. Evaluation of mathematical models based on kinetic selection theory

One of the main reasons for failing of the sedimentation process in activated sludge waste water treatment systems is the phenomenon of filamentous bulking. This occurs when filamentous bacteria overgrow floc-forming bacteria. In this paper mathematical models are discussed which describe the competition of flocs and filaments based on the kinetic selection theory. It is proven with a stability analysis for a continuous reactor, that, in order to control filamentous bulking, the dilution rate plays a crucial role. Moreover, it is shown that coexistence of both organisms is generically not possible. Afterwards the continuous reactor model is extended in order to describe a standard waste water treatment system. Due to the complexity of the extended model it is difficult to perform the stability analysis analytically. It is proven that the model can be reduced without loss of stability properties. For the reduced model it is proven with a stability analysis that the transport terms play a crucial role in the survival of one or the other organism. As for the continuous reactor model it is shown that coexistence of both organisms is generically not possible.

Modelling and dynamical analysis of unitank biological wastewater

By applying modern model based control theory to biotechnological systems such as wastewater treatment plants important process improvements can be expected. Mathematical (low complexity) models, useful for dynamical optimization of systems and for the design of on-line model based controllers have been developed. A new technique, based on equilibrium lines in the state space domain, is introduced to analyze the dynamic behavior of such systems. The use of sensitivity studies as a tool to discriminate between different model structures is clearly illustrated

Robustness of Nonlinear Observers

Abstract The lack of accurate and cheap on-line sensors typical for biotechnological processes, such as wastewater treatment plants and fermentation processes, necessitates the use of nonlinear state observers . Due to the existence of several quite different design methodologies there exists an observer selection problem for the process engineer, who wants to use the observer concept to relax the measurement problem. Performance analysis (evalution of a set of performance measures) is an excellent tool for approaching the observer selection problem. In this contribution robustness analysis of four nonlinear observers is considered for a prototype bioprocess model. It must be emphasized that large uncertainty (both parametric and structural) on the process model is typical for bioprocesses. The main contributions are (i) the introduction of robustness measures, inspired from a process engineering point of view, (ii) presentation of the (general) concepts used for analysis and (iii) illustration how the results must be interpreted.

Optimal Design and Control of Cyclically Operated Biological Wastewater Treatment Plants

Abstract Optimal control of cyclically operated activated sludge wastewater treatment systems is considered. An optimal control strategy is derived which can easily be implemented in practice. It is shown that the obtained reference dynamics has model independent properties which guarantees in robustness against model uncertainty. It is demonstrated how application of optimal control theory reveals important features of the optimal control strategy without explicitly solving the two-point boundary value problems typically encountered when applying the minimum principle of Pontryagin. Moreover, a method for solving optimal control problems for complex interconnected systems is presented. The basic idea of this method is to combine the solutions of simplified optimal control problems in a well motivated manner.

State and parameter estimation of bioprocess models - a case study

Abstract The application of modern model based control techniques to biotechnological processes -such as biological wastewater treatment and fermentation processesis hampered due to the complex, nonlinear and time varying characteristics of these systems, and the lack of reliable, accurate and cheap on-line sensors. An approach to tackle the measurement problem is the use of estimation schemes. The estimation problem is analyzed for a typical bioprocess model. A direct link between the measurability of the process and the design of the plant is established. The analysis of the estimation problem is shown to be a powerful tool for determining an optimal investment policy for sensors.