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M02 – PARIS‐SACLAY 25/01/2016 ‐ 29/01/2016

Control of biological systems: from the cell to the environment

 
Denis Dochain
ICTEAM,
Université catholique de Louvain, Belgium
http://www.uclouvain.be/denis.dochain
denis.dochain@uclouvain.be

Aim 

The objective of this course is to give an introduction and cover recent aspects of dynamical modeling, monitoring and control of biological systems. The course will cover the following topics :

Dynamical modeling of biological systems 

the notion of reaction networks and mass balance modeling will be introduced as a central concept to build a general dynamical model for biological systems. It will be used to model the biological system at the level of the cell (via the notions of metabolic engineering) up to the interaction mechanisms among different species (by considering microbial ecology notions). The model will cover both homogeneous conditions, known as stirred conditions in reactors for instance (described by ODE’s (ordinary differential equations)) and non homogeneous ones, encountered e.g. in incompletely mixed reactors, such as plug flow and diffusion based conditions in reactors, as well as population balance models that describe the distribution of age or mass of the cells (described by PDE’s (partial differential equations)). Mathematical concepts of the general dynamical model, including reaction invariant, model reduction and stability, as well as microbial ecology concepts like the competitive exclusion principle, will be studied. The link with metabolic engineering will also be introduced. The course will also cover the identification of bioprocess models (including the structural and practical model identifiability and the design of optimal experiments for parameter estimation). It will also address simulation issues related to PDE models and the use of reduction methods for this type of models.

Monitoring 

this part of the course will be dedicated to the design applications of state observers (Luenberger observers, Kalman filters, asymptotic observers, finite-time converging observers, …) and parameter estimation algorithms (in particular to estimate reaction rates and yield coefficients), that take advantage of the specific structural properties of the biological system models.
 

Control

the course will emphasize optimal control and (adaptive) linearizing control (including adaptive extremum seeking). The choice of these control approaches will be motivated in the context of biosystem applications.

Several practical applications will be used to illustrate the techniques and principles covered in this course. Examples will include biological systems from the food industry and the pharmaceutical industry to the environment and the (waste) water treatment. Computer hands-out exercices will be integrated in the course.