Dynamic analysis and control of chemical and biochemical reaction networks
Advanced Control of Chemical Processes, Volume # 6 | Part# 1
Authors
Irene Otero-Muras, Gabor Szederkenyi, Antonio A. Alonso, Katalin M. Hangos
Identifier
None
Index Terms
biochemical reaction networks,passivity,nonlinear control,entropy
Abstract
Metabolic or cell signalling pathways are examples of biochemical networks exhibiting possible complex dynamics in the form of steady-state multiplicity, sustained oscillations or even deterministic chaos. The origin of these nonlinear phenomena is not always well understood, nor it can be systematically predicted beyond a case by case basis. Despite considerable progress in dynamic aspects, efforts are still needed to develop efficient and robust methods of stabilization and control of reaction networks. In this work, we combine concepts and tools from irreversible thermodynamics and systems theory to explore the underlying dynamic properties of a general class of chemical and biochemical networks. Lyapunov and passivity based methods are given for the systematic design of globally stabilizing feedback controllers in both the concentration space and a novel minimal description of the kinetic networks dynamics: the reaction space.
References
[1] Alonso, A. A. and B. E. Ystdie (2001). Stabilization
of distributed systems using irreversible
thermodynamics. Automatica 37(11), 1739-
1755.
[2] Alonso, A.A., C.V. Fernandez and J.R. Banga
(2004). Dissipative systems: From physics to
robust nonlinear control. Int. J. of Robust and
Nonlinear Control 14, 157-159.
[3] Callen, H. B. (1980). Thermodynamics and an
introduction to thermostatistics. John Wiley
and Sons. New York.
[4] Feinberg, M. (1979). Lectures on chemical reaction
networks. Lectures given at the Mathematics
Research Center, University of Wisconsin.
[5] Gorban, A. N., I.V. Karlin and A.Y. Zinovyev
(2004). Invariant grids for reaction kinetics.
Physica A 33, 106-154.
[6] Gunawardena, J. (2003). Chemical network theory
for in-silico biologists. Lecture given at the
Bauer Center for Genomics Research, Harvard
University.
[7] Hangos, K.M. and I.T. Cameron (2001). Process
Modelling and Model Analysis. Academic
Press. London.
[8] Sontag, E. (2001). Structure and stability of certain
chemical networks and applications to
the kinetic proofreading model of t-cell receptor
signal transduction. IEEE Trans. Autom.
Control 46, 1028-1047.
[9] Thomas, R. and M. Kaufman (2001). Multistationarity,
the basis of cell differentiation
and memory: Structural conditions of multistationarity
and other nontrivial behaviour.
Chaos 11, 170-179.
[10] Van der Shaft, A. (2000). L2 -Gain and Passivity
Techniques in Nonlinear Control. Springer.
