DocumentCode :
2937085
Title :
Robust estimation for hybrid models of genetic networks
Author :
Li, Xiao-Dong ; Chaves, Madalena ; Gouzé, Jean-Luc
Author_Institution :
BIOCORE Project-team, INRIA Sophia Antipolis Mediterranee, Sophia-Antipolis, France
fYear :
2012
fDate :
3-6 July 2012
Firstpage :
145
Lastpage :
150
Abstract :
In this paper we consider state estimation problems with Boolean measurements for a classical negative loop genetic network governed by a piecewise affine (PWA) model. In the first part, an observer is proposed for the case where full state Boolean measurements are available. In particular sliding modes may occur and this leads to finite time convergence for the observer. In the second part we discuss state estimation with partial state Boolean measurements. A naive approach based on algebraic computation is proposed to solve the initial condition inverse problem. In the third part the observer is used to identify some unknown but fixed parameters of the model. We also investigate the robustness of the observer for a parametric uncertain model, and show that the error bound is proportional to the magnitude of the uncertainty.
Keywords :
Boolean algebra; convergence; estimation theory; genetic algorithms; observers; parameter estimation; PWA model; algebraic computation-based naive approach; classical negative loop genetic network; finite time convergence; hybrid genetic networks models; observer; parametric uncertain model; partial state Boolean measurements; piecewise affine model; robust estimation; sliding modes; state estimation problems; uncertainty magnitude; Convergence; Genetics; Observers; Robustness; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control & Automation (MED), 2012 20th Mediterranean Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4673-2530-1
Electronic_ISBN :
978-1-4673-2529-5
Type :
conf
DOI :
10.1109/MED.2012.6265629
Filename :
6265629
Link To Document :
بازگشت