A tunable multivariable nonlinear robust observer for biological systems.
This paper presents a robust nonlinear asymptotic observer with adjustable convergence rate with a great potential of applicability for biological systems in which the main state variables are difficult and expensive to measure or such measurements do not exist. This observer scheme is based on the classical asymptotic observer, which is modified to allow the tuning of the convergence rate. It is shown that the proposed observer provides fast and satisfactory estimates when facing load disturbances, system failures and parameter uncertainty while maintaining the excellent robustness and stability properties of the classical asymptotic observer. The implementation of the tunable observer is carried out by numerical simulations of a mathematical model of an anaerobic digestion process used for wastewater treatment. The key results are examined and further developed.
Alcaraz-González
Víctor
V
Departamento de Ingeniería Química, Universidad de Guadalajara-CUCEI, Blvd. Marcelino García Barragán 1451, Guadalajara, Jalisco, 44430, México. victor@ccip.udg.mx
Salazar-Peña
Rodolfo
R
González-Alvarez
Víctor
V
Gouzé
Jean-Luc
JL
Steyer
Jean-Philippe
JP
D017711:Nonlinear Dynamics; D049490:Systems Biology / Q000706:statistics & numerical data*