Adaptive filtering and estimation of nonlinear biological systems

Author

Maher, M. ; Dahhou, B. ; Zeng, F.Y.

Author_Institution

Lab. d´´Autom. et d´´Anal. des Syst., CNRS, Toulouse, France

fYear

1993

fDate

17-20 Oct 1993

Firstpage

235

Abstract

This paper presents a study of 3 estimation algorithms. They are used to palliate the bioprocess sensors deficiencies which are not able to provide direct real-time measurements. State and parameter estimation algorithms developed mainly for nonlinear biological systems are compared. They are the extended Kalman filter, the method of Dochain and Bastin (1990) and the method of Zeng and Dahhou. Their computational properties are compared and their convergence is tested on a simulated nonlinear fermentation process

Keywords

adaptive filters; chemical technology; filtering theory; identification; nonlinear systems; adaptive estimation; adaptive filtering; bioprocess sensor deficiencies; computational properties; extended Kalman filter; nonlinear biological systems; parameter estimation; simulated nonlinear fermentation process; state estimation; Adaptive filters; Biological system modeling; Biological systems; Biology computing; Biomass; Biosensors; Carbon dioxide; Computational modeling; Parameter estimation; Plants (biology);

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on

Conference_Location

Le Touquet

Print_ISBN

0-7803-0911-1

Type

conf

DOI

10.1109/ICSMC.1993.390715

Filename

390715