14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper FrA6.2

Elayan, Elamari (Univ. of Caen), Giri, Fouad (GREYC), Pigeon, Eric (Univ. of Caen), Massieu, Jean-Francois (Univ. of Caen)

Ozone Concentration Modeling Using a Fuzzy Model Over the Basse Normandie

Scheduled for presentation during the Regular Session "Identification in Biological Systems" (FrA6), Friday, March 31, 2006, 10:50−11:10, Newcastle Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 16, 2018

Keywords Nonlinear System Identification, Biological Systems, Model Validation


Takagi-Sugeno (TS) modeling formalism has been widely used to build up multi-model representations for nonlinear systems. In this paper, TS approach is applied to get a multi-model description of Ozone generation process in a specific geographical zone. This is done in two steps: firstly, an adequate structure of the desired multi-model is designed. This structure involves a set of local linear models (each one is valid for a certain range of operating conditions) and an interpolative mechanism that combines the outputs of the local models into a continuous global output. The second step consists in identifying the parameters of the local models using the parametric identification approach. The identification scheme developed is applied to model ozone generation in the Basse- Normandie region (France). The model thus obtained turned out to be satisfactory and currently used to build-up a predictor for this region.