Title :
Nonparametric estimation of uncertain components in nonlinear dynamical system modelling
Author :
Hilgert, N. ; Senoussi, R. ; Vila, J.P.
Author_Institution :
INRA Lab. de Biometrie, Montpellier, France
Abstract :
A nonparametric identification of uncertain components in the modelling of time varying stochastic autoregressive nonlinear processes is proposed. A kernel estimator of the uncertain component is defined, whose almost sure convergence has been established under mild conditions. This approach is particularly well adapted to the identification of kinetic components in the modelling of biotechnological processes.
Keywords :
estimation theory; identification; modelling; nonlinear systems; stochastic systems; biotechnological processes; kernel estimator; nonlinear dynamical system modelling; nonparametric estimation; nonparametric identification; time varying stochastic autoregressive nonlinear processes; uncertain components; Adaptation models; Biological system modeling; Convergence; Estimation; Kernel; Stochastic processes; Substrates; Estimation; Nonlinear dynamics; Stochastic;
Conference_Titel :
Control Conference (ECC), 1997 European
Conference_Location :
Brussels
Print_ISBN :
978-3-9524269-0-6
