Identification, estimation, and control of uncertain dynamic systems : a nonparametric approach

Hilgert Nadine, Rossi Vivien, Vila Jean-Pierre, Wagner Vérène. 2007. Identification, estimation, and control of uncertain dynamic systems : a nonparametric approach. Communications in Statistics. Theory and Methods, 36 (14) : 2509-2525. International Symposium on Applied Stochastic Models and Data Analysis. 11, Brest, France, 17 Mai 2005/20 Mai 2005.

Résumé : This article is devoted to a presentation of the authors' practice of the non-parametric estimation theory for the estimation, filtering, and control of uncertain dynamic systems. The fundamental advantage of this approach is a weak dependency on prior modeling assumptions about uncertain dynamic components. This approach appears to be of great interest for the control of general discrete-time processes, and in particular, biotechnological processes, which are emblematic of nonlinear uncertain and partially observed systems.

Mots-clés Agrovoc : statistiques, modèle mathématique, biotechnologie

Classification Agris : U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : Hors axes (2005-2013)

Auteurs et affiliations

• Hilgert Nadine, INRA (FRA)
• Rossi Vivien, CIRAD-ES-UPR Dynamique forestière (FRA) ORCID: 0000-0001-5458-1523
• Vila Jean-Pierre, INRA (FRA)
• Wagner Vérène, Institut de veille sanitaire (FRA)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/541924/)

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