Identification, estimation, and control of uncertain dynamic systems : a nonparametric approach
Hilgert N., Rossi V., Vila J.P., Wagner V.. 2007. Communications in Statistics. Theory and Methods, 36 (14) : p. 2509-2525. International Symposium on Applied Stochastic Models and Data Analysis. 11, 2005-05-17/2005-05-20, Brest (France).
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 : statistiques; modèle mathématique; biotechnologie
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