Identification,Estimation, and Control of Uncertain Dynamic Systems: A Nonparametric Approach |
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| Authors: | Nadine Hilgert Vivien Rossi Vérène Wagner |
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| Institution: | 1. UMR Analyse des Systèmes et Biométrie, INRA , Montpellier, France;2. UR Dynamique des Forêts Naturelles, CIRAD , Montpellier, France;3. Département Santé et Environnement , Institut de Veille Sanitaire , Saint-Maurice, France |
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| Abstract: | This article is devoted to a presentation of the author' 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. |
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| Keywords: | Discrete-time stochastic systems Fault detection Markov controlled processes Nonlinear filtering Nonparametric identification Predictive control |
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