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Moving Horizon State Estimation for a bioprocesses modelled by a neural network

Laboratoire d'Automatique de Grenoble, ENSIEG, UMR CNRS, BP 46-38402 St Martin d'Hères cedex

L. Boillereaux

Laboratoire d'Automatique de Grenoble, ENSIEG, UMR CNRS, BP 46-38402 St Martin d'Hères cedex

In this article, we propose a Moving-Horizon State-Estimation method, applied to a neural dynamical process model. Firstly, the approach chosen to represent a nonlinear dynamical system by a neural network is explained. After that, the MHSE method, used to perform the state estimation, is presented. The algorithm performances are showed on a biotechnological process. The combination of the MHSE method and the neural network permits a particularly efficient estimation of the state of the process. with a nonlinear model easy to build thanks to the neural network, and with an easy tuning due to the choice of the MHSE method.

Key Words: Estimation • neural network • software sensor • bioprocess.

Transactions of the Institute of Measurement and Control, Vol. 19, No. 5, 263-270 (1997)
DOI: 10.1177/014233129701900506


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