Title: Estimation of the order and the memory of Volterra model from input/output observations

Authors: Safa Chouchane; Kais Bouzrara; Hassani Messaoud

Addresses: Laboratory of Automatic, Signal and Image Processing, National School of Engineers of Monastir, University of Monastir, 5019, Tunisia ' Laboratory of Automatic, Signal and Image Processing, National School of Engineers of Monastir, University of Monastir, 5019, Tunisia ' Laboratory of Automatic, Signal and Image Processing, National School of Engineers of Monastir, University of Monastir, 5019, Tunisia

Abstract: This paper proposes a new method to estimate, from input/output measurements, the structure parameters (order and memory) of Volterra models used for describing nonlinear systems. For each structure parameter (order and memory), the identification method is based on the definition, for increasing values of such parameter, of a specific matrix the components of which are lagged inputs and lagged outputs. This matrix becomes singular once the parameter value exceeds its exact value. The proposed method is tested in numerical examples, then it is used for modelling a chemical reactor and the results were successful.

Keywords: nonlinear system; Volterra model; structure estimation; determinant ratio.

DOI: 10.1504/IJMIC.2018.091240

International Journal of Modelling, Identification and Control, 2018 Vol.29 No.3, pp.244 - 254

Available online: 10 Apr 2018 *

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