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

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.