Abstract
This paper proposes a new method to estimate, from input/output measurements, the structural parameters (order and memory) of the Volterra models used for describing a nonlinear thermal process, the Trainer PT326. The proposed estimation method is an extension of the recent work in which a new algorithm for estimating the memory of the Volterra model was proposed. The structure parameters identification method, proposed in this paper, is based on the definition of a specific matrix whose components are lagged inputs and lagged outputs. We prove that this matrix becomes singular once the parameter value exceeds its exact value. The estimated values of the order and the memory are used to provide a suitable Volterra model for the Process Trainer PT326. The performance of the model and the identification method that uses experimental data are evaluated.
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