Identification of the parameters of a normalized BOUC — WEN MODEL

Abstract

The article considers the problem of identifying the parameters of the Bouc — Wen phenomenological model which describes the functioning of a wide range of nonlinear hysteretic systems by means of differential equations. The parameters of the standard Bouc — Wen model are analysed regarding their effect on the shape of the hysteresis loop. The models are classified with regard to their dissipativity depending on the value range of their parameters. The article provides an analytical description of the input signal, given that the Bouc — Wen model is to be embedded into a biological-based artificial neural network as a hysteresis quantizer. The article describes a parameter identification procedure for a normalized model based on the identification of the limit cycles of the equations describing the hysteresis loop. The parametric correspondence between the initial standard Bouc — Wen model and the normalized one is considered, as well as the influence of each parameter on the shape of the hysteresis curve. Analysing the input/output correspondence of the Bouc — Wen model, we obtained the analytical dependencies determining the parameters of the normalized model. We also suggest an algorithm for calculating the parameters of the Bouc — Wen model. The theoretical assumptions presented in the article are illustrated by the results of computational experiments.