Identification of linear systems with hard input nonlinearities of known structure
This paper studies identification of linear systems with input nonlinearities of known structure. For input nonlinearities parametrized by one parameter, a deterministic approach is proposed based on the idea of separable least squares. The identification problem becomes equivalent to a one-dimensional minimization problem. The method may be used for several common static and nonstatic input nonlinearities. For a general input nonlinearity, a correlation analysis based identification algorithm is presented which is shown to be convergent. Two examples are studied.
scientific article; zbMATH DE number 1797062