Brief Identification of linear systems with hard input nonlinearities of known structure

  • Authors:

  • Er-Wei Bai

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2002

Quantified Score

Hi-index 22.17

Visualization

Abstract

This paper studies identification of systems with input nonlinearities of known structure. For input nonlinearities parameterized by one parameter, a deterministic approach is proposed based on the idea of separable least squares. The identification problem is shown to be equivalent to an one-dimensional minimization problem. The method is very effective 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.