A modified model decomposition identification for bilinear-in-parameter systems

摘要

The so-called bilinear-in-parameter models are usually derived from the block-oriented nonlinear models and identified by different methods. Inspired by the model decomposition-based identification technique, this paper develops a recursive least squares algorithm to estimated the model parameters and obtained a global convergence which are shown by a simulation example.