Performance analysis of the auxiliary model-based least-squares identification algorithm for one-step state-delay systems

Abstract

Based on the input–output representation of one-step state-delay systems, we use the auxiliary model-based recursive least-squares algorithm to estimate the parameters of the systems and study the convergence of the proposed algorithm by using the stochastic process theory. A simulation example is provided.

Keywords:

• parameter estimation
• recursive identification
• state-space model
• auxiliary model identification
• least squares

2010 AMS Subject Classifications::

• 93B30
• 93A30

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (No. 60973043) and in part by the 111 Project (B12018).