Convergence of HLS estimation algorithms for multivariable ARX-like systems

A hierarchical least squares (HLS) algorithm is derived in details for identifying MIMO ARX-like systems based on the hierarchical identification principle. It is shown that the parameter estimation errors by the HLS algorithm consistently converge to zero for bounded noise variances by using the stochastic martingale theory. A numerical example is given. Ó 2007 Published by Elsevier Inc.

• Type: Journal
• Year: 2007
• Where: AMC
• Authors: Lingyun Wang, Feng Ding, Peter X. Liu
• Keywords: AMC 2007, Hierarchical Identification Principle, Parameter Estimation Errors, Stochastic Martingale Theory