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Hierarchical stochastic gradient parameter estimation algorithms for multivariable systems with colored noises

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2 Author(s)
Feng Ding ; School of Communication and Control Engineering, Jiangnan University, Wuxi, China 214122 ; Yanjun Liu

This paper develops a hierarchical extended stochastic gradient identification algorithms for MIMO ARMAX-like systems to deal with colored noises based on the hierarchical identification principle. The convergence performance of such algorithms is studied in detail; in particular, conditions for parameter estimation errors to converge to zero are established, which include persistent excitation of the extended information vectors and strict positive realness of the noise models. Finally, the proposed algorithms are tested on an example to show their advantages and effectiveness.

Published in:

2009 American Control Conference

Date of Conference:

10-12 June 2009