arbiter
JournalsPricingAccount

Three‐Stage Filtered Gradient Identification Methods for Multivariable ARX Systems With Colored Noise

Haoming Xing et al.

Optimal Control Applications and Methods2026https://doi.org/10.1002/oca.70063article
ABDC B
Weight
0.53

What the paper says

ABSTRACT This article investigates the identification issue of multivariable ARX systems with colored noise. To address the bias caused by colored noise, a data filtering method is applied to whiten the original multivariable system, which filters the input–output data without altering their inherent dynamics and yields a filtered identification model. Considering the computational complexity and burden in multivariable system identification, a three‐stage filtered stochastic gradient algorithm is proposed based on the filtered identification model with a hierarchical strategy. In addition, the historical innovations are utilized to further improve estimation accuracy and convergence performance, resulting in a three‐stage filtered multi‐innovation stochastic gradient algorithm. The numerical examples verify the effectiveness of the proposed algorithms in identifying multivariable ARX systems.

8 citations

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1002/oca.70063

Or copy a formatted citation

@article{haoming2026,
  title        = {{Three‐Stage Filtered Gradient Identification Methods for Multivariable ARX Systems With Colored Noise}},
  author       = {Haoming Xing et al.},
  journal      = {Optimal Control Applications and Methods},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/oca.70063},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Three‐Stage Filtered Gradient Identification Methods for Multivariable ARX Systems With Colored Noise

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.53

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.70 × 0.15 = 0.10
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.