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Electrical Engineering and Systems Science > Systems and Control

arXiv:2204.08317 (eess)
[Submitted on 14 Apr 2022]

Title:An alternative approach for distributed parameter estimation under Gaussian settings

Authors:Subhro Das
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Abstract:This paper takes a different approach for the distributed linear parameter estimation over a multi-agent network. The parameter vector is considered to be stochastic with a Gaussian distribution. The sensor measurements at each agent are linear and corrupted with additive white Gaussian noise. Under such settings, this paper presents a novel distributed estimation algorithm that fuses the the concepts of consensus and innovations by incorporating the consensus terms (of neighboring estimates) into the innovation terms. Under the assumption of distributed parameter observability, introduced in this paper, we design the optimal gain matrices such that the distributed estimates are consistent and achieves fast convergence.
Comments: 10 pages. arXiv admin note: text overlap with arXiv:2203.03521
Subjects: Systems and Control (eess.SY); Information Theory (cs.IT); Machine Learning (cs.LG); Optimization and Control (math.OC)
Cite as: arXiv:2204.08317 [eess.SY]
  (or arXiv:2204.08317v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2204.08317

Submission history

From: Subhro Das [view email]
[v1] Thu, 14 Apr 2022 03:49:31 UTC (16 KB)
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