Quantized Input and Output‐Based Identification of FIR Systems With Event‐Triggered Communication and Data Packet Drop

ABSTRACT This article studies the problem of finite impulse response (FIR) system identification with binary sensor and the either‐or communication, together with the packet drop for quantized inputs. We propose online identification algorithms for two cases of known and unknown probability of packet drop, and prove strong convergence and asymptotic normality of the algorithms. Additionally, we introduce metrics to describe the speed of the algorithm's convergence when the probability of packet drop is unknown. Finally, the effectiveness of the theoretical results is verified by experiment.

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Publication Details

Journal
International Journal of Adaptive Control and Signal Processing
Published
2025-05-26
DOI
https://doi.org/10.1002/acs.4033
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

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Controls
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article

Quantized Input and Output‐Based Identification of FIR Systems With Event‐Triggered Communication and Data Packet Drop

Lingfeng Chen, Jin Guo, Kun Zhang, Peng Yu
International Journal of Adaptive Control and Signal Processing
Distributed Control Multi-Agent Systems
article

Quantized Input and Output‐Based Identification of FIR Systems With Event‐Triggered Communication and Data Packet Drop

Lingfeng Chen, Jin Guo, Kun Zhang, Peng Yu
article en

Abstract

ABSTRACT This article studies the problem of finite impulse response (FIR) system identification with binary sensor and the either‐or communication, together with the packet drop for quantized inputs. We propose online identification algorithms for two cases of known and unknown probability of packet drop, and prove strong convergence and asymptotic normality of the algorithms. Additionally, we introduce metrics to describe the speed of the algorithm's convergence when the probability of packet drop is unknown. Finally, the effectiveness of the theoretical results is verified by experiment.

International Journal of Adaptive Control and Signal ProcessingVol. 39(9)
Beijing Transportation Research Center (CN), Beihang University (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China, Beijing Nova Program, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 88%
Distributed Control Multi-Agent Systems
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Quantized Input and Output‐Based Identification of FIR Systems With Event‐Triggered Communication and Data Packet Drop — Lingfeng Chen, Jin Guo, et al. · International Journal of Adaptive Control and Signal Processing (2025) | TGRS Research Map | TGRS