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Peer-to-Peer Networking and Applications
Erschienen in: Peer-to-Peer Networking and Applications 5/2020

03.03.2020

Polynomial regressors based data-driven control for autonomous underwater vehicles

verfasst von: Hongran Li, Weiwei Xu, Heng Zhang, Jian Zhang, Yi Liu

Erschienen in: Peer-to-Peer Networking and Applications | Ausgabe 5/2020

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Abstract

This paper proposes a data-driven control approach on the basis of polynomial regressors for autonomous underwater vehicles (AUVs). In contrast to conventional control approach, data-driven control does not require modeling for the systems. It only utilizes the analysis of massive stored dataset to predict the future control input, which can achieve the future output. Generally, the massive stored dataset can be analyzed by short-length vectors linearly. In this paper, a novel point is the improvement of existing data-driven control by polynomial regressors, which improve the control performance of AUVs. By numerical simulations, we illustrate the effectiveness of our proposed approach.
Vorheriger Artikel Efficient caching strategy in wireless networks with mobile edge computing
Nächster Artikel Revenue-optimal task scheduling and resource management for IoT batch jobs in mobile edge computing

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Metadaten
Titel
Polynomial regressors based data-driven control for autonomous underwater vehicles
verfasst von
Hongran Li
Weiwei Xu
Heng Zhang
Jian Zhang
Yi Liu
Publikationsdatum
03.03.2020
Verlag
Springer US
Erschienen in
Peer-to-Peer Networking and Applications / Ausgabe 5/2020
Print ISSN: 1936-6442
Elektronische ISSN: 1936-6450
DOI
https://doi.org/10.1007/s12083-020-00878-6

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