Cited by 80Reinforcement Learning in RoboticsShip Hydrodynamics and ManeuverabilityMaritime Navigation and Safety

Reinforcement learning-based adaptive PID controller for DPS

Lee, Daesoo, Lee, Seung Jae, Yim, Solomon C.·2020·Ocean Engineering

Integrity signals

Registry

Crossref · 10.1016/j.oceaneng.2020.108053

Cites

37 of 37 references verified0 citation errors · 0 not checkable

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Authors
Lee, D., Lee, S. J., & Yim, S. C.
Affiliations
  • Korea Maritime and Ocean University (KR)
  • Oregon State University (US)
Corresponding author
Lee, Seung Jae
Venue
Ocean Engineering
Publisher
Elsevier BV
Published
2020-11
Volume
216
Pages
108053
ISSN
0029-8018 (ISSN-L)
OpenAlex
W3101203226
Cited by
80
References
37
Citations by year
2026: 11 · 2025: 19 · 2024: 13 · 2023: 18 · 2022: 15 · 2021: 4
FWCI
3.63
Type
journal article
Language
en
Open access
closed
Locations
Ocean Engineering (publishedVersion)
Funders
  • Korea Maritime and Ocean University
  • Oregon State University
  • Ministry of Trade, Industry and Energy
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
  • Physical Sciences › Engineering › Ocean Engineering › Ship Hydrodynamics and Maneuverability
  • Physical Sciences › Engineering › Ocean Engineering › Maritime Navigation and Safety
Keywords
dynamic positioning system, adaptive PID control, deep reinforcement learning, controller gain tuning, ship control, fuzzy logic comparison

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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