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Record W4386173000 · doi:10.54254/2753-8818/5/20230479

Comparison of anti-interference ability between PID controller and ADRC controller in UAV operation at ocean

2023· article· en· W4386173000 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTheoretical and Natural Science · 2023
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsPID controllerControl theory (sociology)Controller (irrigation)Control engineeringInterference (communication)Computer scienceEngineeringControl (management)Artificial intelligenceTemperature control

Abstract

fetched live from OpenAlex

With the maturity of UAV technology, drones can carry different instruments in the air to help people complete their work more efficiently. However, different working environments also bring different challenges to UAV control systems. This paper mainly discusses the quadrotor UVA and compares the stability of the Proportional Integral Derivative (PID) controller and Active disturbance rejection controller (ADRC) under the disturbance of gusts at sea. The flight principle of the quadrotor and the dynamic model of the quadrotor will be discussed on this basis. Then the composition and mathematical formula of the PID and ADRC controllers are introduced and compared. In general, this paper focused on the anti-jamming ability of different controllers under the influence of gust, which shows that although the ADRC controller has a more complex system and tedious parameter adjustment process in comparison with the PID controller, it has excellent anti-gust interference ability and can better serve the offshore operation of UAV.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.282
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it