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Record W3025244420 · doi:10.1109/tmech.2020.2995138

Control of Multiple Quad-Copters With a Cable-Suspended Payload Subject to Disturbances

2020· article· en· W3025244420 on OpenAlexafffund
Keyvan Mohammadi, Shahin Sirouspour, Ali Grivani

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPayload (computing)Control theory (sociology)UnderactuationPassivityController (irrigation)Computer scienceBounded functionObserver (physics)Energy (signal processing)Control engineeringEngineeringControl (management)MathematicsPhysics

Abstract

fetched live from OpenAlex

In this article, a new control scheme is proposed to enable multiple quad-copters to cooperatively carry a cable-suspended payload. This cascaded controller takes into account the quad-copters underactuation and exploits the energetic passivity of the payload-cables-drones multibody system to achieve stable control. The controller is simple and requires no information about the cables tensions. A storage function inspired by the mechanical energy of the system is introduced and used to derive the control laws that achieve semiglobal exponential stability. The stability is shown to be robust with respect to bounded disturbance forces acting on the quad-copters and the payload. Additionally, a time-domain observer estimates the energy that perturbations may inject to the system and dissipates it through variable damping. This helps suppress disturbance-induced oscillations. The effectiveness of the control strategy is demonstrated in several experiments.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations64
Published2020
Admission routes2
Has abstractyes

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Same venueIEEE/ASME Transactions on MechatronicsSame topicAdaptive Control of Nonlinear SystemsFrench-language works237,207