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Record W2343039740 · doi:10.1109/tcst.2015.2505642

Inner–Outer Loop Control for Quadrotor UAVs With Input and State Constraints

2015· article· en· W2343039740 on OpenAlexaff
Ning Cao, Alan F. Lynch

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInner loopControl theory (sociology)Loop (graph theory)PID controllerController (irrigation)Tracking (education)EngineeringTrajectoryStability (learning theory)ThrustControl systemControl engineeringComputer scienceControl (management)PhysicsMathematicsAerospace engineeringArtificial intelligenceTemperature control

Abstract

fetched live from OpenAlex

The constrained control of unmanned aerial vehicles (UAVs) is a challenging task due to their nonlinear and underactuacted dynamics. This brief focuses on the position control of a quadrotor UAV with state and input constraints using an inner-outer loop control structure. The outer loop generates a saturated thrust, and the reference roll and pitch angles, while the inner loop is designed to follow these reference angles using a traditional PID controller. Assuming perfect inner loop tracking, the outer loop nested saturation controller guarantees global asymptotic stability for output regulation and tracking. The effect of nonideal inner loop tracking on closed-loop stability is analyzed. The proposed method is experimentally validated on an indoor quadrotor platform.

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 communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.217
Teacher spread0.204 · 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

Citations225
Published2015
Admission routes1
Has abstractyes

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