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Extended State Observer-Based Finite-Time Trajectory Tracking Control of Fixed-Wing UAV With Prescribed Error Constraint

2022· article· en· W4288047810 on OpenAlexafffund
Yiwei Xu, Ziquan Yu, Fuyang Chen, Youmin Zhang

Bibliographic record

Venue2022 International Conference on Unmanned Aircraft Systems (ICUAS) · 2022
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsConcordia University
FundersState Key Laboratory of Mechanics and Control of Mechanical StructuresFundamental Research Funds for the Central UniversitiesNatural Science Foundation of Jiangsu ProvinceNanjing UniversityNatural Sciences and Engineering Research Council of CanadaAeronautical Science Foundation of ChinaChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsControl theory (sociology)TrajectoryTracking (education)Tracking errorObserver (physics)Computer scienceNonlinear systemTerminal sliding modeState observerBounded functionConstraint (computer-aided design)Fixed wingSliding mode controlWingMathematicsControl (management)EngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper proposes a finite-time trajectory tracking control (TTC) for a fixed-wing unmanned aerial vehicle (UAV) by a fast non-singular terminal sliding-mode strategy. A second-order nonlinear model is established to transform the UAV outer loop dynamics. To estimate the external disturbance, an extended state observer with finite-time observation capability is utilized. Furthermore, the trajectory tracking errors are constrained within a bounded region by prescribed performance control. Finally, simulations are conducted to verify the effectiveness of the finite-time TTC scheme.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.238
Teacher spread0.208 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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