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Record W4312690047 · doi:10.1016/j.ifacol.2022.10.182

Quadrotor Attitude and Altitude Tracking Control Using Finite Discrete-Time Linear Quadratic Tracking Controller

2022· article· en· W4312690047 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

VenueIFAC-PapersOnLine · 2022
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsControl theory (sociology)WeightingRobustness (evolution)Discrete time and continuous timeTracking (education)MathematicsEuler anglesComputer scienceControl (management)Physics

Abstract

fetched live from OpenAlex

In this paper, an optimal finite discrete-time linear quadratic tracking (LQT) control method is proposed to control the altitude and attitude of a quadrotor. First, the dynamic model of the quadrotor is derived using Newton-Euler equations. Next, non-linear equations of the quadrotor are written in the state space form and linearized around an equilibrium point. Then, continuous-time linear state-space equations are converted into discrete-time equations considering a specific sampling time. Moreover, the controller design process is completed by determining the performance index and the weighting matrices, and the optimal control input is acquired for the closed-loop system. In the end, the simulation results are shown to demonstrate the robustness of the controller against parameter uncertainties and show its performance in attenuating the external disturbance effect.

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 categoriesMeta-epidemiology (narrow)
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 score0.217
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.247
Teacher spread0.228 · 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