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Record W3198993070 · doi:10.1109/taes.2021.3111785

Path Following Control Design for a Gliding Missile

2021· article· en· W3198993070 on OpenAlexaff
Rollen S. D’Souza, Christopher Nielsen

Bibliographic record

VenueIEEE Transactions on Aerospace and Electronic Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicGuidance and Control Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMissileMissile guidanceControl theory (sociology)Inner loopEngineeringThrustOrientation (vector space)Inertial frame of referenceControl systemPath (computing)Loop (graph theory)Controller (irrigation)Computer scienceAerospace engineeringControl (management)PhysicsMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

A path following control architecture that drives a gliding missile, that is a missile without thrust, toward a prespecified linear path in an inertial frame using only torque control is developed and flight results are presented. A fast time-scale inner-loop control system stabilizes the orientation dynamics with a custom control law. Two slow time-scale outer-loop designs are proposed that render the inertial path exponentially stable for the missile’s translational dynamics. Since a gliding missile has no thrust input, the outer-loop is unable to directly actuate its control. Instead, we present an orientation extraction scheme to convert the outer-loop’s control signal into a desired orientation for the inner-loop. The control algorithm is implemented on a proprietary missile and empirical flight data are presented to demonstrate its effectiveness.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.206
Teacher spread0.195 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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