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Record W2802829176 · doi:10.1139/tcsme-2004-0007

Combined H-Infinity Model-Matching Control and Dual-rate Digital Redesign for Missile Acceleration Autopilots

2004· article· en· W2802829176 on OpenAlexaffvenue
C.A. Rabbath, Nabil Aouf, N. Hori, Marc Lauzon

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsConcordia UniversityMcGill UniversityDefence Research and Development Canada
Fundersnot available
KeywordsAutopilotMissileControl theory (sociology)AccelerationFlight envelopeInner loopAirframeEngineeringMissile guidanceControl engineeringControl systemComputer scienceAerodynamicsController (irrigation)Aerospace engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper proposes a missile acceleration autopilot obtained via H ∞ model-matching control and dual-rate digital redesign. The first stage of the procedure consists in solving an H ∞ model-matching problem in continuous-time. The second stage of the proposed approach is the conversion of the optimal continuous-time control system to a fast-inner-loop rate, slow-outer-loop rate digital control system using a dual-rate digital redesign approach which takes into account the closed-loop dynamics of the missile autopilot in the conversion. Reducing the order of the autopilot transfer functions and scheduling the controllers over the entire flight envelope constitute the last stages of the proposed approach. The proposed dual-rate missile acceleration autopilot is very useful in practice since it provides satisfactory closed-loop performances over an extended range of sampling rates, as compared with other digital autopilots. A nonlinear missile airframe dynamics model is used to demonstrate the application of the proposed missile autopilot design technique and the comparison with well-known approaches.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.203
Teacher spread0.186 · 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.

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

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
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicAdaptive Control of Nonlinear SystemsFrench-language works237,207