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Record W4379875455 · doi:10.2514/6.2023-3801

Application of Type One Adaptive Fuzzy Sliding Mode Control System for the Longitudinal Motion of the Cessna Citation X

2023· article· en· W4379875455 on OpenAlexaff
S. Mohammad Hosseini, Georges Ghazi, Ruxandra Mihaela Botez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMotion controlMotion (physics)CitationFuzzy control systemAdaptive controlMode (computer interface)Sliding mode controlComputer scienceFuzzy logicControl theory (sociology)Control systemControl (management)PhysicsEngineeringArtificial intelligenceElectrical engineeringWorld Wide WebRobotHuman–computer interaction

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2023-3801.vid This paper presents a new approach developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE) to control the longitudinal motion of the Cessna Citation X aircraft during cruise using a Type One Adaptive Fuzzy Sliding Mode control system. To achieve this, the nonlinear model of the aircraft was generated using the simulation platform developed at LARCASE, which was validated with flight data obtained from a Level D Research Aircraft Flight Simulator (RAFS) manufactured by CAE Inc. The term Level-D refers to the highest certification level of an aircraft's flight dynamics that can be issued by the Federal Administration of Aviation (FAA, AC 120-40B). A Type One Fuzzy Logic system was used to approximate the uncertainties and nonlinearities that may hinder the aircraft's performance, while the sliding mode control technique was chosen to ensure that the pitch rate can track the desired reference value. To take into account the variations in the aircraft's parameters and dynamics in different flight conditions, an adaptive control approach was adopted for the proposed controller to update the parameters to their optimal values over time. Based on the simulation results, the proposed controller robustly maintained the pitch rate of the aircraft at the reference value in the presence of variation in aircraft dynamics, while providing smooth elevator deflection to prevent any mechanical damage to the actuators in various flight conditions.

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: Empirical · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score0.162

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 head0.019
GPT teacher head0.221
Teacher spread0.202 · 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
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
Published2023
Admission routes1
Has abstractyes

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