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Record W2547052951 · doi:10.1049/iet-est.2016.0034

Fractional order fuzzy sliding mode controller for the quarter car with driver model and dual actuators

2016· article· en· W2547052951 on OpenAlexaboutno aff
S. Rajendiran, P. Lakshmi, B. Rajkumar

Bibliographic record

VenueIET Electrical Systems in Transportation · 2016
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsnot available
Fundersnot available
KeywordsActuatorDual (grammatical number)Dual modeControl theory (sociology)Quarter (Canadian coin)Controller (irrigation)Mode (computer interface)Fuzzy logicEngineeringAutomotive engineeringComputer scienceControl (management)Artificial intelligenceAerospace engineeringElectrical engineering

Abstract

fetched live from OpenAlex

The ride quality and travel comfort of the passenger is based on the type of the suspension system used in the vehicle. The active suspension system is one of the good choices to reduce the vibration and enhance the travel comfort. In this study, a quarter car with integrated seat suspension and driver model (QCSD) is considered for analysis. The controllers are designed for both single actuator (SA) and dual actuator (DA). To reduce the vibration and increase the travel comfort, different types of sliding mode controllers (SMCs) such as fuzzy SMC (FSMC), fractional order SMC and fractional order FSMC (FrFSMC) are designed and simulated in the active suspension system of the QCSD. Three types of road disturbances are used to stimulate the vibration in the system. The responses of the controllers with the QCSD are compared with the passive system and existing state feedback controller. The result shows that the FrFSMC performs better than the other controllers for DA as well as SA. While comparing the DA and SA, DA performs better than SA.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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Same venueIET Electrical Systems in TransportationSame topicVibration Control and Rheological FluidsFrench-language works237,207