MétaCan
Menu
Back to cohort
Record W4411408501 · doi:10.1109/tie.2025.3572927

Hybrid Power Control Strategy for Electromechanical Braking System Based on Sliding Mode Approach

2025· article· en· W4411408501 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

VenueIEEE Transactions on Industrial Electronics · 2025
Typearticle
Languageen
FieldEngineering
TopicIndustrial Technology and Control Systems
Canadian institutionsUniversity of Victoria
FundersNational Natural Science Foundation of China
KeywordsSliding mode controlControl theory (sociology)Mode (computer interface)Dynamic brakingPower (physics)Automotive engineeringControl (management)Control engineeringEngineeringComputer scienceMaterials scienceBrakePhysicsNonlinear system

Abstract

fetched live from OpenAlex

In this article, a new hybrid power reaching law (PRL) is designed for the clamping force control of electromechanical braking (EMB) system. In order to overcome the chattering and slow global convergence of the traditional reaching law, a new arccotangent type auxiliary function is designed and the exponential term is optimized to realize the real-time adjustment of the gain coefficient, which can effectively improve the adaptive ability and convergence speed of sliding mode in different reaching stages. The existence, reachability and global finite time convergence of the new reaching law are proved. On this basis, a compound control method of clamping force for EMB system is proposed, which combines the proposed new hybrid PRL with disturbance observer to effectively carry out feedforward compensation, and the stability analysis method is proposed. Finally, the effectiveness and superiority of the proposed control strategy are verified by experimental platform.

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: none
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.235
Teacher spread0.216 · 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