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Record W2024094544 · doi:10.1109/smc.2014.6974475

Adaptive super twisting sliding mode control of a HVAC system

2014· article· en· W2024094544 on OpenAlexaff
Kaveh Kianfar, Mehrdad Saif, Roozbeh Izadi‐Zamanabadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of WindsorSimon Fraser University
Fundersnot available
KeywordsHVACSliding mode controlControl theory (sociology)Adaptive controlMode (computer interface)Computer scienceControl systemControl (management)Control engineeringEngineeringPhysicsElectrical engineeringMechanical engineeringArtificial intelligenceAir conditioningOperating system

Abstract

fetched live from OpenAlex

In this paper an adaptive super twisting sliding mode cascaded control strategy to control superheat temperature of an evaporator of Heating Ventilation Air Conditioning Systems(HVAC) is presented. Two internal loop and external loop of the cascaded controller are designed using sliding mode by utilizing feedback linearization method. By controlling superheat temperature, Tsh, in the external loop, and evaporating temperature of refrigerant, Te, in the internal loop, a better performance with robustness against parameter uncertainty is achieved. The value of superheat temperature is determined by using the estimated value of length of two phase flow of the refrigerant inside the evaporator. The performance of the proposed control strategy against disturbance and parameter uncertainties is illustrated through simulation in MATLAB/Simulink environment. It is shown that in comparison with super-twisting method, the proposed adaptive super twisting method improves the performance of system by reduction of undesirable chattering in the response of system.

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 score0.967
Threshold uncertainty score0.702

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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