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Record W2143404182 · doi:10.1109/ccece.2006.277850

Sliding Mode Controller For Pulse Width Modulation Based DSTATCOM

2006· article· en· W2143404182 on OpenAlexaff
M.A. Eldery, Ehab F. El‐Saadany, M. Salama

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPulse-width modulationMode (computer interface)Control theory (sociology)Modulation (music)Controller (irrigation)Computer sciencePulse-frequency modulationElectronic engineeringFrequency modulationVoltagePhysicsAcousticsElectrical engineeringEngineeringBandwidth (computing)Amplitude modulationTelecommunicationsControl (management)

Abstract

fetched live from OpenAlex

In this paper, a controller is designed to achieve robust control for DSTATCOM which is controlled as a voltage source inverter utilizing pulse width modulation. DSTATCOM dynamic equations show that the nonlinearities of the DSTATCOM and uncertainties of the system model have large contribution in system dynamic response. Hence, a robust nonlinear control strategy based on sliding mode control, which is a standard approach to tackle the parametric and modeling uncertainties of a nonlinear system, is chosen for the control. For sliding mode controller, Lyaponov stability method is applied to keep the nonlinear system under control. The sliding mode approach is a method which transforms a higher-order system into first-order system. In that way, a simple control algorithm can be applied, which is very straightforward and robust. The simulation results show the ability of the proposed controller to give an enhanced performance at all operating points and with different load types.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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

Citations20
Published2006
Admission routes1
Has abstractyes

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Same topicAdaptive Control of Nonlinear SystemsFrench-language works237,207