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Improved Control for Three- Phase Rectifiers with Constant Power Loads

2023· article· en· W4378843300 on OpenAlexaff
Franco Degioanni, Ignacio Galiano Zurbriggen, Martin Ordonez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsControl theory (sociology)Rectifier (neural networks)PWM rectifierOperating pointController (irrigation)Overshoot (microwave communication)Three-phaseConvertersPulse-width modulationSettling timePhase marginMaximum power transfer theoremComputer sciencePower (physics)EngineeringVoltageElectronic engineeringElectrical engineeringControl engineeringAmplifierStep response

Abstract

fetched live from OpenAlex

Three-Phase Pulse Width Modulated (PWM) rec-tifiers are used in a different number of applications such as battery chargers, renewable energy systems, and motor drives, among others. Most of these systems adopt a multi-stage archi-tecture and the rectifier is used as the first stage to transfer the power from the AC source to the DC bus which is connected to one or more power converters to transfer the power to different types of loads. These load converters usually regulate their output currents and voltages, and consequently, they present constant power load (CPL) behavior from the rectifier's point of view. The presence of CPLs in the DC-bus provides additional constraints for the control design deteriorating the stability and dynamic performance of the system. Although conventional linear control approaches are able to regulate the DC-bus around the design operating point, they are ineffective when large CPL transients are applied, obtaining large settling times and voltage/current overshoot that can lead to system failure due to the collapse of the DC-bus. This work introduces an effective geometric-based controller that improves the dynamic performance of three- phase rectifiers loaded with CPLs in the DC-bus. The design and operation of the proposed controller are based on the normalized decoupled model of the rectifier in the synchronous reference frame (SRF). The derived model provides a simple graphical representation of the operating point dynamics in the state plane. In this way, the insights provided by the state plane analysis can be applied to define and derive a control law that achieves improved dynamic performance under CPL transients. The implementation of the proposed controller is validated by hardware-in-the-loop(HIL) experimental results and compared with the conventional linear approach.

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 score0.990
Threshold uncertainty score0.330

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 head0.006
GPT teacher head0.208
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

Citations2
Published2023
Admission routes1
Has abstractyes

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