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Record W1990572733 · doi:10.1109/ias.2014.6978405

MTPA and FW based robust nonlinear speed control of IPMSM drive using Lyapunov stability criterion

2014· article· en· W1990572733 on OpenAlexaff
Garin Schoonhoven, M. Nasir Uddin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsLakehead University
Fundersnot available
KeywordsControl theory (sociology)BacksteppingLyapunov functionLyapunov stabilityStatorRobust controlNonlinear systemController (irrigation)TorqueStability (learning theory)Computer scienceRobustness (evolution)Electronic speed controlAdaptive controlControl engineeringEngineeringMathematicsControl systemControl (management)Physics

Abstract

fetched live from OpenAlex

This paper presents a robust nonlinear control technique for wide range speed operation of interior permanent magnet (IPM) synchronous machines based on the use of maximum torque per ampere (MTPA) and flux weakening (FW) controls. The global asymptotic stability of the drive is demonstrated by Lyapunov stability criterion in conjuncture with Barbalat's lemma. For the proposed nonlinear controller the MTPA and FW schemes are used to control the d-axis stator current below and above the rated speed, respectively. Control laws are developed based on adaptive backstepping technique to ensure robust system stability. The system nonlinearities are also accommodated through the online estimation of critical parameters. The control and adaptive backstepping laws have been successfully implemented in a MATLAB/Simulink simulation environment. Simulation results indicate robust speed tracking performance for the IPM synchronous motor ensuring global stability of the drive 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.439

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 head0.015
GPT teacher head0.205
Teacher spread0.190 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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