A DSP-Based Implementation of a New Nonlinear Control for a Three-Phase Neutral Point Clamped Boost Rectifier Prototype
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Bibliographic record
Abstract
This work presents the design and implementation of a nonlinear control strategy for a three-phase three-level neutral-point-clamped boost rectifier. The adopted control consists of nonlinear feedback linearization technique. The nonlinear state-space model of the rectifier was obtained in the dq0 reference frame. The input/output feedback linearization is then applied and the linearizing control law is derived. Therefore, the resulting model is linearized and decoupled in three independent subsystems. Afterwards, the stabilizing controllers are designed based on linear techniques to control line currents, output, and neutral point voltages. The control law is designed using Simulink/Matlab and applied to the converter via a 1.8-kHz pulsewidth modulator (PWM). Both control law and PWM signals are executed in real time using the DS1104 DSP of dSPACE. A 1.2 kW laboratory prototype is built for validation purposes. The proposed control law robustness is validated for diverse severe load and system parameter variations. It shows robust performance in terms of high power factor, low total harmonic distortion and output voltage ripples, small overshoot, and short settling time.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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