Synchronization to disturbed AC utility network signals in power electronics applications
Bibliographic record
Abstract
This thesis presents a digital signal processing system for synchronization to AC utility network signals in power electronics applications. The proposed system is suitable in applications where the signal to which synchronization must be accomplished contains severe disturbances and where the signal frequency and the signal amplitude are variable. The system is based on a multirate phase-locked loop (PLL). The main advantages of the multirate approach are that it relaxes the implementation of the antialiasing filter and it enables one to accommodate the varying amplitude of the input signals. The antialiasing filter, which is in this case a high order bandpass filter, is implemented in the digital part of the system. This feature is achieved by applying the oversampling technique to the input signal. The antialiasing filter automatically adapts to the input signal frequency through the system's variable sample rate operation. The thesis deals with modeling, analysis, control and implementation issues of the proposed system. Nonlinear and linear state-space models and a transfer function model of the system are derived. The system's control aspects are discussed using the derived transfer function model. The system is implemented on a platform based on the Texas Instruments TMS320C31 floating point digital signal processor. Tracking properties of the implemented system are verified with realistic signals such as a sinusoidal signal containing notch type disturbance and noise and an arc furnace voltage signal.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".