Dual-Loop Estimation Based Adaptive Controller for Microgrid Connected Boost Converters
Bibliographic record
Abstract
DC microgrids are an excellent solution to integrate modern power generation and consumption with legacy infrastructure. Tightly regulated converters connecting ac and dc loads to the dc bus challenge the stability of the microgrid by showing a constant power load (CPL) behavior. This work proposes a dual-loop estimation based adaptive controller (DLEAC) for converters regulating the dc bus voltage, and a novel nonlinear estimator to identify the CPL and resistive power consumption components. The controller combines a feedback linearization control for the current loop with a traditional dual-loop proportional-integral control structure in which the proportional and integral gains of the voltage controller vary according to the estimated load power, allowing it to maintain constant dynamics at all operating conditions. The proposed methods show low computation complexity and are suitable for implementation on industry-standard microcontrollers. Detailed mathematical procedures, as well as comprehensive simulation and experimental validation are included in this article.
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How this classification was reachedexpand
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)
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 teacher head, 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".