Robust Integral Sliding Mode Control of Non-minimum Phase DC-DC Converters
Bibliographic record
Abstract
In this paper, a modified integral sliding mode controller (ISMC) is proposed for non-minimum phase dc-dc converters. A boost dc-dc converter operating in continuous conduction mode (CCM) is chosen as a representative case study. The converter's bilinear model and its effect on the controller design necessitate the need for a nonlinear controller. Unlike a recently introduced ISMC, the proposed controller does not need a priori knowledge of initial conditions such as inductor current or capacitor voltage, nor does it implement a sign function to ensure a fast response or reachability. A novel modified sliding surface which ensures reachability, stability and reduces chattering at the steady-state operation point is proposed. Moreover, the proposed controller in conjunction with a disturbance observer (DO) enables the converter to maintain stable operation under disturbances and uncertainties. The system's robustness against drastic, discontinuous, autonomous, or non-zero derivative disturbances are enhanced by including an invariant saturation function. The performance of the proposed ISMC is tested and compared with a well-established linear controller to prove its validity under different types and levels of disturbances and uncertainties.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".