A 2-Link Robot with Adaptive Sliding Mode Controlled by Barrier Function
Bibliographic record
Abstract
This paper focuses on designing several controllers to attenuate the chattering problem: a conventional sliding mode controller (CSMC) with a barrier function (BF) and a saturation function (SF), and an adaptive sliding mode controller (ASMC) with SF as well as ASMC with BF.The key distinction between CSMC and ASMC lies in the fact that ASMC doesn't require knowledge of the upper bounds of uncertainties and the determination of gain.ASMC can minimize the magnitude of control signals to an acceptably low level.Despite perturbations such as parameter uncertainty (PU), external disruption (ED), and the friction coefficient of Coulomb (CF), both CSMC and ASMC can effectively handle the 2-link robot.They stabilize the robot manipulator and achieve the required joint position.Due to the ASMC's lower controller gain compared to CSMC, the amplitude of the chatter (zigzag motion) has been minimized.Simulation results using MATLAB 2018a/Simulink demonstrate that the ASMC outperforms the CSMC in achieving more favorable outcomes.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".