Design and Experiment of Interval Type-2 Fuzzy Hierarchical Sliding-Mode Control for Pendubot With Uncertainties
Bibliographic record
Abstract
In this article, a novel interval type-2 fuzzy hierarchical sliding mode control (IT2FHSMC) is proposed for controlling a pendubot system under uncertain conditions. The proposed methodology involves the construction of a hierarchical sliding-mode controller (HSMC) to provide rapid response and finite-time convergence, resulting in an excellent performance characteristics. Interval type-2 fuzzy logic control is applied to optimize HSMC for avoiding chattering phenomena and reducing the effects of uncertainty or noises. Moreover, key parameters of HSMC are tuned by using the balancing composite motion optimization algorithm. By employing the Lyapunov synthesis technique, the system's overall stability is ensured. Computer simulations and physical experiments are carried out to prove the efficacy of the IT2FHSMC compared with HSMC and type-1 hierarchical sliding-mode control and adaptive backstepping nonsingular fast terminal sliding-mode control for robust fault tolerant control.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".