Finite-time Nonlinear H∞ Control of Robot Manipulators with Prescribed Performance
Bibliographic record
Abstract
This study addresses the problem of constrained finite-time nonlinear H∞ tracking control for robot manipulators, despite the existence of actuator faults, system uncertainties, and external disturbances. Following the backstepping recursive design procedure, a constrained tracking control with a simple structure is developed to guarantee that the state errors converge to zero in finite time and the L2 gain of the closed-loop system is not greater than a prescribed value. Further, the favorable performance of the control system in steady-state and transient response, including maximum tracking error, maximum overshoot, and minimum convergence rate, are simultaneously imposed. Moreover, the developed controller is free of the singularity associated with the use of fractional power in finite-time control and it is not contingent on solving the Hamilton-Jacobi or Riccati equations. The fault tolerant capability and efficacy of the proposed control framework are demonstrated through simulation studies and comparisons with pertinent works.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".