Robust adaptive fixed-time control for a class of nonlinear systems with actuator faults
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Bibliographic record
Abstract
This paper addresses the output tracking problem of adaptive fixed-time fault-tolerant control for a class of nonlinear systems. In particular, we focus on two types of actuator faults: lock-in-place and loss of effectiveness. Specifically, a robust adaptive fault-tolerant controller is designed to compensate for the effect of actuator faults. By applying the classical backstepping design algorithm and fixed-time control theory, an adaptive fixed-time controller is developed, ensuring that the tracking error converges into a small neighbourhood around the origin within a fixed time where the convergence time is independent of initial conditions. Theoretical analysis and simulation outcomes prove that the closed-loop system is fixed-time stable and all signals are bounded by choosing the parameters appropriately. The effectiveness and feasibility of the presented control scheme are verified through the simulation results.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 it