Reconfigurable cooperative control of networked lagrangian systems under actuator saturation constraints
Bibliographic record
Abstract
In this study, a reconfigurable control strategy is proposed for state synchronisation and tracking control of networked (electro-) mechanical Euler–Lagrange (EL) systems that are subject to input saturation constraints that may arise as a result of actuator faults or failures. The reconfigurable controller consists of three main parts. The first part, denoted as the constrained ‘nominal’ controller, is a distributed controller that is employed to guarantee global stability of the multi-agent-networked EL system provided that certain mild connectivity conditions are satisfied in the absence or presence of actuator saturation constraints. The second part, denoted as the constrained ‘reconfigured’ controller, is a non-linear smooth distributed controller that has a different structure and gains from the constrained nominal controller. This controller can preserve the overall control objectives in the presence of actuator faults and actuator saturation constraints. The third part is a switching strategy between the constrained nominal and the constrained reconfigured controllers. Global stability as well as asymptotic convergence of the synchronisation and the tracking errors to origin for switchings under certain conditions between the constrained nominal and the constrained reconfigured controllers with non-vanishing dwell-times for a fixed network topology are shown to be guaranteed. Simulation results of a network of three robotic manipulators are reported to demonstrate and validate the merits of the proposed controllers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".