Integral Sliding Mode Flight Controller Design for a Quadrotor and the Application in a Heterogeneous Multi-Agent System
Bibliographic record
Abstract
This paper investigates a novel integral sliding mode control (ISMC) strategy for the waypoint tracking control of a quadrotor in the presence of model uncertainties and external disturbances. The proposed controller has the inner-outer loop structure: The outer loop is to generate the reference signals of the roll and pitch angles, while the inner loop is designed by using the ISMC technique for the quadrotor to track the desired x, y positions and roll and pitch angles. The Lyapunov stability analysis is provided to show that the negative effects of the bounded model uncertainties and external disturbances can be significantly decreased. The designed controller is then applied to a heterogeneous multi-agent system (MAS) consisting of quadrotors and two-wheeled mobile robots (2WMRs) to solve the consensus problem. We present the control algorithms for the 2WMRs and quadrotors. Consensus of the heterogeneous MAS can be reached if the switching graphs always have a spanning tree. Finally, the experimental tests are conducted to verify the effectiveness of the proposed control methods.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".