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Record W4403390212 · doi:10.1109/tase.2024.3473972

Event-Based Finite Time Stabilizability and Formation Control of Multi-Agent Systems

2024· article· en· W4403390212 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Automation Science and Engineering · 2024
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsUniversity of Victoria
FundersTaishan Scholar Project of Shandong ProvinceNational Natural Science Foundation of China
KeywordsMulti-agent systemControl (management)Computer scienceControl systemEvent (particle physics)Control theory (sociology)Control engineeringEngineeringDistributed computingArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

The paper considers the event-triggered stabilizability of multi-agent systems (MAS). To reduce the frequency of control input update and information transmission, a novel distributed event-triggered control strategy with state estimation feedback is designed to achieve stabilizability. Event-trigger rules involving dynamic threshold are constructed, which ensure the convergence of systems states in finite time. By utilizing iSCC (independent strongly connected component) partition and Lyapunov stability theory, sufficient criteria for achieving finite time stabilizability have been obtained. Moreover, formation control under event-trigger scheme is addressed based on the obtained stabilizability results. Besides, it has been proven that the event-trigger interval has a positive lower bound, which can avoid Zeno behavior. Finally, the effectiveness of the theoretical results is verified by simulation.Note to Practitioners—In the fields of control and engineering, system stability has always been a research hotspot. Traditional stability analysis often focuses on the asymptotic stability. However, many practical scenarios require the system to reach a stable state within a finite time, i.e., finite time stabilizability, such as rapid response systems, emergency braking systems, and responding to emergencies. Hence, the research on finite time stabilizability has important practical value. In order to reduce the frequency of control updates, this paper proposes the finite time stabilizability under event-trigger scheme and designs a novel feedback controller based on state estimation, which has not been discussed before. At the same time, to explore the impact of network topology on stabilizability, the sufficient conditions for achieving finite time stabilizability of the system are obtained by iSCC graph partition. Dynamic threshold in event-triggering conditions to guarantee the implementation of finite time stabilizability is constructed. Finally, the theoretical results are applied to formation control. The research is of great significance for improving system performance and meeting real-time requirements.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.233
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it