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ieee-transactions-on-automatic-control

Use when targeting IEEE Transactions on Automatic Control (TAC) or deciding whether a systems-and-control manuscript fits this venue. Encodes the jo…

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技能内容

IEEE Transactions on Automatic Control (ieee-transactions-on-automatic-control)

Journal positioning

IEEE Transactions on Automatic Control (TAC) is the flagship archival journal of

the systems-and-control field, publishing rigorous theoretical and methodological

contributions across control theory, estimation, optimization for control, hybrid

and networked systems, and the mathematics of dynamical systems. The defining

expectation is a provable, general result: a new theorem, a new method with

guarantees, or a sharp answer to an open systems-and-control question. Application

papers that tune a known controller for one plant, or simulation studies without a

generalizable theoretical contribution, are a poor fit and are routinely returned.

This skill is a fit / venue-selection / re-framing tool. It does not replace

the journal's current official author information. Before submitting, re-check the

live IEEE TAC author guidance and submission system.

When to trigger

  • The author names TAC as the target for a control-theory, estimation, or

dynamical-systems manuscript and wants a fit/framing check.

  • A control contribution must be re-framed from "we controlled this system" into a

general theorem or method statement with explicit assumptions.

  • The author is choosing between TAC and automatica, or between a full Paper and a

Technical Note / shorter contribution.

  • The author needs TAC's specific desk-reject heuristics and a credible

alternative-venue route for application-heavy work.

Scope & topic fit

  • Control theory: stability, robust/H-infinity, adaptive, nonlinear, optimal,

model-predictive, and geometric control, with new analysis or synthesis results.

  • Estimation and filtering: state estimation, observers, Kalman-type and set-membership

filtering, when the contribution is a new guarantee or method, not a tuning.

  • Networked, distributed, multi-agent, and hybrid/switched systems; event-triggered

and quantized control; consensus and distributed optimization with convergence

proofs.

  • Optimization, game-theoretic, and learning-based control when the result is

rigorous (stability/convergence/regret guarantees), not purely empirical.

  • Stochastic systems and control; systems-theoretic aspects of dynamical systems.

Method & evidence bar

  • The central object is a theorem with a correct, complete proof under clearly

stated, non-vacuous assumptions; the generality and tightness of the result are

what carry the paper.

  • Assumptions must be reasonable and explicitly discussed: a result that holds only

under assumptions that effectively presuppose the conclusion is not a contribution.

  • Numerical examples are illustrations, not evidence of generality; simulations

support intuition but never substitute for the proof.

  • Position against the closest prior results precisely: state what is new relative to

existing theorems (weaker assumptions, larger class of systems, tighter bound,

constructive vs. existence).

  • Notation must be standard and self-consistent; the problem formulation must be

mathematically precise before any result is stated.

Structure & house style

  • IEEE double-column format; TAC publishes full Papers and shorter

Technical Notes / Correspondence — match the article type to the size and

scope of the contribution, and re-check current definitions on the live guide.

  • Problem statement and assumptions come early and precisely; main results are

stated as numbered theorems/propositions/lemmas with proofs (in-text or in an

appendix per the current format).

  • The introduction must position the open problem and the gap in existing theory,

not survey applications.

  • Figures are used sparingly and purposefully (block diagrams, convergence/phase

plots); the paper stands on its theorems, not its plots.

  • Supplementary proofs/appendices carry length-limited material per current rules.

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and

../../resources/official-source-map.md; start from the IEEE Author Center

anchors, then cite the current TAC-specific page you checked.

  • Search the live site for "IEEE Transactions on Automatic Control information for

authors" and follow the current ScholarOne/IEEE version.

  • Re-check article types (Paper vs. Technical Note), page/length limits and

overlength policy, and the IEEE double-column template.

  • Confirm reproducibility/data/code expectations for any numerical or experimental

results.

  • Re-check ORCID, competing-interests, funding, author-contribution, and AI-use

disclosure requirements, and IEEE open-access options.

  • If the live official instructions conflict with this skill, the official

instructions win.

Pre-submission self-check

  • [ ] The contribution is stated as a general theorem/method with explicit, non-vacuous assumptions — not as a successful control of one plant.
  • [ ] Every main result has a complete, correct proof; simulations are illustrative only.
  • [ ] The novelty is pinned to specific prior theorems (weaker assumptions / wider class / tighter bound / constructive).
  • [ ] The problem formulation is mathematically precise before any result is stated.
  • [ ] Article type (Paper vs. Technical Note) matches the scope, and length is within current limits.
  • [ ] Notation is standard, consistent, and defined.

Common desk-reject triggers

  • Application/tuning paper: a known control method applied to one specific system with

no generalizable theoretical contribution.

  • Simulation-only "validation" with no theorem, or a theorem whose assumptions

effectively assume the result.

  • Incremental extension of an existing result with no weakening of assumptions or

broadening of the system class.

  • Incorrect, incomplete, or hand-waved proofs; mismatched or undefined notation.
  • Scope mismatch: a signal-processing, pure-optimization, or machine-learning paper

with control only as a label.

Re-routing decision

  • Methodological control breadth, longer development → automatica.
  • Signal-processing estimation/detection as the core → ieee-transactions-on-signal-processing.
  • Power-system or power-electronics control application → ieee-transactions-on-power-systems / ieee-transactions-on-power-electronics.
  • Robotics planning/control as the central contribution → ieee-transactions-on-robotics / the-international-journal-of-robotics-research.
  • Optimization theory with no control object → a dedicated optimization venue.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] IEEE Transactions on Automatic Control
[Topic tags] <2–3 closest control subtopics>
[Contribution type] theorem / method-with-guarantee / open-problem answer
[Method/evidence] <does the result clear the generality + proof-rigor bar?>
[Top risk] <the single most likely reason for rejection>
[Article type] Paper / Technical Note
[Official items to re-check] <article type / length / template / data-code / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>

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原文件路径Engineering-Technology-Journal-Skills/skills/ieee-transactions-on-automatic-control/SKILL.md

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