Academic Journal
Q1IEEE Transactions on Automatic Control
About IEEE Transactions on Automatic Control
IEEE Transactions on Automatic Control is a scholarly journal published by Institute of Electrical and Electronics Engineers Inc.. SCImago 2025 places it in Q1 with an SJR of 3.929 and an H-index of 359.
Its listed coverage is 1963-2026 and its research categories include Computer Science Applications (Q1); Control and Systems Engineering (Q1); Electrical and Electronic Engineering (Q1). The 2025 dataset reports 879 documents and 19460 citations across the latest three-year reporting window.
IEEE Transactions on Automatic Control: Leading the Future of Control Systems Research
The IEEE Transactions on Automatic Control is a premier, peer-reviewed journal published by the Institute of Electrical and Electronics Engineers (IEEE). Recognized globally, this publication plays a critical role in advancing the field of automatic control systems. It offers cutting-edge research and theoretical insights that contribute to the development of intelligent systems and automation technologies. For researchers, academicians, and industry professionals, this journal is an essential source for the latest innovations in control theory and practice.
What is IEEE Transactions on Automatic Control?
IEEE Transactions on Automatic Control is dedicated to publishing high-quality research papers in the areas of control theory, systems engineering, and signal processing. The journal covers a broad spectrum of topics including:
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Linear and nonlinear control systems
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Robust and adaptive control
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Stochastic control and filtering
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Optimization in control
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Networked and distributed systems
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Machine learning in control applications
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Cyber-physical systems and control of autonomous agents
Each article is subjected to a rigorous peer-review process to ensure the highest standards of academic excellence and technical depth.
Why is it Important?
As automation and intelligent systems become increasingly integral to modern technology, the research published in IEEE Transactions on Automatic Control shapes the future of engineering, robotics, and artificial intelligence. This journal is widely cited in scholarly work and continues to influence innovations in a wide range of applications—from industrial automation and aerospace engineering to smart grids and autonomous vehicles.
The publication serves as a bridge between theoretical advancements and practical implementations, helping engineers and scientists apply the latest control techniques in real-world systems.
Key Features and Benefits
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Authoritative Research: The journal publishes only the most impactful and original research, making it a go-to source for thought leadership in automatic control.
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Wide Reach: With a strong international readership and high citation index, publishing in IEEE Transactions on Automatic Control provides global exposure.
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Interdisciplinary Focus: The journal attracts work from various domains including electrical engineering, mechanical systems, artificial intelligence, and mathematics.
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SEO and Digital Access: Indexed in leading academic databases such as Scopus, Web of Science, and IEEE Xplore, the journal is easily accessible to researchers around the world.
How to Access or Submit
IEEE Transactions on Automatic Control is available through IEEE Xplore, the IEEE’s digital library. Subscribers can access full articles, while non-members can purchase single issues or papers. Authors interested in publishing can submit manuscripts via the IEEE Manuscript Central portal. Strict submission guidelines ensure only the most innovative and relevant work is published.
Final Thoughts
For those working in or studying control systems, automation, robotics, and related fields, the IEEE Transactions on Automatic Control is a vital resource. Its reputation, depth, and influence make it one of the top journals in electrical and control engineering. Whether you're seeking the latest developments or aiming to publish groundbreaking research, this journal offers an unparalleled platform for knowledge exchange and professional growth.
Journal Metrics
Metrics can change by reporting year. Verify time-sensitive values with the publisher or indexing service.
Aims & Scope
Scope of IEEE Transactions on Automatic Control: Advancing the Science of Systems and Control
The IEEE Transactions on Automatic Control is one of the most prestigious journals in the field of control systems engineering. Published by the Institute of Electrical and Electronics Engineers (IEEE), this peer-reviewed journal is a critical resource for researchers, academics, and industry professionals who work in the domain of automatic control theory, applications, and systems engineering.
Core Focus and Areas of Interest
The journal focuses on publishing high-quality, original research papers that make significant contributions to the field of automatic control. The scope encompasses a wide range of topics, including but not limited to:
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Linear and Nonlinear Systems
Analysis and design methods for both linear and nonlinear control systems, stability, robustness, and performance. -
Adaptive and Optimal Control
Techniques that adapt to system changes in real time and those that aim to optimize system performance under constraints. -
Stochastic and Robust Control
Systems that handle uncertainty and noise, with emphasis on probabilistic and deterministic robust strategies. -
Distributed and Networked Control Systems
Control of interconnected systems, including multi-agent systems and cyber-physical systems. -
Control of Hybrid and Discrete-Event Systems
Integration of continuous and discrete dynamics, including event-driven control and switching systems. -
Learning-Based and Data-Driven Control
Emerging fields that use machine learning and artificial intelligence in control system design.
Applications in Diverse Domains
IEEE Transactions on Automatic Control encourages submissions that explore innovative applications of control theory in a wide array of industries and technologies. These include:
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Autonomous vehicles and robotics
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Smart grids and energy systems
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Aerospace and avionics control systems
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Industrial process automation
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Biomedical systems and healthcare technologies
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Environmental and climate control systems
By promoting interdisciplinary approaches, the journal bridges the gap between theoretical advances and real-world implementations.
Audience and Impact
With its rigorous peer-review process and high impact factor, IEEE Transactions on Automatic Control is widely regarded as a benchmark publication in the control systems community. The journal serves:
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Researchers looking for cutting-edge developments and theoretical innovations.
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Educators seeking reliable academic content for teaching advanced control theory.
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Engineers and Practitioners implementing control strategies in complex systems.
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Graduate Students exploring potential research directions and methodologies.
Submission and Editorial Standards
The journal maintains a high standard for academic excellence. All submissions undergo thorough peer review by experts in the field, ensuring the quality, originality, and significance of the research. Authors are encouraged to submit papers that clearly present theoretical results, supported by mathematical rigor, simulations, or experimental validation.
Recent Research Articles
Latest publications matched automatically by ISSN.
Accelerated Consensus-Based SPSA Algorithm for Multisensor Multitarget Tracking Problem
Victoria Erofeeva, Oleg Granichin, Anna Sergeenko
2026-09 · DOI: 10.1109/tac.2026.3678473Artificial Multistep Ahead Optimal Strategy for Opinion Dynamics With Delayed Decision Making
Qingsong Liu, Wenjun Mei, Li Chai
2026-09 · DOI: 10.1109/tac.2026.3677730Online Learning and Control Synthesis for Reachable Paths of Unknown Nonlinear Systems
Yiming Meng, Taha Shafa, Jesse Wei, Melkior Ornik et al.
2026-09 · DOI: 10.1109/tac.2026.3674029Optimal Sensor Selection for $K$-Step Prognosability Verification and Enforcement of Unbounded Petri Nets
Shaopeng Hu, Ruotian Liu, Maria Pia Fanti, Zhiwu Li et al.
2026-09 · DOI: 10.1109/tac.2026.3683281Event-Triggered Byzantine-Resilient Algorithm for Distributed Optimization With Sublinear Convergence
Yun-Long Li, Yan-Wu Wang, Xiao-Kang Liu, Jiaqi Yan et al.
2026-09 · DOI: 10.1109/tac.2026.3673146Multi-Partite Output Regulation of Multi-Agent Systems
Kursad Metehan Gul, Selahattin Burak Sarslmaz
2026-09 · DOI: 10.1109/tac.2026.3682209Data-Driven Control of Continuous-Time LTI Systems via Non-Minimal Realizations
Alessandro Bosso, Marco Borghesi, Andrea Iannelli, Giuseppe Notarstefano et al.
2026-09 · DOI: 10.1109/tac.2026.3680845On the Oracle Complexity of Interpolation-Based Gradient Descent
Dongmin Lee, William Lu, Anuran Makur
2026-09 · DOI: 10.1109/tac.2026.3682210Table of Contents
2026-09 · DOI: 10.1109/tac.2026.3718670Safety-Constrained Control With Tunable Performance Using Dual-Mode Method and Local Trajectory Adjustment
Xingqiang Zhao, Yongduan Song, Changyun Wen
2026-09 · DOI: 10.1109/tac.2026.3675547Reaching Resilient Leader–Follower Consensus in Time-Varying Networks via Multihop Relays
Liwei Yuan, Hideaki Ishii
2026-09 · DOI: 10.1109/tac.2026.3680751Differentially Private Gradient-Tracking-Based Distributed Stochastic Optimization Over Directed Graphs
Jialong Chen, Jimin Wang, Ji-Feng Zhang
2026-09 · DOI: 10.1109/tac.2026.3678834An Efficient Algorithm for Nonlinear Regression Problems With Huber Loss
Guang-Yong Chen, Xiang-Xiang Su, Min Gan, Peng Xue et al.
2026-09 · DOI: 10.1109/tac.2026.3683294One-Bit Consensus of Controllable Linear Multiagent Systems With Communication Noises
Ru An, Ying Wang, Yanlong Zhao, Ji-Feng Zhang et al.
2026-09 · DOI: 10.1109/tac.2026.3680847Finite-Time Resilient Output Feedback Control for Semi-Markov Jump Systems With Imprecise Matching and Jumping Information
Haiyang Chen, Guangdeng Zong, Guangming Zhuang, Shiji Song et al.
2026-09 · DOI: 10.1109/tac.2026.3676341Model Reference Adaptive Control of Almost Periodic Piecewise Linear Systems With Variable Periods and Disturbance Input
Tan Zhuolin, Xiaochen Xie, Jiantai Huang, Huijun Gao et al.
2026-09 · DOI: 10.1109/tac.2026.3674419Data-Driven Cooperative Output Regulation via Output Feedback Control
Yifei Li, Wenjie Liu, Gang Wang, Lihua Xie et al.
2026-09 · DOI: 10.1109/tac.2026.3682640Distributed Resilient Fixed-Time Control for Cooperative Output Regulation of MASs Over Directed Graphs Under DoS Attacks
Wenji Cao, Lu Liu, Dan Zhang, Gang Feng et al.
2026-09 · DOI: 10.1109/tac.2026.3682978Gain and Performance Constrained LQR Design via SDP
Graziano Chesi
2026-09 · DOI: 10.1109/tac.2026.3672339High-Probability Convergence Theory for Distributed Composite Optimization With Sub-Weibull Noises
Zhan Yu, Zhongjie Shi, Deming Yuan
2026-09 · DOI: 10.1109/tac.2026.3687492Reviews
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April 22, 2025 at 3:16 am
April 22, 2025