IEEE/CAA Journal of Automatica Sinica

Scope

The scope of the IEEE/CAA Journal of Automatica Sinica includes the field of automation. The objective of this journal is high quality and rapid publication of articles, with a strong focus on new trends, original theoretical and experimental research and developments, emerging technologies, and industrial standards in automation. Specifically, the Journal focuses on such areas as automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network based automation, robotics, computer-aided technologies for automation systems, sensing and measurement, navigation, guidance, and control, smart city, smart grid, big data and data mining, internet of things, cyber-physical systems, blockchain, cloud computing for automation, mechatronics.

IEEE/CAA Journal of Automatica Sinica was lunched on January 1, 2014.

Editor-in-Chief

Qing-Long Han
Editor-In-Chief

Distinguished Professor, PhD, MAE, FIEEE, FIFAC, FIEAust
Member of the Academia Europaea (The Academy of Europe)

Pro Vice-Chancellor (Research Quality)

Swinburne University of Technology
EN Building, Level 6, Room 602c
John Street, Hawthorn, Melbourne, Victoria 3122, Australia

Tel.:  +61 3 9214 3808

Fax.:  +61 9214 8264

Email: [email protected]

Articles

16 May 2025
Dear Editor, This letter deals with the distributed recursive set-membership filtering (DRSMF) issue for state-saturated systems under encryption-decryption mechanism. To guarantee the data security, the encryption-decryption mechanism is considered in the signal transmission process. Specifically, a novel DRSMF scheme is developed such that, for both state saturation and encryption-decryption mechanism,...
16 May 2025
DeepSeek, a Chinese artificial intelligence (AI) startup, has released their V3 and R1 series models, which attracted global attention due to their low cost, high performance, and open-source advantages. This paper begins by reviewing the evolution of large AI models focusing on paradigm shifts, the mainstream large language model (LLM)...
16 May 2025
This paper investigates the bipartite consensus control problem for discrete time nonlinear multiagent systems (MASs) based on data-driven adaptive method. To begin with, a dynamic linearization strategy is utilized to establish the relationship between bipartite tracking error and control input for MASs. Secondly, the unknown parameter linearly associated with control...
16 May 2025
Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits (ICs), requiring high-precision synchronous motion between the reticle and wafer stages. Disturbances generated by each stage during high-acceleration movements are transmitted through the base frame, resulting in degradation of synchronization performance. To address this challenge, this paper...
15 May 2025
The passing of Professor Wolter “Wolt” Fabrycky, an outstanding member and great leader, is a big loss to our international systems engineering professional community. “Wolt was a legend in the systems engineering community with his teaching, advising, and dissemination of knowledge through the books he authored.”, as stated by Professor...
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31 March 2025
Competition-based $k-mathbf{winners}-mathbf{take}-mathbf{all} (k mathbf{WTA})$ networks play a crucial role in multi-agent systems. However, existing $k mathbf{WTA}$ networks either neglect the impact of noise or only consider simple forms, such as constant noise. In practice, noises often exhibit time-varying and nonlinear characteristics, which can be modeled using nonlinear functions and approximated...
31 March 2025
The maneuvering of a large-scale unmanned aerial vehicle (UAV) swarm, notable for flexible flight with collision-free, is still challenging due to the significant number of UAVs and the compact configuration of the swarm. In light of this problem, a novel parallel control method that utilizes space and time transformation is...
31 March 2025
Adaptive graph neural networks (AGNNs) have achieved remarkable success in industrial process soft sensing by incorporating explicit features that delineate the relationships between process variables. This article introduces a novel GNN framework, termed entropy-regularized ensemble adaptive graph $(mathbf{E}^{mathbf{2}}mathbf{AG})$, aimed at enhancing the predictive accuracy of AGNNs. Specifically, this work pioneers...
04 March 2025
Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems (ITS) in the real world. As a state-of-the-art generative model, the diffusion model has proven highly successful in image generation, speech generation, time series modelling etc. and now opens a new avenue...
03 March 2025
As embodied intelligence (EI), large language models (LLMs), and cloud computing continue to advance, Industry 5.0 facilitates the development of industrial artificial intelligence (IndAI) through cyber-physical-social systems (CPSSs) with a human-centric focus. These technologies are organized by the system-wide approach of Industry 5.0, in order to empower the manufacturing industry...

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