IEEE SMC: Systems, Man, & Cybernetics Society

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]

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Articles

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02 July 2025
Hybrid Event-Triggered Control with Stability Analysis
In this paper, a novel hybrid event-triggered control (ETC) method is developed based on the online action-critic technique, which aims at tackling the optimal regulation problem of discrete-time nonlinear systems. In order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain...
02 July 2025
Nash Bargaining Solution-Based Multi-Objective Model Predictive Control for Constrained Interactive Robots
Dear Editor, This letter proposes a novel Nash bargaining solution-based multi-objective model predictive control (MPC) scheme to deal with the interaction force control and the path-following problem of the constrained interactive robot. Considering the elastic interaction force model, a mechanical trade-off always exists between the interaction force and position, which...
02 July 2025
Machine Learning-Based Prediction of Depressive Disorders via Various Data Modalities: A Survey
Depression, a pervasive mental health disorder, has substantial impacts on both individuals and society. The conventional approach to predicting depression necessitates substantial collaboration between health care professionals and patients, leaving room for the influence of subjective factors. Consequently, it is imperative to develop a more efficient and accessible prediction methodology...
01 July 2025
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01 July 2025
Prescribed Performance Control of Nonlinear Systems With Unknown Sign-Switching Virtual Control Coefficients
The problem of high-performance tracking control for the lower-triangular systems with unknown sign-switching virtual control coefficients as well as unmatched disturbances is investigated in this paper. Instead of the online estimation algorithm, the sliding mode method and the Nussbaum gain technique, a group of orientation functions are employed to handle...
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01 July 2025
System Identification in the Network Era: A Survey of Data Issues and Innovative Approaches
System identification is a data-driven modeling technique that originates from the control field. It constructs models from data to mimic the behavior of dynamic systems. However, in the network era, scenarios such as sensor malfunctions, packet loss, cyber-attacks, and big data affect the quality, integrity, and security of the data....
16 June 2025
Embodied Multi-Agent Systems: A Review
Multi-agent systems (MASs) have demonstrated significant achievements in a wide range of tasks, leveraging their capacity for coordination and adaptation within complex environments. Moreover, the enhancement of their intelligent functionalities is crucial for tackling increasingly challenging tasks. This goal resonates with a paradigm shift within the artificial intelligence (AI) community,...
13 June 2025
Data-Driven Bipartite Consensus Control for Large Workpieces Rotation of Nonlinear Multi-Robot Systems
In this paper, a novel data-driven bipartite consensus control scheme is proposed for the rotation problem of large workpieces with multi-robot systems (MRSs) under a directed communication topology. The rotation of a large workpiece is described as the MRSs with cooperation and antagonism interaction. By the signed graph theory, it...
13 June 2025
Mixed Motivation Driven Social Multi-Agent Reinforcement Learning for Autonomous Driving
Despite great achievement has been made in autonomous driving technologies, autonomous vehicles (AVs) still exhibit limitations in intelligence and lack social coordination, which is primarily attributed to their reliance on single-agent technologies, neglecting inter-AV interactions. Current research on multi-agent autonomous driving (MAAD) predominantly focuses on either distributed individual learning or...
16 May 2025
DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models
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)...

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