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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03 July 2026
Safety and Stability of Nonlinear Systems with Multiple High-Relative-Degree Time-Varying State Constraints: Theory and Its Application to UAV Tracking
It remains a challenge to stabilize a nonlinear system while satisfying time-varying state constraints for safety. In this study, we developed a time-varying nonlinear control barrier function (TVNCBF) approach to stabilize a nonlinear system with high-relative-degree state constraints. This approach mitigated potential conflicts among multiple control barrier function constraints, providing...
03 July 2026
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03 July 2026
Inside front cover
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03 July 2026
A Koopman-Based Equivalent-Input-Disturbance Tremor-Suppressing Strategy
Dear Editor, This letter introduces a novel Koopman-based equivalent-input-disturbance (EID) approach to enhance tremor suppression performance. Since the first-order linear model used in the conventional EID approach cannot accurately describe the wrist-exoskeleton system, we propose a Koopman modeling framework to construct a high-precision linear model. Furthermore, we incorporate an additional...
03 July 2026
Data-Physics Hybrid MPC for Disturbed Underactuated Crane: Design and Experiments
Dear Editor, This letter deals with model predictive control (MPC) of disturbed underactuated overhead crane systems under system uncertainties and disturbances. Considering the reliance on high-precision prediction model of MPC, we enhance first-principle dynamics with a residual term representing unmodeled dynamics. The residual, learned by a Gaussian process (GP) offline,...
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02 June 2026
Toward Resilient Vehicle Platooning: A Two-Layer Secure Control Architecture Against Hybrid Cyber-Physical Threats
This paper presents a hierarchical secure control framework for resilient vehicular platooning under hybrid cyber-physical threats, including coupled false data injection (FDI) and denial-of-service (DoS) attacks, as well as actuator faults. A two-layer architecture is adopted to decouple cyber-layer disruptions from physical-layer execution, thereby enhancing system modularity and fault isolation....
02 June 2026
Gain-Based Neural Secure Protection Control for Feedforward Nonlinear Systems with Unknown Control Coefficients and Impulsive FDI Attacks
This paper proposes a gain-based neural secure protection (GBNSP) control scheme for feedforward nonlinear systems subject to unknown control coefficients and impulsive false data injection (FDI) attacks. Notably, the nonlinear functions of the systems are relaxed to any continuous functions and the control coefficients are permitted to be constants with...
01 June 2026
Intelligent Safe Optimal Control Towards Koopman Operator-Driven Nonlinear Systems with Asymmetric State and Input Constraints
For unknown nonlinear systems subject to asymmetric state and input constraints simultaneously, this article establishes a safe value iteration paradigm to learn an optimal control policy in a data-based manner. Initially, the Koopman operator, instead of the black-box neural network, is applied to extract the inherent dynamics of the controlled...
01 June 2026
A Novel Model Free Adaptive Fuzzy Control for Discrete- Time T-S Fuzzy Systems with Local Nonlinear Models
This paper presents a model-free adaptive fuzzy control (MFAFC) scheme for discrete-time Takagi-Sugeno (T-S) fuzzy systems with local nonlinear models. First, the T-S fuzzy system is transformed into a linearized model using a dynamic linearization technique. Then, a model-free adaptive control scheme is developed for T-S fuzzy systems. Next, a...
01 June 2026
Perceiving the Battery Multi-Electrochemical States in Real-time Based on Model-Informed Neural Network
Accurate estimation of electrochemical states serves as a pathway to observe internal battery behaviors, effectively bridging the gap between micro mechanism and macro performance and enabling more precise control in an advanced battery management system. Yet conventional pseudo-two-dimensional (P2D) physics methods suffer from high computational complexity and limit their online...

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