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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28 August 2026
Nonlinear Set-Membership Estimation and Its Application to the Design of an Interacting Multiple Model Estimator
In this paper, an interacting multiple model (IMM) nonlinear set-membership estimation (NSME) is investigated for nonlinear systems with unknown-but-bounded (UBB) noises. First, two different NSME approaches are developed based on whether the characteristics of different noises are employed. Based on the proposed NSME method, a novel IMM-NSME algorithm is developed,...
28 August 2026
A Knowledge-Imparting Generative Modelling Framework for Heterogeneous Federated Learning
Federated learning aims to provide security for client data privacy in practical machine learning applications. In principle, a global server aggregates the models produced by local clients to obtain a global model. However, the server is challenged when collaborating with local clients handling non-identically distributed data without authorisation to access...
28 August 2026
Distributed Secure Estimation of LTI System Under Unbounded Multisource Attack and Unknown Input
Dear Editor, This letter investigates the distributed secure estimation of a linear time-invariant (LTI) system with an unknown input command when multisource attacks compromise different communication links through various malicious signals. The dimension of multisource attacks is generally larger than the dimension of measurements, which is a challenge for attack...
28 August 2026
Human-in-the-Loop Control for Industrial IoT Systems: A Modified FAS Predictive Control
Dear Editor, Based on the fully actuated system (FAS) theory, this letter aims at a human-in-the-loop control (HLC) problem for industrial Internet of Things (IoT) systems. The main role of HLC is to directly manipulate the tracking target by sending a control command of human operators to the non-zero input...
28 August 2026
Data-Driven Reinforcement Learning and Approximate Optimal Control for Linear Time-Varying Systems
Dear Editor, This letter investigates the optimal control problem for linear time-varying systems through a novel data-driven reinforcement learning (RL) method. While the optimal solution for such systems can theoretically be obtained by solving the well-known differential Riccati equation (DRE), the time-varying nature of DRE makes analytical solutions intractable even...
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03 August 2026
Proportional-Integral Observer Design for Multi-Rate Systems Under Decode-and-Forward Relays: Tackling Power-Dependent Packet Dropouts
In this paper, the problem of proportional-integral observer (PIO) design is investigated for a class of discrete-time multi-rate systems with multiple sensors, with the sensor sampling periods being allowed to differ from the system updating periods. The facilitation of communication between sensors and the remote PIO through wireless networks, which...
03 August 2026
Event-Triggered-Based Adaptive Practical Fixed-Time Tracking Control for Uncertain Nonlinear Systems With Unmeasurable States
In this paper, the problem of adaptive event-triggered (ET) fixed-time tracking control (FTTC) for a class of uncertain nonlinear systems (NSs) with partially unmeasurable states is investigated. An observer and a set of radial basis function neural networks (RBFNNs) are introduced to reconstruct the unmeasurable states and to approximate the...
03 August 2026
Visual-Based Flower Counting: Techniques and Applications
With the rapid integration of modern information technologies into agriculture, smart agriculture enables increasingly precise phenotyping and yield prediction. Flower counting is a key phenological indicator; however, achieving high precision remains a significant challenge due to severe occlusion, density variations, and environmental variability (e.g., lighting/weather). Moreover, existing studies remain fragmented...
03 August 2026
A Two-Step Iterative Local Search for the Harvester Scheduling Problem with Splittable Workloads
With the growing emphasis on intelligent agriculture, scheduling problems involving multiple harvesters in large-scale croplands have attracted increasing attention. In these scenarios, harvesters collaboratively perform tasks in expansive croplands, with each harvester taking on a portion of the workload. This study defines such problems as the harvester scheduling problem with...
03 July 2026
LL-Refiner: Learning Adaptive Refinement for Ultra-High-Definition Low-Light Image Enhancement
Low-light image enhancement aims to address various degradations in low-light conditions, such as low illumination, noise pollution, color distortion, and missing scene content. With advances in digital imaging technology, the resolution of captured images has seen substantial improvements. This poses new challenges in achieving good enhancement performance for multi-scale details...

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