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

12 February 2024
This paper presents a novel sequential inverse optimal control (SIOC) method for discrete-time systems, which calculates the unknown weight vectors of the cost function in real time using the input and output of an optimally controlled discrete-time system. The proposed method overcomes the limitations of previous approaches by eliminating the...
12 February 2024
Low-light images suffer from low quality due to poor lighting conditions, noise pollution, and improper settings of cameras. To enhance low-light images, most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is difficult. In contrast, a self-supervised method breaks free from the reliance...
12 February 2024
This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems (SPSs) with unknown dynamics based on reinforcement learning (RL). Taking into account the slow and fast characteristics among system states, the interconnected SPS is decomposed into the slow time-scale dynamics and the fast...
12 February 2024
The copper disc casting machine is core equipment for producing copper anode plates in the copper metallurgy industry. The copper disc casting machine casting package motion curve (CPMC) is significant for precise casting and efficient production. However, the lack of exact casting modeling and real-time simulation information severely restricts dynamic...
12 February 2024
This work proposes an event-triggered adaptive control approach for a class of uncertain nonlinear systems under irregular constraints. Unlike the constraints considered in most existing papers, here the external irregular constraints are considered and a constraints switching mechanism (CSM) is introduced to circumvent the difficulties arising from irregular output constraints....
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12 February 2024
This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators. First, a fixed-time disturbance observer (FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems. Then an adaptive scheme is used...
29 January 2024
This paper provides a comprehensive review of the current status, advancements, and future prospects of humanoid robots, highlighting their significance in driving the evolution of next-generation industries. By analyzing various research endeavors and key technologies, encompassing ontology structure, control and decision-making, and perception and interaction, a holistic overview of the...
29 January 2024
The power grid is undergoing a transformation from synchronous generators (SGs) toward inverter-based resources (IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants (VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed...
04 January 2024
In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming (ADP) technique based on the internal model principle (IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically,...
10 November 2023
Reinforcement learning (RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming (ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the...

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