A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation

Vol. 10,  No. 8, 2023

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PERSPECTIVE
New Control Paradigm for Industry 5.0: From Big Models to Foundation Control and Management
Fei-Yue Wang
2023, 10(8): 1643-1646. doi: 10.1109/JAS.2023.123768
Abstract(1423) HTML (43) PDF(1117)
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REVIEWS
Attacks Against Cross-Chain Systems and Defense Approaches: A Contemporary Survey
Li Duan, Yangyang Sun, Wei Ni, Weiping Ding, Jiqiang Liu, Wei Wang
2023, 10(8): 1647-1667. doi: 10.1109/JAS.2023.123642
Abstract(945) HTML (230) PDF(236)
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The blockchain cross-chain is a significant technology for inter-chain interconnection and value transfer among different blockchain networks. Cross-chain overcomes the “information island” problem of the closed blockchain network and is increasingly applied to multiple critical areas such as financ...

Hyperspectral Image Super-Resolution Meets Deep Learning: A Survey and Perspective
Xinya Wang, Qian Hu, Yingsong Cheng, Jiayi Ma
2023, 10(8): 1668-1691. doi: 10.1109/JAS.2023.123681
Abstract(2180) HTML (69) PDF(540)
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Hyperspectral image super-resolution, which refers to reconstructing the high-resolution hyperspectral image from the input low-resolution observation, aims to improve the spatial resolution of the hyperspectral image, which is beneficial for subsequent applications. The development of deep learning...

PAPERS
Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence
Xingxia Wang, Jing Yang, Yutong Wang, Qinghai Miao, Fei-Yue Wang, Aijun Zhao, Jian-Ling Deng, Lingxi Li, Xiaoxiang Na, Ljubo Vlacic
2023, 10(8): 1692-1703. doi: 10.1109/JAS.2023.123753
Abstract(1552) HTML (221) PDF(648)
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Very recently, intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers, entrepreneurs, and policymakers from various sectors around the world. However, there is no consensus on why and what is Industry 5.0 yet. In this paper, we define Industry 5.0 fr...

Development of a Bias Compensating Q-Learning Controller for a Multi-Zone HVAC Facility
Syed Ali Asad Rizvi, Amanda J. Pertzborn, Zongli Lin
2023, 10(8): 1704-1715. doi: 10.1109/JAS.2023.123624
Abstract(379) HTML (60) PDF(56)
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We present the development of a bias compensating reinforcement learning (RL) algorithm that optimizes thermal comfort (by minimizing tracking error) and control utilization (by penalizing setpoint deviations) in a multi-zone heating, ventilation, and air-conditioning (HVAC) lab facility subject to ...

Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis
Weiliang Zuo, Jingmin Xin, Changnong Liu, Nanning Zheng, Akira Sano
2023, 10(8): 1716-1729. doi: 10.1109/JAS.2023.123549
Abstract(449) HTML (139) PDF(78)
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Despite some efforts and attempts have been made to improve the direction-of-arrival (DOA) estimation performance of the standard Capon beamformer (SCB) in array processing, rigorous statistical performance analyses of these modified Capon estimators are still lacking. This paper studies an improved...

Scheduling Dual-Arm Multi-Cluster Tools With Regulation of Post-Processing Time
Qinghua Zhu, Bin Li, Yan Hou, Hongpeng Li, Naiqi Wu
2023, 10(8): 1730-1742. doi: 10.1109/JAS.2023.123189
Abstract(310) HTML (39) PDF(36)
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As wafer circuit width shrinks down to less than ten nanometers in recent years, stringent quality control in the wafer manufacturing process is increasingly important. Thanks to the coupling of neighboring cluster tools and coordination of multiple robots in a multi-cluster tool, wafer production s...

Echo State Network With Probabilistic Regularization for Time Series Prediction
Xiufang Chen, Mei Liu, Shuai Li
2023, 10(8): 1743-1753. doi: 10.1109/JAS.2023.123489
Abstract(523) HTML (33) PDF(79)
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Recent decades have witnessed a trend that the echo state network (ESN) is widely utilized in field of time series prediction due to its powerful computational abilities. However, most of the existing research on ESN is conducted under the assumption that data is free of noise or polluted by the Gau...

Neural-Network-Based Adaptive Finite-Time Control for a Two-Degree-of-Freedom Helicopter System With an Event-Triggering Mechanism
Zhijia Zhao, Jian Zhang, Shouyan Chen, Wei He, Keum-Shik Hong
2023, 10(8): 1754-1765. doi: 10.1109/JAS.2023.123453
Abstract(547) HTML (135) PDF(172)
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Helicopter systems present numerous benefits over fixed-wing aircraft in several fields of application. Developing control schemes for improving the tracking accuracy of such systems is crucial. This paper proposes a neural-network (NN)-based adaptive finite-time control for a two-degree-of-freedom ...

LETTERS
Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators
Zhongbo Sun, Shijun Tang, Jiliang Zhang, Junzhi Yu
2023, 10(8): 1766-1768. doi: 10.1109/JAS.2023.123273
Abstract(291) HTML (35) PDF(53)
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A Coverage Optimization Algorithm for Underwater Acoustic Sensor Networks based on Dijkstra Method
Meiqin Tang, Jiawen Sheng, Shaoyan Sun
2023, 10(8): 1769-1771. doi: 10.1109/JAS.2023.123279
Abstract(268) HTML (49) PDF(50)
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An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration
Zhihao Hao, Guancheng Wang, Bob Zhang, Leyuan Fang, Haisheng Li
2023, 10(8): 1772-1774. doi: 10.1109/JAS.2023.123360
Abstract(255) HTML (51) PDF(35)
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Underwater Data-Driven Positioning Estimation Using Local Spatiotemporal Nonlinear Correlation
Chengming Luo, Luxue Wang, Xudong Yang, Gaifang Xin, Biao Wang
2023, 10(8): 1775-1777. doi: 10.1109/JAS.2023.123288
Abstract(233) HTML (45) PDF(51)
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Relay-Switching-Based Fixed-Time Tracking Controller for Nonholonomic State-Constrained Systems: Design and Experiment
Zhongcai Zhang, Jinshan Bian, Kang Wu
2023, 10(8): 1778-1780. doi: 10.1109/JAS.2022.106046
Abstract(334) HTML (74) PDF(96)
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