Article
Automation & Control Systems
Xu Liu, Lingling Li, Fang Liu, Biao Hou, Shuyuan Yang, Licheng Jiao
Summary: The proposed deep group spatial-spectral attention fusion network is a novel classification method for PAN and MS images, which effectively combines spatial and spectral information to achieve comparable results in image interpretation through feature extraction, attention fusion, and classifier integration at pixel level.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Wu Deng, Junjie Xu, Xiao-Zhi Gao, Huimin Zhao
Summary: In this paper, an enhanced MSIQDE algorithm based on mixing multiple strategies, called EMMSIQDE, is proposed to overcome the limitations of QDE in optimization problems. EMMSIQDE achieves better optimization performance by using new mutation strategies and evolution mechanisms, as well as a feasible solution space transformation strategy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Review
Automation & Control Systems
Tianci Zhang, Jinglong Chen, Fudong Li, Kaiyu Zhang, Haixin Lv, Shuilong He, Enyong Xu
Summary: Research on intelligent fault diagnosis using artificial intelligence technologies has achieved significant progress, particularly in the field of S&I-IFD. Existing strategies include data augmentation, feature learning, and classifier design. Future research directions involve meta-learning and zero-shot learning.
Review
Automation & Control Systems
M. A. Ganaie, Minghui Hu, A. K. Malik, M. Tanveer, P. N. Suganthan
Summary: This paper provides a comprehensive review of state-of-art deep ensemble models, their applications in different domains, and potential research directions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Automation & Control Systems
Zhaohui Zheng, Ping Wang, Dongwei Ren, Wei Liu, Rongguang Ye, Qinghua Hu, Wangmeng Zuo
Summary: The proposed CIoU loss and Cluster-NMS approach, which incorporates geometric factors, significantly improve average precision and average recall in object detection and instance segmentation, with notable gains without sacrificing inference efficiency.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Jiayi Ma, Linfeng Tang, Fan Fan, Jun Huang, Xiaoguang Mei, Yong Ma
Summary: This study proposes a novel image fusion framework called SwinFusion, which combines cross-domain long-range learning and Swin Transformer. The framework integrates complementary information and achieves global interaction through attention-guided cross-domain modules. It also addresses multi-scene image fusion problems by preserving structure, detail, and intensity. Extensive experiments prove the superiority of SwinFusion compared to other state-of-the-art fusion algorithms. The implementation code and pre-trained weights are available at https://github.com/Linfeng-Tang/SwinFusion.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Automation & Control Systems
Lianbo Ma, Min Huang, Shengxiang Yang, Rui Wang, Xingwei Wang
Summary: This article proposes an adaptive localized decision variable analysis approach under the decomposition-based framework to solve large-scale multiobjective and many-objective optimization problems. The algorithm incorporates the guidance of reference vectors into control variable analysis and optimizes decision variables using an adaptive strategy. Experimental results validate the effectiveness and efficiency of the proposed algorithm on the large-scale multiobjective and MaOPs.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Guohuai Lin, Hongyi Li, Hui Ma, Deyin Yao, Renquan Lu
Summary: This paper investigates the human-in-the-Ioop leader-following consensus control problem in multi-agent systems with unknown matched nonlinear functions and actuator faults. A neural fault-tolerant controller with dynamic coupling gains is proposed by using neural networks and fault estimators. It is proved that the state of each follower can synchronize with the leader's state and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Simulation results are presented to demonstrate the effectiveness of the proposed control method.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Automation & Control Systems
Fuyuan Xiao
Summary: This article discusses the importance of uncertainty in decision-making processes, as well as the connections between quantum mechanics and the uncertainty reasoning tool CET. It introduces a new CEQD model to predict the impact of interference effects on human decision-making behaviors, along with the design of corresponding belief transformation functions to explain these effects, with experimental results confirming the effectiveness of the method proposed.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Weizheng Wang, Hao Xu, Mamoun Alazab, Thippa Reddy Gadekallu, Zhaoyang Han, Chunhua Su
Summary: The Industrial Internet of Things (IIoT) has significantly transformed personal lifestyles and society operations, sparking interest in areas such as intelligent logistics, smart grids, and smart cities. To address security concerns in IIoT, researchers have proposed a novel certificateless signature scheme using blockchain technology and smart contracts, demonstrating its advantages in security and efficiency.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Xiaoming Wang, Changhe Li, Yanbin Zhang, Zafar Said, Sujan Debnath, Shubham Sharma, Min Yang, Teng Gao
Summary: Nanofluid minimum quantity lubrication is a new process for clean manufacturing, but effective lubrication during turning requires changing the microstructure of the tool rake face to provide a channel for lubricant diffusion. The arrangement of textures has a significant impact on cutting performance, with textures perpendicular to the main cutting edge direction achieving lowest cutting force and optimal workpiece surface.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Automation & Control Systems
Chao Deng, Changyun Wen, Jiangshuai Huang, Xian-Ming Zhang, Ying Zou
Summary: This article addresses the distributed tracking problem for uncertain nonlinear multiagent systems under event-triggered communication. A new methodology is proposed to achieve stability and asymptotic tracking through grouping and designing event-triggered observers. A simulation example demonstrates the effectiveness of the proposed method.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Review
Automation & Control Systems
Haogang Li, Yanbin Zhang, Changhe Li, Zongming Zhou, Xiaolin Nie, Yun Chen, Huajun Cao, Bo Liu, Naiqing Zhang, Zafar Said, Sujan Debnath, Muhammad Jamil, Hafiz Muhammad Ali, Shubham Sharma
Summary: This article reviews the mechanisms and properties of extreme pressure (EP) and antiwear (AW) additives in boundary lubrication and discusses the advantages and disadvantages of traditional and nanoparticle additives. It also studies the influence of non-polar chain length on traditional additives and the effects of nanoparticle structure parameters, concentration, and media polarity on properties.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Automation & Control Systems
Absalom E. Ezugwu, Abiodun M. Ikotun, Olaide O. Oyelade, Laith Abualigah, Jeffery O. Agushaka, Christopher I. Eke, Andronicus A. Akinyelu
Summary: Clustering is an essential tool in data mining, and there is a need for improved, flexible, and efficient clustering techniques. This study presents a comprehensive review of traditional and state-of-the-art clustering techniques, demonstrating the importance of clustering in various disciplines and fields such as big data, artificial intelligence, and robotics.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Automation & Control Systems
Nianyin Zeng, Zidong Wang, Weibo Liu, Hong Zhang, Kate Hone, Xiaohui Liu
Summary: In this article, a dynamic-neighborhood-based switching PSO (DNSPSO) algorithm is proposed with improved velocity update mechanism and learning strategy. The differential evolution algorithm is successfully hybridized with the particle swarm optimization algorithm to enhance the solution accuracy for multimodal optimization problems.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Yang Liu, Deyin Yao, Hongyi Li, Renquan Lu
Summary: This article introduces a definition of compound tracking control and a finite-time performance function, and utilizes methods such as adaptive neural networks to design a distributed cooperative regulation protocol. Simulation experiments confirm the effectiveness of the theoretical findings.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Huanqing Wang, Wen Bai, Xudong Zhao, Peter Xiaoping Liu
Summary: This article discusses finite-time-prescribed performance-based adaptive fuzzy control for a class of strict-feedback systems in the presence of actuator faults and dynamic disturbances. An adaptive fuzzy fault-tolerant control strategy is introduced to deal with the difficulties associated with actuator faults and external disturbances. A modified performance function called the finite-time performance function (FTPF) is presented, which ensures that all signals of the closed-loop system are bounded and the tracking error converges to a predetermined region in finite time. The effectiveness of the controller is verified through simulation results.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Chunyong Yin, Sun Zhang, Jin Wang, Neal N. Xiong
Summary: This article proposes an integrated model for anomaly detection, using convolutional neural network (CNN) and recurrent autoencoder as the basis, and extracting features through two-stage sliding window data preprocessing. Empirical results show that the proposed model performs better on multiple classification metrics and achieves excellent results in anomaly detection.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Peng Cheng, Shuping He, Vladimir Stojanovic, Xiaoli Luan, Fei Liu
Summary: This article addresses the design issue of fuzzy asynchronous fault detection filter for a class of nonlinear Markov jump systems by using an event-triggered scheme. The asynchronous phenomenon between system and filter is characterized via a hidden Markov model with partly accessible mode detection probabilities, and sufficient conditions for the presence of FAFDF are obtained applying Lyapunov function methods.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Guozeng Cui, Jinpeng Yu, Qing-Guo Wang
Summary: This article investigates the problem of finite-time adaptive fuzzy tracking control for multi-input and multi-output (MIMO) nonlinear systems with input saturation. A new finite-time command filter and modified error compensation mechanism are introduced to address complexity explosion and filter error effects. The proposed finite-time adaptive control scheme guarantees finite-time bounded signals and regulation of output tracking errors to a small neighborhood of the origin. Numerical comparison example verifies the effectiveness of the proposed control scheme.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
