Article
Automation & Control Systems
Yong-Sheng Ma, Wei-Wei Che, Chao Deng, Zheng-Guang Wu
Summary: This article studies the observer-based event-triggered containment control problem for linear multiagent systems under denial-of-service attacks, proposing an improved separation method-based observer design method and a novel observer-based event-triggered containment controller design method to make the systems resilient to DoS attacks.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Hao Chen, Yan-Jun Liu, Lei Liu, Shaocheng Tong, Zhiwei Gao
Summary: An adaptive sliding-mode control scheme is developed for uncertain quarter vehicle active suspension systems, incorporating integral terminal SMC, neural networks, and backstepping technique to ensure stability. The use of Barrier Lyapunov functions and a continuous differentiable asymmetric saturation model further improve system stability. Results show that the proposed control strategy is effective in simulation.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Guang Chen, Haitao Wang, Kai Chen, Zhijun Li, Zida Song, Yinlong Liu, Wenkai Chen, Alois Knoll
Summary: This article presents the first-ever survey of recent studies in deep learning-based small object detection. It provides an overview of the basic elements of small object detection, state-of-the-art datasets, performance of different methods, and the latest small object detection networks. The article also discusses promising directions and tasks for future work in small object detection.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Ye Tian, Yajie Zhang, Yansen Su, Xingyi Zhang, Kay Chen Tan, Yaochu Jin
Summary: The proposed two-stage evolutionary algorithm adjusts the balance between objective optimization and constraint satisfaction adaptively, addressing the difficulty of striking a good balance in complex feasible regions. Experimental studies demonstrate the superiority of the algorithm over state-of-the-art algorithms, especially on problems with complex feasible regions.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Cybernetics
Honghao Gao, Kaili Xu, Min Cao, Junsheng Xiao, Qiang Xu, Yuyu Yin
Summary: This article proposes a method for dish health assessment based on deep features and attention mechanism, aiming to improve taste recognition accuracy by applying a hand-deep local-global net (HDLGN) and introducing a local attention mechanism in dish image recognition.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2022)
Article
Automation & Control Systems
Jiajing Wu, Qi Yuan, Dan Lin, Wei You, Weili Chen, Chuan Chen, Zibin Zheng
Summary: This article proposes an approach to detect phishing scams on Ethereum by mining its transaction records. By constructing the transaction network and using a novel network embedding algorithm, the features of addresses are successfully extracted and classified using a support vector machine. Experimental results demonstrate the effectiveness of this method on Ethereum and the superiority of the feature extraction algorithm.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Quan-Ke Pan, Liang Gao, Ling Wang
Summary: This article addresses a novel scheduling problem in modern manufacturing systems and proposes a cooperative co-evolutionary algorithm to solve it. Experimental results show that the algorithm outperforms other metaheuristics in the literature.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Qiqi Zhu, Weihuan Deng, Zhuo Zheng, Yanfei Zhong, Qingfeng Guan, Weihua Lin, Liangpei Zhang, Deren Li
Summary: This article introduces a spectral-spatial-dependent global learning framework based on global convolutional long short-term memory and global joint attention mechanism to address insufficient and imbalanced HSI classification. Proposed hierarchically balanced sampling strategy and weighted softmax loss to tackle imbalanced sample problems, and achieved superior performance compared to other state-of-the-art methods in experiments on three public HSI datasets.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Zhiwen Chen, Jiamin Xu, Tao Peng, Chunhua Yang
Summary: A new fault diagnosis method combining structural analysis and graph convolutional network is proposed, utilizing a hybrid of available measurement and prior knowledge. Experimental results demonstrate that this method achieves better diagnosis results compared to existing methods based on common evaluation indicators.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Xinbo Yu, Bin Li, Wei He, Yanghe Feng, Long Cheng, Carlos Silvestre
Summary: An adaptive impedance controller for human-robot co-transportation is proposed in this research. It utilizes vision and force sensing to obtain human hand position in task space, ensuring safe interaction and smooth control behavior during the transportation task.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Hui Ma, Hongru Ren, Qi Zhou, Renquan Lu, Hongyi Li
Summary: This article investigates Nussbaum gain adaptive control for a type of nonlinear systems, tackling challenges such as periodic disturbances and unknown control direction by utilizing Fourier series expansion and radial basis function neural network for function approximation. The control algorithm is designed with a Nussbaum-type function to handle dead zone output and unknown control direction, ensuring bounded closed-loop signals and tracking error convergence. Simulation results validate the effectiveness and applicability of the proposed analysis approach.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Siyang Song, Shashank Jaiswal, Enrique Sanchez, Georgios Tzimiropoulos, Linlin Shen, Michel Valstar
Summary: This article addresses two important issues in automatic personality analysis systems: the use of short video segments or single frames for inferring personality traits, and the lack of methods for encoding person-specific facial dynamics. To tackle these issues, the paper proposes a novel Rank Loss for self-supervised learning of facial dynamics and a method to represent person-specific dynamics. The approach achieves promising results in personality estimation and shows the importance of the tasks performed by the subject in the video and the use of multi-scale dynamics.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Review
Computer Science, Cybernetics
Baoquan Cheng, Chaojie Fan, Hanliang Fu, Jianling Huang, Huihua Chen, Xiaowei Luo
Summary: This study aims to answer how to adopt EEG for measuring and computing construction workers' cognitive statuses through a critical review. The literature search and selection process included 21 eligible articles. The content analysis was then conducted from three aspects of investigated cognitive statuses, experiment design, and data analysis. This review provides guidance for researchers to use EEG for measuring and computing various cognitive statuses of construction workers, and it also offers valuable suggestions for future research and on-site construction management.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2022)
Article
Automation & Control Systems
Yue Yang, Yang Xiao, Tieshan Li
Summary: MASs are distributed systems with multiple intelligent agents, and formation control is a significant technique within MASs. Despite widespread use in various fields, there has been limited research on security issues related to formation control in MASs. This study aims to investigate potential security problems in formation control on a multirobot system, proposing different levels of control attacks and demonstrating how cyberattacks can disrupt physical movements of robots. Experimental results show that these attacks can easily interrupt formation movements and even cause irreversible losses in a multirobot system.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Xiaobing Du, Cuixia Ma, Guanhua Zhang, Jinyao Li, Yu-Kun Lai, Guozhen Zhao, Xiaoming Deng, Yong-Jin Liu, Hongan Wang
Summary: This article introduces a deep learning method for EEG-based emotion recognition, which can automatically extract spatial features between different EEG electrodes and achieve state-of-the-art performance in emotion recognition.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2022)
Article
Automation & Control Systems
Ke Chen, Bing Xue, Mengjie Zhang, Fengyu Zhou
Summary: This study proposes a novel PSO-based feature selection method to solve high-dimensional classification problems through information sharing between two related tasks, achieving higher classification accuracy in a faster time than existing methods.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Qian Ma, Shengyuan Xu
Summary: This technical correspondence investigates the consensus problem for second-order multiagent systems under network topologies with a directed spanning tree. It provides consensus analysis for systems with the distributed delayed proportional-integral (PI)-type controller, and identifies crossing directions of the characteristic roots using a sufficient condition. Simulation examples are used to demonstrate the theoretical analysis.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Jia Chen, Ming Zhong, Jianxin Li, Dianhui Wang, Tieyun Qian, Hang Tu
Summary: This article focuses on the "oversmoothing" problem in attributed network representation learning, proposing to evaluate a smoothing parameter based on network topological characteristics to adaptively smooth node attributes and structure information, resulting in robust and distinguishable node features.Extensive experiments show that this approach effectively preserves the intrinsic information of networks compared to state-of-the-art works on benchmark datasets with varying topological characteristics.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Hongjing Liang, Guangliang Liu, Tingwen Huang, Hak-Keung Lam, Bohui Wang
Summary: This article proposes a solution to the cooperative fault-tolerant control problem for networks of stochastic nonlinear systems with actuator faults and input saturation. Fuzzy neural networks are used to estimate unknown functions and stochastic disturbance terms, while a smooth nonlinear function is constructed to estimate the saturation function. A novel adaptive fault-tolerant control protocol is proposed using backstepping design technique, and the stochastic Lyapunov functional strategy is used to prove convergence and boundedness of the closed-loop systems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Junkang Ni, Peng Shi, Yu Zhao, Quan Pan, Shuoyu Wang
Summary: This article investigates the problem of fixed-time event-triggered output consensus tracking for high-order multiagent systems under directed interaction graphs. It proposes a fixed-time event-triggered distributed observer and triggering functions, and designs an event-triggered adaptive dynamic surface fixed-time controller. The contribution of this article is to present a novel event-triggered fixed-time distributed observer and a novel fixed-time controller, which can achieve practical fixed-time output consensus tracking of high-order MAS under directed interaction graphs.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
