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Controllability of heterogeneous networked sampled-data systems

Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive Control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Full-Range Non-Resonant PWM Zero-Voltage-Switching Power Converters With Minimized Inductor Current Ripple

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年第2期13卷 2014-2026页

作者： Liu, Fei Ruan, Xinbo Yao, Kai Gu, Ling Yang, Fei Tse, Chi K. Nanjing University of Aeronautics and Astronautics Center for More-Electrical-Aircraft Power System College of Automation Engineering Nanjing211106 China Nanjing University of Science and Technology School of Automation Nanjing210094 China City University of Hong Kong Department of Electrical Engineering Hong Kong

Soft-switching techniques can greatly reduce the switching loss, thus improving the efficiency, power density, and reliability of power converters. Focusing on the non-resonant pulsewidth modulation (PWM) converters, this article proposes a novel approach to realize zero-voltage-switching (ZVS) with constant frequency in the full operation range while minimizing the current ripple. First, the basic quadrilateral current modulation unit (QCMU) is proposed, where an inductor is spanned across the midpoint of two half-bridge legs, so that the inductor current is shaped as quadrilateral with its minimum value constant. Based on that, a family of full-range non-resonant PWM ZVS converters, including dc-dc, dc-ac, and ac-dc converters, is generated. Then, the optimal operating mode and control scheme based on the combined PWM and phase-shift control for the proposed ZVS converters are presented. Experimental results of dc-dc converter, and simulation results of dc-ac inverter and ac-dc rectifier as an extension, are provided to verify the effectiveness of the proposed non-resonant PWM ZVS converters. © 2013 IEEE.

关键词： Resonant converters

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A trajectory-level robot skill learning method based on fuzzy systems

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Science China(Information Sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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Stochastic Trajectory Optimization for Robotic Skill Acquisition From a Suboptimal Demonstration

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IEEE Robotics and automation Letters 2025年第6期10卷 6127-6134页

作者： Ming, Chenlin Wang, Zitong Zhang, Boxuan Cao, Zhanxiang Duan, Xiaoming He, Jianping Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai China School of Computation Information and Technology Germany Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China Shanghai Jiao Tong University State Key Laboratory of Submarine Geoscience the Department of Automation Shanghai200240 China

Learning from Demonstration (LfD) has emerged as a crucial method for robots to acquire new skills. However, when given suboptimal task trajectory demonstrations with shape characteristics reflecting human preferences but subpar dynamic attributes such as slow motion, robots not only need to mimic the behaviors but also optimize the dynamic performance. In this work, we leverage optimization-based methods to search for a superior-performing trajectory whose shape is similar to that of the demonstrated trajectory. Specifically, we use Dynamic Time Warping (DTW) to quantify the difference between two trajectories and combine it with additional performance metrics, such as collision cost, to construct the cost function. Moreover, we develop a multi-policy version of the Stochastic Trajectory Optimization for Motion Planning (STOMP), called MSTOMP, which is more stable and robust to parameter changes. To deal with the jitter in the demonstrated trajectory, we further utilize the gain-controlling method in the frequency domain to denoise the demonstration and propose a computationally more efficient metric, called Mean Square Error in the Spectrum (MSES), that measures the trajectories' differences in the frequency domain. We also theoretically highlight the connections between the time domain and the frequency domain methods. Finally, we verify our method in both simulation experiments and real-world experiments, showcasing its improved optimization performance and stability compared to existing methods. © 2016 IEEE.

关键词： Frequency domain analysis

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Cataract Surgical Instruments Segmentation Free of Motion Blur Influence 24

Cataract Surgical Instruments Segmentation Free of Motion Bl...

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13th International Conference on Bioinformatics and Biomedical Science, ICBBS 2024

作者： Sun, Xuebin Wang, Jinxi Yang, Xiaofei School of Electrical Automation and Information Engineering Tianjin University Tianjin China Department of Aerospace Laser Technology and System Shanghai Institute of Optics and Fine Mechanics Shanghai China

ISBN: (纸本)9798400717956

Most of the existing cataract surgical instrument segmentation algorithms fail to consider the motion blur caused by the surgeon's hand movement or defocused camera. Most prior deblurring methods are oriented to visual tasks to merely recover the structure information from motion-blurred images. However, during surgical instrument segmentation, it is important to obtain the exact location of the surgical instruments at the current time to pave the way for subsequent downstream tasks, such as tracking and position estimation. In this work, we propose a spatiotemporal (ST) information-based network, consisting of the deblurring module and a subsequent segmentation module, for cataract surgical instrument segmentation free of motion blur influence to address the missing gap in the existing literature. The ST recurrent network with a series of ST-LSTM and gradient highway units removes the motion blur, which then enables for accurate semantic segmentation. The ST network model subsequently captures the temporal and spatial correlation for semantic segmentation. Experimental results quantitatively and qualitatively demonstrate that our method outperforms the state-of-the-art on our self-constructed dataset and the CaDIS benchmark dataset. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Semantic Segmentation

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Coprime Factorization-Based Encryption and Attack Detection for Nonlinear Cyber-Physical systems Using Deep Learning Approach

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IEEE Transactions on automation Science and engineering 2025年 22卷 14020-14029页

作者： Wu, Shimeng Luo, Hao Zhang, Jiusi Qiao, Xinyu Tian, Jilun Jiang, Yuchen Harbin Institute of Technology Department of Control and Simulation Center Harbin150001 China National Key Laboratory ofComplex System Control and Intelligent Agent Cooperation Harbin150001 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper presents a data-driven framework for integrating encryption transmission and attack detection in cyber-physical systems (CPS) with nonlinear physical plants. The main focus of this research is to use deep neural networks to realize the coprime factorization (CF) of nonlinear systems. The definition of the CF guides the network training and designing process, and the model’s topology is designed in the state-space form, which improves the interpretability of the data-driven CF. Based on the CF-aided neural networks, an encrypted transmission module is designed that projects information related to system dynamics into a perpendicular data space, which complements existing encryption methods from a control theory perspective. Subsequently, an anomaly detector are designed using the same CF pairs. This detector not only provides high-accuracy detection of attacks but also distinguishes between attacks and faults, thereby reducing the false positive rate and enhancing the reliability of the attack detection. The proposed method has been validated in a real CPS using a mecanum-wheeled vehicle as the physical plant, demonstrating its effectiveness and applicability. © 2004-2012 IEEE.

关键词： Factorization

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Bibliometric and Content Analysis of Large Language Models Research in Software engineering: The Potential and Limitation in Software engineering

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International Journal of Advanced Computer Science and Applications 2025年第4期16卷 344-356页

作者： Damayanti, Annisa Dwi Gani, Hamdan Zhipeng, Feng Gani, Helmy Zuhriyah, Sitti Nurani Djabir, St. Nurhayati Wardani, Nur Ilmiyanti Department of Environmental Engineering Faculty of Engineering Hasanuddin University Makassar Indonesia Department of Machinery Automation System ATI Makassar Polytechnic Makassar Indonesia School of Culture Creativity and Media Hangzhou Normal University Zhejiang Hangzhou China Department of Industrial Hygiene Faculty of Public Health Occupational Health and Safety Makassar College of Health Sciences Indonesia Department of Computer System Universitas Handayani Makassar Makassar Indonesia Department of Information Systems and Technology Institut Teknologi dan Bisnis Nobel Indonesia Jl. Sultan Alauddin No.212 Makassar90221 Indonesia Department of Informatics Engineering Universitas Handayani Makassar Makassar Indonesia

Large Language Models (LLM) is a type of artificial neural network that excels at language-related tasks. The advantages and disadvantages of using LLM in software engineering are still being debated, but it is a tool that can be utilized in software engineering. This study aimed to analyze LLM studies in software engineering using bibliometric and content analysis. The study data were retrieved from Web of Science and Scopus. The data were analyzed using two popular bibliometric approaches: bibliometric and content analysis. VOS Viewer and Bibliometrix software were used to conduct the bibliometric analysis. The bibliometric analysis was performed using science mapping and performance analysis approaches. Various bibliometric data, including the most frequently referenced publications, journals, and nations, were evaluated and presented. Then, the synthetic knowledge method was utilized for content analysis. This study examined 235 papers, with 836 authors contributing. The publications were published in 123 different journals. The average number of citations per publication is 1.44. Most publications were published in Proceedings International Conference on Software engineering and ACM International Conference Proceeding Series, with China and the United States emerging as the leading countries. It was discovered that international collaboration on the issue was inadequate. The most often used keywords in the publications were "software design," "code (symbols)," and "code generation." Following the content analysis, three themes emerged: 1) Integration of LLM into software engineering education, 2) application of LLM in software engineering, and 3) potential and limitation of LLM in software engineering. The results of this study are expected to provide researchers and academics with insights into the current state of LLM in software engineering research, allowing them to develop future conclusions. © (2025), (Science and Information Organization). All Rights Res

关键词： Software design

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Enhancing IC substrate manufacturing through differential geometry and lightweight networks for etching defect detection

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Journal of Manufacturing systems 2025年 80卷 902-915页

作者： Yu, Yongxing Huang, Dan Hu, Yueming School of Automation Science and Engineering South China University of Technology Guangzhou510641 China Engineering Research Center of Precision Electronic Manufacturing Equipment Ministry of Education and Guangdong Provincial Engineering Laboratory for Advanced Chip Intelligent Packaging Equipment South China University of Technology Guangzhou510641 China Department of Automation North China Electric Power University Baoding071003 China Baoding key Laboratory of State Detection and Optimization Regulation for Integrated Energy System North China Electric Power University Baoding071003 China

With the advancement of high-density interconnect technology in semiconductor manufacturing, the precision and complexity of integrated circuit (IC) substrates have significantly increased, placing higher demands on quality control. Efficient and accurate detection of complex etching defects, which often occur during manufacturing, has become critical to preventing potential product defects. A defect detection method is proposed that combines a lightweight network with differential geometry tools to address the issue of etching defects in IC substrates. First, an improved deformable model is used to rapidly extract regular circuit trace contours from complex metallographic images, and morphological processing is applied to enhance the details, achieving precise image segmentation. For under-etching defects between circuit traces, differential processing of the original and segmented images is performed to locate abnormal regions. Subsequently, an optimized lightweight network based on MobileNet, termed OMNet, is designed to achieve the rapid identification of under-etching defects in these regions. For etching defects occurring on circuit traces, the DGEtch method employs a high-precision discrete curvature calculation based on the Frenet frame to evaluate angular discontinuities in contours, enabling accurate detection of etching defects. Experimental results demonstrate that the proposed method achieves an average recall rate of over 95% and maintains a precision above 90%. It exhibits high accuracy and stability in detecting etching defects and consistently outperforms existing models, particularly in handling complex mixed defects. This study provides an effective solution for detecting complicated defects in high-density IC substrate manufacturing. © 2025 The Society of Manufacturing Engineers

关键词： Inspection

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