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Improved Stability Criteria on Discrete-time systems with Time-varying and Distributed Delays

International Journal of Automation and computing 2013年第3期10卷 260-266页

作者： Ting Wang Ming-Xiang Xue Chun Zhang Shu-Min Fei Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University

This work was supported by National Natural Science Foun- dation of China （Nos. 60905009, 61004032, 61104119, 61174076, and 61172135）, and Jiangsu Province Natural Science Foundation （Nos. SBK201240801 and BK20123... 详细信息

关键词： Discrete-time system global stability interval time-varying delay distributed delay reciprocal convex technique.

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Semi-supervised feature contrast incremental learning framework for bearing fault diagnosis with limited labeled samples

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Applied Soft Computing 2025年 176卷

作者： Tao, Xuyang Shen, Changqing Li, Lin Wang, Dong Shi, Juanjuan Zhu, Zhongkui School of Rail Transportation Soochow University Suzhou215131 China Space Optoelectronic Measurement and Perception Lab. Beijing Institute of Control Engineering Beijing100190 China The State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiao Tong University Shanghai200240 China

In real-world scenarios, rotating machinery consistently introduces new fault classes, but intelligent fault diagnosis methods mostly rely on the closed-world assumption, expecting only known fault classes during testing. Moreover, obtaining a sufficient number of labeled samples is often challenging. These challenges constrain the application and reliability of intelligent diagnosis models in real-world scenarios. Semi-supervised incremental learning enables continuous learning of new fault classes in an open environment, relying on a small number of labeled samples and a certain number of unlabeled samples. To address the semi-supervised incremental learning problem of fault classes, semi-supervised feature contrast (SSFC) is proposed, a new approach for bearing fault diagnosis with limited labeled samples. Specifically, a feature contrastive loss incorporating enhancement strategies is designed, independent of labeled sample information. This approach enables the model to retain knowledge of old classes while learning about new ones. A label reconstruction mechanism based on class centroids is utilized, effectively leveraging the structural information inherent in the samples to support supervised training. A dynamic class prototype cosine classifier initialized by class centroids is devised to mitigate interference between knowledge of fault classes. Finally, two incremental fault diagnosis case studies are designed to evaluate the effectiveness of the proposed method. The fault diagnosis results indicate that SSFC can continuously learn knowledge of new fault classes with limited labeled samples and effectively alleviate catastrophic forgetting. © 2025 Elsevier B.V.

关键词： Self-supervised learning

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Federated Services: A Smart Service Ecology with Federated Security for Aligned Data Supply and Scenario-Oriented Demands

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IEEE/CAA Journal of Automatica Sinica 2025年第5期12卷 925-936页

作者： Jia, Xiaofeng Li, Juanjuan Wang, Shouwen Qi, Hongwei Wang, Fei-Yue Qin, Rui Zhang, Min Liang, Xiaolong Beijing Big Data Centre Beijing100101 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Technology Company Ltd. Beijing100190 China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Macao999078 China

This paper introduces federated services as a smart service ecology with federated security to align distributed data supply with diversified service demands spanning digital and societal contexts. It presents the comprehensive researches on the theoretical foundation and technical system of federated services, aiming at advancing our understanding and implementation of this novel service paradigm. First, a thorough examination of the characteristics of federated security within federated services is conducted. Then, a five-layer technical framework is formulated under a decentralized intelligent architecture, ensuring secure, agile, and adaptable service provision. On this basis, the operational mechanisms underlying data federation and service confederation is analyzed, with emphasis on the smart supply-demand matching model. Furthermore, a scenario-oriented taxonomy of federated services accompanied by illustrative examples is proposed. Our work offers actionable insights and roadmap for realizing and advancing federated services, contributing to the refinement and wider adoption of this transformative service paradigm in the digital era. © 2014 Chinese Association of Automation.

关键词： Decentralized autonomous organizations and operations decentralized physical infrastructure networks federated security federated services multimodal large language models smart contracts

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Negative-pressure soft pneumatic actuators enabled by asymmetrically distributed bending units

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Extreme Mechanics Letters 2025年 77卷

作者： Fu, Zeyu Chen, Tianyu Zou, Haoran Zhu, Zhiwei Deng, Zichen Wang, Yifan School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an710072 China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore 639798 Singapore State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China

Soft pneumatic actuators are highly flexible and can adapt to complex environments, attracting significant attention for their ability to operate in settings where rigid actuators cannot. Most existing soft pneumatic actuators are powered by positive pressure, which has the disadvantage of volume increase during operation and risk of exploding under large pressures. In this study, we designed a new type of soft actuator by inducing asymmetric bending deformation throughout a holey structure under negative pressure. Using finite element analysis and a theoretical model, we studied the effects of various geometric parameters on the structure's bending behavior. We found that the displacement of the circle's center from the central axis is a parameter with the most significant impact on the bending behavior of the structure. By designing circular holes with offset from the central axis, the structure can bend toward the offset direction during subsequent bending deformation. Based on this deformation mechanism, we designed a soft gripper that bends upon actuation and effectively picks up objects. We further designed a bi-directional gripper that bends towards both sides and a circular gripper that contracts towards the center upon evacuation to hold objects. These soft grippers’ grasping capabilities are validated by experimental tests. Finally, by arranging the holes in a wavy pattern within the structure, we created a crawling robot that moves forward through cyclic negative pressure actuation. These findings highlight the potential of leveraging bending behaviors in asymmetrically distributed holey structures for the development of negative-pressure driven soft actuators and robots. © 2025 Elsevier Ltd

关键词： Pneumatic actuators

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Multi-Agent Coverage control in Non-Convex Annulus Region with Conformal Mapping

arXiv

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arXiv 2025年

作者： Feng, Xun Zhai, Chao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and Engineering Research Center of Intelligent Technology for Geo-exploration Ministry of Education Wuhan430074 China

Efficiently fulfilling coverage tasks in non-convex regions has long been a significant challenge for multi-agent systems (MASs). By leveraging conformal mapping, this paper introduces a novel sectorial coverage formulation to transform a non-convex annulus region into a topologically equivalent one. This approach enables the deployment of MASs in a non-star-shaped region while optimizing coverage performance and achieving load balance among sub-regions. It provides a unique perspective on the partitioned sub-regions to highlight the geodesic convex property of the non-star-shaped region. By utilizing the sectorial partition mechanism and the diffeomorphism property of conformal mapping, a decentralized control law is designed to drive MASs towards a desired configuration, which not only optimizes the global coverage cost but also ensures exponential convergence of equitable workload. Moreover, an iterative search algorithm is developed to identify the optimal approximation of multi-agent deployment in the non-star-shaped region. Theoretical analysis is conducted to confirm the asymptotic stability and global convergence with arbitrary small tolerance of the closed-loop system. Finally, numerical simulations demonstrate the practicality of the proposed coverage formulation with conformal mapping. Copyright © 2025, The Authors. All rights reserved.

关键词： Conformal mapping

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Application of Particle Swarm Optimization Algorithm Based on Adaptive Inertia Adjustment Strategy in Scheduling of the Coking Process

Application of Particle Swarm Optimization Algorithm Based o...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Yiheng Chen Fan Yin Xiaochong Chen Yi Ren Jie Hu Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

The sccheduling for pushing plan during the coking process critically affects the efficiency and stability of production. However, the complexity with mutiple-stage during production makes it difficult to design an efficient coke pushing plan. To address this issue, this paper proposes a scheduling method based on the particle swarm optimization algorithm. Firstly, the fuzzy c-means clustering is utilized to categorize actual operating conditions as either normal or abnormal, thereby facilitating the scheduling of pushing plan under disparate conditions. Subsequently, the scheduling problem for the pushing plan is transformed into a traveling salesman problem, and scheduling models under various conditions are established. Finally, to accelerate the convergence and enhance the algorithm's global search capability, an adaptive inertia adjustment strategy is employed to dynamically regulate the velocity and position of particles. The proposed method has been implemented in the coking process. Through the analysis of application results, the completion coefficient of pushing plan has been increased by 4.25%, demonstrating that the proposed has advantages in scheduling the pushing plan during the actual coking process.

关键词： Job shop scheduling Heuristic algorithms Clustering algorithms Production Traveling salesman problems Stability analysis Robustness complexity theory Particle swarm optimization Convergence

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Pipeline Anomaly Detection Based on KPCA and Cosine Distance Prototypical Network

Pipeline Anomaly Detection Based on KPCA and Cosine Distance...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Kang Yi Xin Liu Wenkai Hu Yupeng Li School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Accurately and promptly detecting the pipeline anomaly is crucial to the safe operation of pipeline systems, while a difficulty lies in that many existing methods require massive data for training models. However, pipelines are running under normal state for the most of the time, and labeled pipeline anomaly data is usually scarce. Among the commonly used sensors, vibration sensors are widely utilized in pipeline detection because of their advantages such as easy installation and high sensitivity. However, the vibration signal shows non-stationary characteristics when anomalies occur, and are contaminated by noises, making it difficult to represent the actual state with features extracted from either the time or frequency domain. Accordingly, this paper proposes a pipeline anomaly detection method based on the KPCA (kernel principal component analysis) and cosine distance prototypical network. First, features are extracted from original signals; then, the feature dimension is reduced by KPCA; last, the cosine distance is introduced to the prototypical network for anomaly detection. The effectiveness of the proposed method is demonstrated by case studies involving experimental data.

关键词： Vibrations Training Time-frequency analysis Sensitivity Pipelines Sensor phenomena and characterization Feature extraction Time-domain analysis Anomaly detection Principal component analysis

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Adaptive control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 807-815页

作者： Yuncheng Ouyang Lu Dong Lei Xue Changyin Sun IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

In this paper, a study of control for an uncertain2-degree of freedom(DOF) helicopter system is given. The2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function(IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.

关键词： 2-degree of freedom (DOF) helicopter adaptive control input deadzone integral barrier Lyapunov function neural networks output constraints

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Geometry-aware 3D pose transfer using transformer autoencoder

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Computational Visual Media 2024年第6期10卷 1063-1078页

作者： Shanghuan Liu Shaoyan Gai Feipeng Da Fazal Waris Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing210096China

3D pose transfer over unorganized point clouds is a challenging generation task,which transfers a source’s pose to a target shape and keeps the target’s *** deep models have learned deformations and used the target’s identity as a style to modulate the combined features of two shapes or the aligned vertices of the source ***,all operations in these models are point-wise and independent and ignore the geometric information on the surface and structure of the input *** disadvantage severely limits the generation and generalization *** this study,we propose a geometry-aware method based on a novel transformer autoencoder to solve this *** efficient self-attention mechanism,that is,cross-covariance attention,was utilized across our framework to perceive the correlations between points at different ***,the transformer encoder extracts the target shape’s local geometry details for identity attributes and the source shape’s global geometry structure for pose *** transformer decoder efficiently learns deformations and recovers identity properties by fusing and decoding the extracted features in a geometry attentional manner,which does not require corresponding information or modulation *** experiments demonstrated that the geometry-aware method achieved state-of-the-art performance in a 3D pose transfer *** implementation code and data are available at https://***/SEULSH/Geometry-Aware-3D-Pose-Transfer-Using-Transfor mer-Autoencoder.

关键词： 3D pose transfer geometry-aware transfor-mer autoencoder cross-covariance attention

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Data-Driven Learning and control with Event-Triggered measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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