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Robust control Analysis With Model Transformation for Interval Type-2 Fuzzy systems

IEEE Transactions on Fuzzy systems 2025年

作者： Yang, Jie Gai, Shaoyan Da, Feipeng Xie, Wenbo Southeast University School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China Shanghai University and Shanghai Artificial Intelligence Laboratory School of Mechatronic Engineering and Automation Shanghai200444 China

To address the problem of robust stability analysis for interval type-2 fuzzy systems (IT2FSs), this paper proposes an innovative analysis approach based on model transformation. Firstly, a classical piecewise linear approximation method is utilized to process the upper boundary membership functions (UMFs) and lower boundary membership functions (LMFs) of the footprint of uncertainty (FOU) in IT2FSs, resulting in linear boundary membership functions (MFs) that are more convenient for analysis, along with the corresponding approximation error functions. Subsequently, a novel error model transformation method is introduced to handle these error terms. By constructing new fuzzy rules and MFs, the boundary error terms are converted into a new fuzzy model, thereby incorporating more information about the error functions into the stability analysis. Based on this model, a robust stability condition in the form of linear matrix inequalities (LMIs) are derived, achieving improved robustness. Finally, the effectiveness of the proposed method is validated through simulations on real-world systems, and its superiority is demonstrated by comparison with existing methods. © 2025 IEEE.

关键词： Membership functions

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Bearing Fault Diagnosis Under Variable Working Conditions Based on Domain Adaptation and Improved Depthwise Separable Convolution Network 26

Bearing Fault Diagnosis Under Variable Working Conditions Ba...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Kuang, Zehui Mao, Fan Zhao, Xingyu Wan, Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Domain adaptation methods and appropriate feature extractors are usually applied to solve the problem that the variable working conditions of bearings affect the effectiveness of the fault diagnostic framework. However, the existing feature extractors are too complex to be deployed in real industries. In this paper, we propose a lightweight framework called improved depthwise separable convolution network (IDSCN) for the diagnosis of bearing faults in variable operating conditions. IDSCN is built on wavelet convolution and depthwise separable residual convolution (DSRC), where the wavelet convolution is used to extract frequency features from the source and target domains, and DSRC guarantees the performance of feature extraction with reduced parameters and computation. To minimise the distribution difference between the source and target domains, the local maximum mean difference is incorporated into the proposed framework. The performance of the proposed framework is validated on the Paderborn University dataset, involving a total of 6 transfer tasks. The experiment shows that the proposed framework achieves satisfactory results and outperforms other frameworks in bearing fault diagnosis. © 2025 IEEE.

关键词： Bearing fault diagnosis Depthwise separable residual convolution Domain adaptation Wavelet convolution

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A coordinated charging/discharging strategy for EVs with flexible mobility in multi-temporary microgrids

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Sustainable Energy, Grids and Networks 2025年 42卷

作者： Wang, Zhixian Falabretti, Davide Wang, Ying Zhang, Kaifeng Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University NO.2 Sipailou Road Jiangsu Nanjing210096 China Department of Energy Politecnico di Milano Milan20156 Italy

The increasing occurrence of extreme weather events can lead to more major power blackouts, which attracts attention to the utilization of temporary microgrids (TMGs) in the restoration stage. However, single TMGs originating after a blackout usually have weak resilience, because of their limited available resources. Therefore, cooperation between microgrids needs urgently to be studied: to this end, this paper proposes a novel charging/discharging strategy for electric vehicles (EVs) to achieve optimal power coordination between TMGs, by taking advantage of EV's temporal-spatial flexible mobility. First, a new user response willingness model for EVs is established considering move distance and charging compensation, and this model is combined with the EV eligibility assessment based on traveling time to evaluate the EV mobile possibility across TMGs. Then, a suitable resilience factor is proposed to measure the resilience of TMGs considering both the current and future operation conditions. Finally, a novel coordinated EV charging/discharging strategy exploiting the EVs’ mobility is developed based on a mixed integer optimization model, to enhance system resilience and reduce total regulation costs. A case study based on the realistic topology of Milan's urban area is analyzed, comparing the results obtained with the strategy without EV spatial cooperation. As a result, the proposed strategy can enhance the resilience of TMGs by 20.93 % and reduce the total regulation cost which is paid to regulation resources for ensuring the power balance of each TMG by 8.43 %. © 2025 Elsevier Ltd

关键词： Travel time

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Frequency Regulation Reserve Optimization Considering Flexible Resource Complementary Aggregation

Frequency Regulation Reserve Optimization Considering Flexib...

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Smart Grid and Artificial Intelligence (SGAI), International Conference on

作者： Zirui Huang Wenbo Mao Yaping Li Kaifeng Zhang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China China Electric Power Research Institute CO. Ltd Nanjing China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

This paper proposes a fast-solving strategy that uses the complementarity of flexible resources to aggregate and participate in frequency regulation. Firstly, this paper proposes a frequency regulation performance index which can consider the adjustment rate, response delay time, adjustable capacity and adjustment cost of flexible resources. Then, based on the index, this paper uses the K-means algorithm to cluster the resources with similar performance. Then, this paper proposes an aggregation strategy considering the complementary of multiple flexible resources. Finally, this paper improves the unit combination optimization model, so that flexible resources can participate in the optimization in the form of aggregation, and the ratio of resources can be determined in advance, reducing the number of optimization parameters and improve the efficiency of solution. In this paper, the simulation is carried out on the IEEE-118 node. The results show that the proposed scheme can effectively improve the rate of optimization solution and effectively avoid the curse of dimensionality in the face of a large number of flexible resources.

关键词： Costs Optimization models Face recognition Smart grids Performance analysis Delays Time factors Indexes Optimization Frequency control

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Pipeline Anomaly Detection Based on KPCA and Cosine Distance Prototypical Network 26

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

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yi, Kang Liu, Xin Hu, Wenkai Li, Yupeng School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331521950

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. © 2025 IEEE.

关键词： Frequency domain analysis

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Multi-Level Features Fusion for Zero-Shot Object Pose Estimation 26

Multi-Level Features Fusion for Zero-Shot Object Pose Estima...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Huang, Nanxin Xu, Chi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Driven by advancements in industrial production and artificial intelligence, the need for pose estimation of new ob-jects in areas like robotic manipulation and virtual reality is increasing. We introduce a zero-shot object pose estimation approach that identifies the poses of objects excluded from the training dataset, removing the requirement for re-modeling. The method is built around a multi-level features fusion framework de-signed to enhance generalization. First, a trainable feature extraction module filters and selects multi-level features extracted by the backbone network. Unlike traditional convolutional ker-nels, we incorporate a dynamic convolution kernel to enhance the feature extraction capability. Second, in the feature fusion module, we adopt a dynamic weight generation strategy to perform weighted fusion of multi-level features. This method enhances template matching by effectively describing similarities between unseen objects (those absent from the training set) and templates, leveraging robust and adaptive feature representations to narrow the gap with seen objects. Experimental results demonstrate that our approach achieves state-of-the-art performance on two popu-lar benchmark datasets, LineMod and LineMod-Occlusion, proves that our method has better generalization than previous models. © 2025 IEEE.

关键词： Industrial robots

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Mechanical and Geometric Properties of Nanosprings Based on Carbon Nanotubes with Dislocation Dipoles

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ACS Applied Nano Materials 2025年第18期8卷 9192-9200页

作者： Lei, Xiao-Wen Koyane, Jumpei Lu, Tong Matsuzaki, Kenichiro Yan, Yi Shi, Jin-Xing Fujii, Toshiyuki School of Materials and Chemical Technology Institute of Science Tokyo 2-12-1 Ookayama Meguro-ku Tokyo152-8550 Japan Department of Engineering Mechanics MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China Department of Production Systems Engineering and Sciences Komatsu University Nu 1-3 Shicyomachi Ishikawa Komatsu923-8511 Japan

Carbon nanotubes (CNTs) are lightweight materials with excellent mechanical, electrical, and thermal conductivity, which make helical CNTs promising candidates for applications in mechanical components such as nanosprings. In this study, based on the continuous dislocation theory, we introduce dislocation dipoles into CNT with discrete crystal structures to design nanosprings, propose a method that integrates mechanics and geometry, and analyze the mechanical and geometric properties of nanosprings. In detail, this study investigated the feasibility of designing helical CNTs through spontaneous deformation induced by dislocation dipoles separated from Stone-Wales defects. Analytical models were constructed by systematically introducing dislocation dipoles into (4,4) CNTs of varying lengths. We combined mechanical and geometric methods, performed molecular dynamics simulations to obtain the stable structure of CNTs with dislocation dipoles, and employed differential geometry to investigate the Willmore energy of helically shaped CNTs. The results showed that when dislocation dipoles were introduced into straight CNTs, energy relaxation calculations demonstrated spontaneous deformation, leading to the formation of a spring-shaped CNT. The CNT length and dislocation type significantly affected the spring constant. Longer CNTs exhibited lower spring constants, and an increase in dislocation density led to a higher average potential energy. This study provides unique insights into the control of the CNT shape and mechanical and geometrical properties, contributing to the design of functional materials such as nanosprings. © 2025 The Authors. Published by American Chemical Society.

关键词： Geometry

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Intrinsic-feature-guided 3D Object Detection

arXiv

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arXiv 2025年

作者： Zhang, Wanjing Wang, Chenxing School of Automation Southeast University 2# Sipailou Xuanwu Nanjing210096 China Key laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

LiDAR-based 3D object detection is essential for autonomous driving systems. However, LiDAR point clouds may appear to have sparsity, uneven distribution, and incomplete structures, significantly limiting the detection performance. In road driving environments, target objects referring to vehicles, pedestrians and cyclists are well-suited for enhancing representation through the complete template guidance, considering their grid and topological structures. Therefore, this paper presents an intrinsic-feature-guided 3D object detection method based on a template-assisted feature enhancement module, which extracts intrinsic features from relatively generalized templates and provides rich structural information for foreground objects. Furthermore, a proposal-level contrastive learning mechanism is designed to enhance the feature differences between foreground and background objects. The proposed modules can act as plug-and-play components and improve the performance of multiple existing methods. Extensive experiments illustrate that the proposed method achieves the highly competitive detection results. Code will be available at https://***/zhangwanjingjj/***. Copyright © 2025, The Authors. All rights reserved.

关键词： Object recognition

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Improved Synthesis of Nondeterministic Publicly-Known Edit Functions for Opacity Enforcement

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IEEE Transactions on Automatic control 2025年

作者： Liu, Rongjian Hadjicostis, Christoforos N. Chongqing Normal University National Center for Applied Mathematics in Chongqing Chongqing401331 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China University of Cyprus Department of Electrical and Computer Engineering Nicosia Cyprus

In this paper, we investigate the synthesis problem of edit functions for opacity enforcement in systems modelled as partially-observed finite-state automata. For better plausible deniability for the edit functions, in cases where the intruder may learn/know their existence, a synthesis problem for nondeterministic edit functions under a publicly-known setting was introduced in the literature, but not yet fully solved. In light of this, we revisit the publicly-known edit mechanism by proposing a sound and complete approach for solving the synthesis problem of nondeterministic publicly-known edit functions. For practical applications, the edit function is assumed to have limited erasure and insertion ability. Our approach is based on a new labelled finite-state structure, and results in wider applicability than previously-proposed in the literature. © 1963-2012 IEEE.

关键词： Discrete event simulation

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In Memory of Wolter J. Fabrycky: A Pioneer of systems engineering and US-Sino Academic Exchange

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IEEE/CAA Journal of Automatica Sinica 2025年第5期12卷 839-840页

作者： Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China

The passing of Professor Wolter “Wolt” Fabrycky, an outstanding member and great leader, is a big loss to our international systems engineering professional community. “Wolt was a legend in the systems engineering community with his teaching, advising, and dissemination of knowledge through the books he authored.”, as stated by Professor Eileen Aken, a former student of Wolt and the head of the Virginia Tech's Grado Department of Industrial and systems Engineeirng where Wolt had served and led for 30 years and retired as John L. Lawrence Professor emeritus.

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