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A Dual-Optimization Fault Diagnosis Method For Rolling Bearing Based On Hierarchical Slope Entropy And SVM Synergized with Shark Optimization Algorithm

SSRN

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SSRN 2022年

作者： Li, Yuxing Tang, Bingzhao Huang, Bo Jiao, Shangbin Xue, Xiaohui School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

Slope entropy (SlopEn) has been widely applied in fault diagnosis and has performed excellent performance, while SlopEn suffers from the problem of thresholds selection. Aim to further enhance the identifying capability of SlopEn in fault diagnosis, on basis of the SlopEn, the concept of hierarchy is combined and proposed new complexity feature, namely hierarchical slope entropy (HSlopEn). Meanwhile, the white shark optimizer (WSO) is applied to optimize the both HSlopEn and support vector machine (SVM), and WSO-HSlopEn and WSO-SVM are proposed respectively. Then, a dual-optimization fault diagnosis method for rolling bearing based on WSO-HSlopEn and WSO-SVM is put forward. Firstly, different types of bearing signals are input and decomposed into several nodes by hierarchical decomposition. Then taking the recognition rate as the fitness function, the parameters of HSlopEn and SVM are determined adaptively by WSO. After that, the WSO-HSlopEn of the nodes are extracted and single-feature and multi-features extraction are performed. Finally, the diagnosis results are output by WSO-SVM. Experimental results demonstrated that whether under single-feature or multi-features, based on WSO-HSlopEn and WSO-SVM fault diagnosis method has the highest recognition rate compared to other hierarchical entropies;moreover, under multi-features, the recognition rates are all higher than 97.5%, and the more features we select, the better the recognition effect will be. when five nodes are selected, the highest recognition rate reaches 100%. © 2022, The Authors. All rights reserved.

关键词： Support vector machines

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controller Synthesis of Signal Temporal Logical Tasks for Cyber-Physical Production systems via Acyclic Decomposition

Controller Synthesis of Signal Temporal Logical Tasks for Cy...

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IEEE Conference on Decision and control

作者： Shuling Wang Shanying Zhu Cailian Chen Liang Xu Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Institute of Artificial Intelligence Shanghai University Shanghai China

Modularization facilitates the adaptability of cyber-physical production systems (CPPSs) with a variety of collaborative tasks. Various production rules can be captured by signal temporal logic (STL) specifications imposed on interconnected multi-agent systems (MASs). In this paper, we focus on the controller synthesis of STL tasks for interconnected MASs to accomplish collaborative tasks in modular CPPSs. Firstly, a class of STL specifications characterizing tasks by the combination of fixed-time reachability and finite-time persistence tasks is proposed, which encompasses a large class of production specifications for the MAS. Secondly, the acyclic decomposition of the global STL formula is constructed to enable conflict-free collaborative tasks and unidirectional couplings between subsystems. By establishing the equivalence between the proposition and the state set of the MAS, necessary and sufficient conditions are respectively proposed for the satisfaction of reachability and persistence tasks. In addition, an algorithm is presented to synthesize controllers for the MAS with the global STL specification based on local controllers of subsystems. An illustrative example is given to show the effectiveness of the proposed method.

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Real-Time Solution of Unsteady Inverse Heat Conduction Problem Based on Improved Whale Optimization Algorithm and Parameter-Adaptive Pid

SSRN

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SSRN 2022年

作者： Huang, Weichao Li, Jiahao Liu, Ding Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China

To the common unsteady inverse heat conduction problem in the industrial field, a real-time solution strategy of improving whale optimization algorithm (IWOA) and parameter-adaptive Proportional-integral-differential (PID) is proposed in the paper. This strategy improves the initial solution distribution, global search capability and population diversity generalization of traditional WOA, which effectively improves the parameters-adaptive capability of PID. In solving the unsteady inverse heat conduction problem, the IWOA-PID feedback control model is first established to adaptively obtain the optimal PID parameters at each time. Then, the deviation between the calculated temperature and the measured temperature of the measured point obtained by solving the direct heat conduction problem (DHCP) is used as the system input. Finally, the real-time heat flux at the boundary of the heat conduction system is solved iteratively. The experimental results shown that the inverse algorithm proposed in the paper can accurately retrieve the variation of the boundary heat flux in real-time, and has good resistance and self-adaptability. © 2022, The Authors. All rights reserved.

关键词： Heat flux

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Distributed Observer Design over Directed Switching Topologies

arXiv

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arXiv 2024年

作者： Xu, Haotian Liu, Shuai Wang, Bohui Wang, Jingcheng School of Control Science and Engineering Shandong University Jinan250061 China The School of Aerospace Science and Technology Xidian University Xi’an710071 China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

The distributed observer design problem holds significant importance in cases in which the output information of a system is decentralized across different subsystems. Each subsystem has a local observer and access to one part of the measurement outputs and information exchanged through communication networks. This paper focuses on the design of distributed observer with jointly connected directed switching networks. The problem presents challenges due to passive switching modes and the open-loop unboundedness that results from local observability. To overcome these challenges, we develop a network transformation mapping method whereby each local observer can classify itself into an independent subgraph based on independent judgment. Next, an observable decomposition and reorganization method is developed for the digraph case to ensure that each subgraph possesses independent dynamic properties. Asymptotic omniscience is then proven using a developed recursive proof method. This paper includes many previous results as special cases, because most are only suitable for undirected switching topologies or fast-switching cases. An adaptive coupling gain design is proposed to simplify the calculation and verification of conditions that guarantee asymptotic omniscience. Finally, simulation results with the power system show the validity of the developed theory. © 2024, CC BY.

关键词： Continuous time systems

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Toward Cable-Driven Continuum Robots: Micro-Motion Augmentation Using Eccentrically Arranged Fibres with Eccentric Lumens

Toward Cable-Driven Continuum Robots: Micro-Motion Augmentat...

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IEEE International Conference on Robotics and Biomimetics

作者： Zecai Lin Cheng Zhou Yun Zou Anzhu Gao Institute of Medical Robotics and Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai P. R. China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai P. R. China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Micro-motion augmentation of macro-motion continuum robot can largely enhance its micro-operation capability during surgery. However, most existing micro-motion continuum robots have non-compact mechanical structure or non-smooth micro tip motion, which leads to complicated control in micro lumens. This paper proposes a micro-motion augmentation method by rotating eccentrically arranged fibres with eccentric lumens for cable-driven continuum robots. Two thermal drawn polymer fibres with an eccentric lumen on each are inserted into its eccentric lumens of the continuum robot. The micro-motion mechanism relies on small changes in the neutral axis of the continuum robot due to the rotation of the eccentrically arranged fibres. A kinematic model considering variable neural axis is built to describe the micro motion, and a simulation is conducted to investigate the deformation characteristics. The resolution and micro motion with respect to different structural parameters are also analysed. Detailed experiments are performed to validate the effectiveness of the proposed method, and results indicate that the repeatability of micro-motion is 10.1 μm (4.0 %).

关键词： Deformation Thermal variables control Biomimetics Surgery Kinematics Lumen Structural engineering Continuum robots Polymers

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Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 239-253页

作者： Yang Xiu Dongfang Li Miaomiao Zhang Hongbin Deng Rob Law Yun Huang Edmond Q.Wu Xin Xu the School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Antai College of Economics&Management Shanghai Jiao Tong UniversityShanghai 200240China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China the Asia-Pacific Academy of Economics and Management University of MacaoMacao 999078China the Department of Decision Science Macao University of Science and TechnologyMacao 999078China the Department of Automation Shanghai Jiao Tong Universityand also with the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China the College of Mechatronics and Automation National University of Defense TechnologyChangsha 410073China IEEE

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake ***,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track *** proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle *** our method,the designed piecewise auxiliary function guarantees the finite-time stability of position ***,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s *** uniform ultimate boundedness of the closed-loop system is proved by analyzing ***,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential *** last,the availability and superiority of this work are shown through simulation and experiment results.

关键词： Line-of-sight(LOS) path following sideslip snake robot

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Symplectic Wigner Distribution in the Linear Canonical Transform Domain: Theory and Application

arXiv

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arXiv 2025年

作者： He, Yangfan Zhang, Zhichao School of Communication and Artificial Intelligence School of Integrated Circuits Nanjing Institute of Technology Nanjing211167 China School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science Application of Hainan Province Hainan Normal University Haikou571158 China Key Laboratory of Numerical Simulation of Sichuan Provincial Universities School of Mathematics and Information Sciences Neijiang Normal University Neijiang641000 China

This paper devotes to combine the chirp basis function transformation and symplectic coordinates transformation to yield a novel Wigner distribution (WD) associated with the linear canonical transform (LCT), named as the symplectic WD in the LCT domain (SWDL). It incorporates the merits of the symplectic WD (SWD) and the WD in the LCT domain (WDL), achieving stronger capability in the linear frequency-modulated (LFM) signal frequency rate feature extraction while maintaining the same level of computational complexity. Some essential properties of the SWDL are derived, including marginal distributions, energy conservations, unique reconstruction, Moyal formula, complex conjugate symmetry, time reversal symmetry, scaling property, time translation property, frequency modulation property, and time translation and frequency modulation property. Heisenberg’s uncertainty principles of the SWDL are formulated, giving rise to three kinds of lower bounds attainable respectively by Gaussian enveloped complex exponential signal, Gaussian signal and Gaussian enveloped chirp signal. The optimal symplectic matrices corresponding to the highest time-frequency resolution are generated by solving the lower bound optimization (minimization) problem. The time-frequency resolution of the SWDL is compared with those of the SWD and WDL to demonstrate its superiority in LFM signals time-frequency energy concentration. A synthesis example is also carried out to verify the feasibility and reliability of the theoretical analysis. Copyright © 2025, The Authors. All rights reserved.

关键词： Wigner-Ville distribution

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Advancing Orchard Fruit Detection: An Innovative Agricultural Foundation Model Approach

Advancing Orchard Fruit Detection: An Innovative Agricultura...

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2024 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2024

作者： Li, Jiajia Lammers, Kyle Yin, Xunyuan Yin, Xiang He, Long Lu, Renfu Li, Zhaojian Department of Electrical and Computer Engineering Michigan State University MI United States School of Chemical and Biomedical Engineering Nanyang Technological University Singapore Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Department of Agricultural and Biological Engineering Pennsylvania State University United States United States Department of Agriculture Agricultural Research Service East LansingMI United States Department of Mechanical Engineering Michigan State University East LansingMI United States

ISBN: (纸本)9798331302214

Fruit harvesting poses a significant labor and financial burden on the fruit industry, which underscore the urgent need for advancements in robotic harvesting solutions. Despite considerable progress in leveraging deep learning and machine learning techniques for fruit detection, a common shortfall is the inability to swiftly extend the developed models across different orchards and/or various fruit species. Additionally, the limited availability of pertinent data further compounds these challenges. In this work, we introduce MetaFruit, the largest publicly available multi-class fruit dataset, comprising 4,248 images and 248,015 manually labeled instances across diverse U.S. orchards. Furthermore, this study proposes an innovative open-set fruit detection system leveraging advanced Vision Foundation Models (VFMs) for fruit detection that can adeptly identify a wide array of fruit types under varying orchard conditions. This system not only demonstrates remarkable adaptability in learning from minimal data through few-shot learning but also shows the ability to interpret human instructions for subtle detection tasks. The performance of the developed foundation model is comprehensively evaluated across several metrics, outperforming existing state-of-the-art algorithms in our MetaFruit, thereby setting a new benchmark in the field of agricultural technology and robotic harvesting. The MetaFruit dataset (https://***/datasets/jiajiali/metafruit) and detection framework (https://***/JiajiaLi04/FMFruit) are open-sourced to foster future research in vision-based fruit harvesting, marking a significant stride toward addressing the urgent needs of the agricultural sector. © 2024 ASABE Annual International Meeting. All rights reserved.

关键词： Orchards

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OLMNE+FT: Multiplex network embedding based on overlapping links

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Physica A: Statistical Mechanics and its Applications 2022年 596卷 127116-127116页

作者： Liang, Bo Wang, Lin Wang, Xiaofan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai China

Network embedding or graph representation learning has recently attracted more researchers’ attention and achieved state-of-the-art performance in many areas and tasks. Nevertheless, most of these methods are targeted for monolayer networks and ignore the multiplexity property of nodes which refers to the multifaceted relationships between two elements. Multiplexity provides multiple types of auxiliary information to refine the characteristics of nodes and can be modeled as a multiplex network. In this study, we propose a multiplex network embedding algorithm to learn a unique embedding for each node in each layer or each relation type. A biased path-dependency random walk strategy is adopted to generate node sequences for integrating different types of relations between nodes, which pays more attention to overlapping links and makes neighbor nodes in the sampling sequence more similar to each other. Then the skip-gram model is used to learn an overall embedding over node sequences. To strengthen the expressive power of the embedding in a specific layer, a fine tuning strategy with low time cost is employed to make the embedding comprise information of nodes at this particular layer and preserve their distinctive properties, and the unique embedding is achieved ultimately. To verify the effectiveness of our algorithms, we validate the performance of our algorithm and other baseline methods in the link prediction task. The results demonstrate that the learned embedding can capture the interlayer relationships and preserve the specific characteristics of nodes, and our algorithms can stably obtain better or comparable performance compared with other methods. © 2022 Elsevier B.V.

关键词： Network embeddings

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The Strength of Structural Diversity in Online Social Networks

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Research 2021年第1期2021卷 1203-1212页

作者： Yafei Zhang Lin Wang Jonathan JHZhu Xiaofan Wang Alex‘Sandy’Pentland Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China Department of Media and Communication and School of Data Science City University of Hong KongHong Kong S.A.R.China Department of Automation Shanghai UniversityShanghai 200444China Media Lab Massachusetts Institute of TechnologyCambridgeMA 02139USA

Understanding the way individuals are interconnected in social networks is of prime significance to predict their collective *** a large-scale dataset from a knowledge-sharing website,this paper presents an exploratory investigation of the way to depict structural diversity in directed networks and how it can be utilized to predict one’s online social *** capture the structural diversity of an individual,we first consider the number of weakly and strongly connected components in one’s contact neighborhood and further take the coexposure network of social neighbors into *** show empirical evidence that the structural diversity of an individual is able to provide valuable insights to predict personal online social reputation,and the inclusion of a coexposure network provides an additional ingredient to achieve that *** synthetically controlling several possible confounding factors through matching experiments,structural diversity still plays a nonnegligible role in the prediction of personal online social *** work constitutes one of the first attempts to empirically study structural diversity in directed networks and has practical implications for a range of domains,such as social influence and collective intelligence studies.

关键词： collective networks founding

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