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Neural Dynamics for Distributed Collaborative Control of Manipulators With Time Delays

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 854-863页

作者： Long Jin xin Zheng xin luo School of Information Science and Engineering Lanzhou UniversityLanzhou 730000 IEEE State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065 Chongqing Institute of Green and Intelligent Technology Chinese Academy of SciencesChongqing 400714China

Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their *** work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics *** assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired *** proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it ***,the proposed neural dynamics solver is proved to be stable,convergent and ***,the allowable threshold value of time delay that ensures the proposed scheme’s stability is *** examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.

关键词： Distributed collaborative control neural dynamics redundancy resolution repetitive motion planning(RMP) time delay

Polymerization-Induced Self-Assembly for the Preparation of Poly(N,N-dimethylacrylamide)-b-Poly(4-tert-butoxystyrene-co-pentafluorostyrene)Particles with Inverse Bicontinuous Phases

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Chinese Journal of Chemistry 2021年第7期39卷 1819-1824页

作者： xin luo Zesheng An Institute of Nanochemistry and Nanobiology College of Environmental and Chemical EngineeringShanghai UniversityShanghai200444 China State Key Laboratory of Supramolecular Structure and Materials College of ChemistryJilin UniversityChangchunJilin130012 China

Main observation and conclusion Polymerization-induced self-assembly(PISA)is an effective method to prepare block copolymer(BCP)particles with various ***,BCPs with inverse bicontinuous phase structure have been rarel... 详细信息

关键词： Block copolymers Inverse bicontinuous phase Mesophases Polymerization-induced self-assembly RAFT polymerization

Tensor Distribution Regression Based on the 3D Conventional Neural Networks

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1628-1630页

作者： Lin Chen xin luo Chongqing Institute of Green and Intelligent Technology Chinese Academy of SciencesChongqing 400714China College of Computer and Information Science Southwest UniversityChongqing 400715China

Dear Editor,This letter presents a novel tensor-distribution-regression model based on 3D conventional neural networks(3D-TDR) with an application to clinical score prediction in aging-related diagnosis. The estimation of clinical scores of subjects using brain magnetic resonance imaging(MRI) helps understand the pathological stage of dementia.

关键词： estimation prediction networks

Data Driven Vibration Control:A Review

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1898-1917页

作者： Weiyi Yang Shuai Li xin luo Chongqing Institute of Green and Intelligent Technology Chinese Academy of SciencesChongqing 400714 Chongqing School University of Chinese Academy of SciencesChongqing 400714China Faculty of Information Technology and Electrical Engineering University of OuluOulu 90570 VTT-Technology Research Center of Finland Oulu 90570Finlan College of Computer and Information Science Southwest UniversityChongqing 400715China

With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic *** shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC *** convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration *** on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of *** doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue.

关键词： Data driven vibration control(DDVC) data science designing method feedforward control industrial robot input shaping optimizing method residual vibration

An Overview of Calibration Technology of Industrial Robots

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 23-36页

作者： Zhibin Li Shuai Li xin luo the School of Computer Science and Technology Dongguan University of TechnologyDongguanGuangdong 523808 the School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China the Department of Electronics and Electrical Engineering Swansea UniversitySwansea SA18EN the Hengrui(Chongqing)Artificial Intelligence Research Center Department of Big Data Analyses TechniquesCloudwalkChongqing 401331China the Department of Electronics and Electrical Engineering Swansea UniversitySwansea SA18ENUK

With the continuous improvement of automation,industrial robots have become an indispensable part of automated production *** widely used in a number of industrial production activities,such as spraying,welding,handling,etc.,and have a great role in these ***,the robotic technology is developing towards high precision,high *** calibration technology has a great significance to improve the accuracy of ***,it has much work to be done in the identification of robot *** parameter identification work of existing serial and parallel robots is *** the one hand,it summarizes the methods for parameter calibration and discusses their advantages and *** the other hand,the application of parameter identification is *** overview has a great reference value for robot manufacturers to choose proper identification method,points further research areas for ***,this paper analyzes the existing problems in robot calibration,which may be worth researching in the future.

关键词： Absolute pose accuracy identification method industrial robots parameter identification robot calibration technology robot parameters

Cryptocurrency Transaction Network Embedding From Static and Dynamic Perspectives: An Overview

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1105-1121页

作者： Yue Zhou xin luo MengChu Zhou the School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065 the Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714 the Chongqing School University of Chinese Academy of SciencesChongqing 400714China the College of Computer and Information Science Southwest UniversityChongqing 400715China the School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA

Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests from both industrial and academic communities. With its rapid development, the cryptocurrency transaction network embedding(CTNE) has become a hot topic. It embeds transaction nodes into low-dimensional feature space while effectively maintaining a network structure,thereby discovering desired patterns demonstrating involved users' normal and abnormal behaviors. Based on a wide investigation into the state-of-the-art CTNE, this survey has made the following efforts: 1) categorizing recent progress of CTNE methods, 2) summarizing the publicly available cryptocurrency transaction network datasets, 3) evaluating several widely-adopted methods to show their performance in several typical evaluation protocols, and 4) discussing the future trends of CTNE. By doing so, it strives to provide a systematic and comprehensive overview of existing CTNE methods from static to dynamic perspectives,thereby promoting further research into this emerging and important field.

关键词： Big data analysis cryptocurrency transaction network embedding(CTNE) dynamic network network embedding network representation static network

A Distributed Adaptive Second-Order Latent Factor Analysis Model

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2343-2345页

作者： Jialiang Wang Weiling Li xin luo the School of Computer Science and Technology Dongguan University of Technology the College of Computer and Information Science Southwest University

Dear Editor,This letter presents a distributed adaptive second-order latent factor(DAS) model for addressing the issue of high-dimensional and incomplete data representation. Compared with first-order optimizers, a second-order optimizer has stronger ability in approaching a better solution when dealing with the non-convex optimization problems, thus obtaining better performance in extracting the latent factors(LFs) well representing the known information from high-dimensional and incomplete data.

关键词： representation incomplete approaching

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SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1717-1719页

作者： Jiufang Chen Ye Yuan xin luo the College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065 the Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China the College of Computer and Information Science Southwest UniversityChongqing 400715China IEEE

Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.

关键词： representation preserving undirected

Bio-inspired Leg Design for a Heavy-Duty Hexapod Robot

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Journal of Bionic Engineering 2022年第4期19卷 975-990页

作者： Haoyuan Yi Zhenyu Xu Xueting xin Liming Zhou xin luo State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Research Institute Inner Mongolia First Machinery Group Co.LtdBaotou 014030China

The leg structure is crucial to the legged robot's motion *** the size and load of the legged robot increasing,the difficulty of leg design increases *** by biomechanics,this paper proposes a leg design approach based on effective mechanical advantage(EMA)for developing the heavy-duty legged *** bio-inspired design approach can reduce the demand for joint actuation forces during walking by optimizing the ratio relationship between the joint driving force and ground contact force.A dimensionless EMA model of the leg for the heavy-duty legged robot is constructed in this *** dimensions and hinge point locations are optimized according to the EMA and energy-optimal *** on the optimal leg structure,an electrically driven tri-segmented leg prototype is *** leg's joint hinge points are located near the main support line,and the load-to-weight ratio is 15:*** leg can realize a swing frequency of 0.63 Hz at the stride length of 0.8 m,and the maximum stride length can reach 1.5 m.

关键词： Legged robot EMA Heavy-duty Bio-inspired