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54th Annual Conference of the Society of Instrument and control Engineers of Japan, SICE 2015

作者： Yongkun, Wang Zhongxin, Liu Mingwei, Sun Zengqiang, Chen Department of Automation Nankai University Tianjin300071 China Tianjin Key Laboratory of Intelligent Robotics College of Computer and Control Engineering Nankai University Tianjin300071 China

ISBN: (纸本)9784907764487

Conventional proportional navigation or augmented proportional navigation guidance laws are widely used for intercepting maneuverable targets;however, they are effective only in intercepting a target with a constant velocity or a known acceleration. In this paper, a continuous second-order sliding mode guidance law is designed to intercept a highly maneuverable target in connection with the super-twisting algorithm. Meanwhile, the target maneuver information, regarded as unpredictable disturbance, is coped with by an extended state observer (ESO) and then is compensated in the guidance law. In the proposed guidance scheme, no information about target motion is needed. The closed-loop error can be guaranteed to be bounded by using Lyapunov method. The simulation results demonstrate the effectiveness and robustness of the proposed guidance method against a highly maneuverable target. © 2015 The Society of Instrument and control Engineers-SICE.

关键词： Lyapunov methods

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Analysis and diagnosis system for various industrial network protocols 6

Analysis and diagnosis system for various industrial network...

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6th International Conference on Electronic Information Technology and Computer Engineering, EITCE 2022

作者： Wang, Jian Jin, Ni Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences LiaoNing ShenYang China

ISBN: (纸本)9781450397148

For a comprehensive and systematic analysis of the communication quality in the industrial field, it is important for manufacturing enterprises to study effective diagnosis and evaluation methods and develop software tool to meet the actual needs of industrial communication networks for high quality, rapid diagnosis and positioning of anomalies. By analyzing the characteristics of various industrial network protocols, this paper studies the measurement methods of the key indicators of the real-time performance of industrial communication networks and the methods of communication anomaly diagnosis, and on this basis, designs and implements the analysis and diagnosis system for various industrial network protocols. © 2022 Association for Computing Machinery.

关键词： Quality control

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Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

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Petroleum Science 2024年第1期21卷 641-653页

作者： Yun-Peng He Hai-Bo Cheng Peng Zeng Chuan-Zhi Zang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016LiaoningChina Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016LiaoningChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169LiaoningChina University of Chinese Academy of Sciences Beijing100049China School of Artifcial Intelligence Shenyang University of TechnologyShenyang 110870LiaoningChina

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well *** learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis ***,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational ***,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different ***,there is heterogeneity in field data,which can dramatically impair the diagnostic *** solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this ***,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC ***,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data ***,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the *** on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational *** the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

关键词： Sucker-rod pumping system Dynamometer card Working condition recognition Deep learning Time-frequency signature Time-frequency signature matrix

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The System of Coordinated Operation of Two Underwater Vehicles in a Complex Environment

The System of Coordinated Operation of Two Underwater Vehicl...

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2023 International Conference on Ocean Studies, ICOS 2023

作者： Filaretov, Vladimir Katsurin, Alexey Institute of Automation and Control Processes Feb Ras Vladivostok State University Laboratory of Robotic Systems Laboratory of Automation and Robotics Vladivostok Russia Far Eastern Federal University M.D. Ageev Institute for Marine Technology Problems Feb Ras Laboratory of Intelligent Information Systems for Marine Robots Department of Automation and Robotics Vladivostok Russia

ISBN: (纸本)9798350382457

The paper discusses methods of coordinated operation of two autonomous underwater vehicles, one of which is equipped with a multi-link manipulator and a vision system, and the second - auxiliary - only a vision system. These methods ensure the joint operation of two autonomous underwater vehicles both in the mode of semi-automatic positional remote control, and in the mode of automatic execution of operations with various objects. At the same time, work is considered in situations when the vision system of the main underwater vehicle does not allow observing the object of work, which is nevertheless located in the working area of the manipulator. In this case, the auxiliary inspection underwater vehicle with its own vision system is used to monitor the object. In the semi-automatic remote control mode, the manipulator automatically takes into account the current spatial orientation of the optical axis of the vision system of the inspection underwater vehicle, as well as the spatial orientations of both underwater vehicles at yaw angles in the absolute coordinate system. And in automatic mode, an accurate transfer of the spatial location and orientation of the object, which are determined using the vision system of the inspection underwater vehicle, is additionally provided to the associated coordinate system of the main underwater vehicle. It is possible to identify and eliminate errors that occur during the operation of the vision system and navigation systems of both underwater vehicles. The results of experimental studies have confirmed the operability of the proposed methods. © 2023 IEEE.

关键词： Autonomous underwater vehicles

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

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Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Fault Detection Based on Hierarchical Mode Analysis with ICA-KICA 41

Fault Detection Based on Hierarchical Mode Analysis with ICA...

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第41届中国控制会议

作者： Shuai Li Xiaofeng Zhou Haibo Shi Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For the problem of fault detection in non-Gaussian and nonlinear multimode processes,a fault detection method based on hierarchical mode analysis with independent component analysis(ICA)-kernel independent component analysis(KICA) is *** stable and transition modes coexist in multimode processes and the mode information has uncertainty,hierarchical mode analysis is used for obtaining the hierarchical mode ***,the ICA-KICA is presented for modeling the stable and transition modes obtained from the hierarchical mode ***,a mode identification method based on discriminant function is given for fault *** penicillin fermentation process is used for the experiments of fault detection and the analyses indicate the performance of the fault detection based on hierarchical mode analysis with ICA-KICA.

关键词： Fault detection multimode process hierarchical mode analysis ICA-KICA

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Towards Disturbance Rejection in Feature Pyramid Network

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 946-958页

作者： Hu, Xiaobo Xu, Wei Gan, Yi Su, Jianbo Zhang, Jun Shanghai Jiao Tong University Joint Institute of UM-SJTU Shanghai200240 China Shanghai Jiao Tong University Research Center of Intelligent Robotics Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

The multiscale problem is one of the challenging topics in the object detection field. Among the current studies toward this problem, feature pyramid network (FPN) has been shown a superior performance. The core principle of FPN is a mapping for the detectable objects into hierarchy features. These features are designed with different size of receptive fields, which brings good scale invariance in the classification and localization subtasks. However, a disturbance of information dilution is generated by the assignment for the detectable objects into different features. This dilution disturbance is associated with the convolution or pooling operation during the hierarchy feature extraction process. Both of the imprecise localization information in the top features and the fuzzy classification information in the bottom ones limit the performance of FPN. Aiming at the disturbance rejection problem of information dilution, this article presents a feature compensation method. A cross compensation between the semantic information and the localization information in hierarchy features is used to enhance the vanilla FPN. Then, the evaluation metrics in an object detection task are examined. Not only the overall performance, but also the respective metrics for multiscale objects validate a considerable improvement of the FPN with a disturbance compensation mechanism. The experimental results demonstrate an effectiveness of the proposed method in this article. © 2020 IEEE.

关键词： Object detection

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Development of Method for Generating Trajectories of Movement of End Effectors and control Programs for Industrial Robots in an Uncertain Working Environment

Development of Method for Generating Trajectories of Movemen...

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2021 International Russian automation Conference, RusAutoCon 2021

作者： Yukhimets, Dmitry Gubankov, Anton Mursalimov, Eduard Institute of Automation and Control Processes Robotic Laboratory Vladivostok Russia Far Eastern Federal University Dept. of Automation and Robotics Vladivostok Russia Institute of Marine Technology Problems Laboratory of Intelligent Information Systems for Marine Robots Vladivostok Russia

ISBN: (纸本)9780738131566

the deals with the implementation of the method of the trajectories generating for end effectors and control programs for industrial robots in an uncertain working environment. To generate correct trajectories, it is proposed to sequentially process data from vision systems, correct them in the human-machine interface, generate a control program in a generalized form using universal commands and then translate it into the form that a specific industrial robot requires. Experimental studies of the proposed method were carried out, which confirmed the operability and effectiveness of the proposed method. © 2021 IEEE.

关键词： Trajectories

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Unsupervised Anomaly Detection Approach Based on Adversarial Memory Autoencoders for Multivariate Time Series

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Computers, Materials & Continua 2023年第7期76卷 329-346页

作者： Tianzi Zhao Liang Jin Xiaofeng Zhou Shuai Li Shurui Liu Jiang Zhu Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110000China Shenyang Institute of Automation Chinese Academy of SciencesShenyang110000China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110000China University of Chinese Academy of Sciences Beijing100000China

The widespread usage of Cyber Physical Systems(CPSs)generates a vast volume of time series data,and precisely determining anomalies in the data is critical for practical *** is the mainstream method for time series anomaly detection,and the anomaly is judged by reconstruction ***,due to the strong generalization ability of neural networks,some abnormal samples close to normal samples may be judged as normal,which fails to detect the *** addition,the dataset rarely provides sufficient anomaly *** research proposes an unsupervised anomaly detection approach based on adversarial memory autoencoders for multivariate time series to solve the above ***,an encoder encodes the input data into low-dimensional space to acquire a feature ***,a memory module is used to learn the feature vector’s prototype patterns and update the feature *** updating process allows partial forgetting of information to prevent model *** that,two decoders reconstruct the input ***,this research uses the Peak Over Threshold(POT)method to calculate the threshold to determine anomalous samples from normal *** research uses a two-stage adversarial training strategy during model training to enlarge the gap between the reconstruction error of normal and abnormal *** proposed method achieves significant anomaly detection results on synthetic and real datasets from power systems,water treatment plants,and computer *** F1 score reached an average of 0.9196 on the five datasets,which is 0.0769 higher than the best baseline method.

关键词： Anomaly detection autoencoder memory module adversarial training

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A distributed integrated energy trading solution

A distributed integrated energy trading solution

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2021 International Conference on Computer, Blockchain and Financial Development, CBFD 2021

作者： Dong, Jingya Song, Chunhe Zheng, Zeyu Zhang, Tao Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Nationality Department of Digital Factory Shenyang China University of Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9781665412278

Blockchain technology can bring profound changes to the energy industry and is now becoming a new driving force for the rapid development of this sector. In order to build a secure, reliable, and stable energy service system, it is necessary to study the framework and interaction mechanism of the energy trading system. This paper introduces a distributed integrated energy trading solution, proposes a new overall architecture, and analyses the blockchain model. This paper presents an algorithm to calculate the score directly in the client. Through this algorithm, users can choose service providers, get rid of cloud control, and realize users' free choice of electricity purchase and interaction between users through the smart contract. The test results show that the system has high performance and efficiency, can meet the needs of integrated energy transactions, and provides a solution for the application of blockchain in energy trading. © 2021 IEEE.

关键词： Smart contract

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