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Chinese Automation Congress (CAC)

作者： Tao Zhang Yingjie Xiong Bolun Wang Hongyu Yan Xiyou Chen School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China College Of Information Science and Engineering Northeastern University Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (纸本)9781665426480

Permanent magnet synchronous motors(PMSM) are popular in AC motor applications due to their small size, high efficiency. They have appeared widely in various areas of life. Due to the high-frequency chattering problem caused by sliding mode observer sensorless control of PMSM, an SMO with piecewise control function is designed in this paper. At the same time, based on the back EMF output of the SMO, the gain of the SMO is adapted to reduce the system bucket vibration problem caused by the conventional SMO. Finally, a simulation experiment was carried out in MATLAB/SIMULINK and compared with the conventional SMO. The results show that the improved SMO has achieved a better control effect.

关键词： Vibrations Adaptation models AC motors Force Sensorless control Observers Permanent magnet motors

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The Design and Implementation of Human Motion Capture System Based on CAN Bus *

The Design and Implementation of Human Motion Capture System...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Xian YUE Aibin ZHU Jiyuan SONG Guangzhong CAO Delin AN Zhifu GUO Institute of Robotics & Intelligent Systems Shaanxi Key Laboratory of Intelligent Robots Xi'an Jiaotong University Xi'an China Shenzhen Key Laboratory of Electromagnetic Control Shenzhen University Shenzhen China Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an China Taiyuan Institute Co.Ltd. of China Coal Technology and Engineering Group Taiyuan China

ISBN: (数字)9781728157153

ISBN: (纸本)9781728157160

Aiming at the existing problems of exoskeletons in human motion capture and recognition, causing human can only move passively in the exoskeleton, which is difficult to efficiently rebuild the connection between human muscles and nerves. This paper describes a system for the analysis of human motion capture based on CAN bus. The system adopts a distributed system architecture, which can collect data including plantar pressure, exoskeleton joint angle, and provide data support for subsequent motion recognition algorithm. The system has a simple measurement method and low dependence on measurement environment. The accuracy of the system is verified by the contrast experiment of Vicon 3D motion capture system. The results of the experiment indicate that the designed human motion capture system has a high accuracy, and meets the requirements of human motion perception when controlling the Rehabilitation Exoskeleton.

关键词： Robot sensing systems Exoskeletons Legged locomotion Foot Pressure sensors Acceleration

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Research on Collaboration Method of Edge IoT Agent Based on Actor Model

Research on Collaboration Method of Edge IoT Agent Based on ...

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Power and Energy Engineering (ICPEE), International Conference on

作者： Bowen Zhang Weiwei Miao Lei Wei Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Information & Telecommunication Branch State Grid Jiangsu Electric Power Co. Ltd. Nanjing China State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

ISBN: (纸本)9781665420471

Focusing on the resource constrained IoT agent collaboration requirements at the edge of the power Internet of things, this paper proposes an edge agent collaborative computation method based on Actor model to satisfy the rapid processing and response requirements of large-scale data in the perception layer of the power Internet of things. Through a unified programming model, this paper can divide the collection and analysis of sensing data in the sensing layer of the power Internet of things into functional components, which can be deployed in different edge IoT agents, to improve the rapid processing ability of edge-side data. At the same time, the components achieve the function cooperation through the message passing mechanism. Finally, this paper implements the proposed scheme based on Akka framework, and designs the edge IoT agent collaborative computing prototype. The prototype system experiments show that the proposed scheme can split the complex services with high resource requirements into different components and deploy them in different edge IoT agents. The proposed method can improve the resource utilization and data processing capacity of the edge IoT agent of the power Internet of things, while ensuring the real-time requirements of edge service analysis.

关键词： Computational modeling Message passing Collaboration Prototypes Programming Data models Real-time systems

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Fault Detection using Common and Specific Variable Decomposition for Nonlinear Multimode Process

Fault Detection using Common and Specific Variable Decomposi...

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Chinese Automation Congress (CAC)

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

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Due to the change of operating conditions including external environments and production schemes, there are usually multiple modes in most industrial processes. Moreover, different linear and nonlinear correlations simultaneously coexist in different modes, which brings difficulty to fault detection. Aiming at this problem, the paper proposes a fault detection method using common and specific variable decomposition for nonlinear multimode process. The proposed method takes into account the linear and nonlinear correlations in different modes and utilizes the common and specific modeling ideas for enhancing the performance of fault detection in multimode process. First, the multimode process data are divided into the common variable subspace and the specific variable subspace based on sliding window low-order and high-order statistics. Then, the nonlinearity coefficient is used to evaluate the linear and nonlinear correlations for each variable subspace. Subsequently, the common and specific PCA-KPCA-SPCA-based multimode process modeling is developed for fault detection. The fault detection results of the Tennessee Eastman (TE) process demonstrate the feasibility and effectiveness of the proposed method.

关键词： Fault detection Correlation Principal component analysis Silicon Process control Manufacturing Loading

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End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences

End-to-End 3D Point Cloud Learning for Registration Task Usi...

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2020 IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Huanshu Wei Zhijian Qiao Zhe Liu Chuanzhe Suo Peng Yin Yueling Shen Haoang Li Hesheng Wang The Chinese University of Hong Kong T Stone Robotics Institute Hong Kong Shanghai Jiao Tong University China University of Cambridge United Kingdom Carnegie Mellon University Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

3D Point cloud registration is still a very challenging topic due to the difficulty in finding the rigid transformation between two point clouds with partial correspondences, and it's even harder in the absence of any initial estimation information. In this paper, we present an end-to-end deep-learning based approach to resolve the point cloud registration problem. Firstly, the revised LPD-Net is introduced to extract features and aggregate them with the graph network. Secondly, the self-attention mechanism is utilized to enhance the structure information in the point cloud and the cross-attention mechanism is designed to enhance the corresponding information between the two input point clouds. Based on which, the virtual corresponding points can be generated by a soft pointer based method, and finally, the point cloud registration problem can be solved by implementing the SVD method. Comparison results in ModelNet40 dataset validate that the proposed approach reaches the state-of-the-art in point cloud registration tasks and experiment resutls in KITTI dataset validate the effectiveness of the proposed approach in real applications.

关键词： Three-dimensional displays Aggregates Pose estimation Feature extraction Task analysis intelligent robots

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Spherical interpolated convolutional network with distance-feature density for 3D semantic segmentation of point clouds

arXiv

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arXiv 2020年

作者： Wang, Guangming Yang, Yehui Zhang, Huixin Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Computer Science and Technology University of Cambridge United Kingdom

The semantic segmentation of point clouds is an important part of the environment perception for robots. However, it is difficult to directly adopt the traditional 3D convolution kernel to extract features from raw 3D point clouds because of the unstructured property of point clouds. In this paper, a spherical interpolated convolution operator is proposed to replace the traditional grid-shaped 3D convolution operator. This newly proposed feature extraction operator improves the accuracy of the network and reduces the parameters of the network. In addition, this paper analyzes the defect of point cloud interpolation methods based on the distance as the interpolation weight and proposes the self-learned distance-feature density by combining the distance and the feature correlation. The proposed method makes the feature extraction of spherical interpolated convolution network more rational and effective. The effectiveness of the proposed network is demonstrated on the 3D semantic segmentation task of point clouds. Experiments show that the proposed method achieves good performance on the ScanNet dataset and Paris-Lille-3D dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

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A Piecewise-Markovian Lyapunov Approach to Reliable Output Feedback control for Fuzzy-Affine systems With Time-Delays and Actuator Faults

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第9期48卷 2723-2735页

作者： Wei, Yanling Qiu, Jianbin Shi, Peng Wu, Ligang State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China School of Electrical and Electronic Engineering University of Adelaide Adelaide SA Australia Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

This paper addresses the problem of delay-dependent robust and reliable H-infinity static output feedback (SOF) control for a class of uncertain discrete-time Takagi-Sugeno fuzzy-affine (FA) systems with time-varying delay and actuator faults in a singular system framework. The Markov chain is employed to describe the actuator faults behaviors. In particular, by utilizing a system augmentation approach, the conventional closed-loop system is converted into a singular FA system. By constructing a piecewise-Markovian Lyapunov-Krasovskii functional, a new H-infinity performance analysis criterion is then presented, where a novel summation inequality and S-procedure are succeedingly employed. Subsequently, thanks to the special structure of the singular system formulation, the piecewise-affine SOF controller design is proposed via a convex program. Lastly, illustrative examples are given to show the efficacy and less conservatism of the presented approach.

关键词： Piecewise Markovian Lyapunov functional reliable output feedback control time-varying delay T-S fuzzy-affine (FA) systems

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Adaptive tracking control of flapping wing micro-air vehicles with averaging theory

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CAAI Transactions on Intelligence Technology 2018年第1期3卷 18-27页

作者： Chen Qian Yongchun Fang Institute of Robotics and Automatic Information Systems College of Computer and Control Engineering Tianjin 300353People's Republic of China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin 300353 People's Republic of China

An input constrained adaptive tracking controller is designed for flapping micro aerial vehicles, wherein the moving averaging filter is adopted to estimate the averaged states of the system. Specifically, in the outer loop controller, an observer is constructed to estimate the disturbances within the system. Moreover, the constrained thrust is designed to keep the frequency in a proper region so as to meet the requirement of average estimation. Then, a tracking differentiator is used to provide trackable trajectories for the inner loop. Subsequently, a new quaternion- based hybrid attitude tracking controller is designed which successfully deals with high-frequency noises and avoids possible chattering. As supported by mathematical analysis, the proposed control strategy guarantees the uniform ultimate boundedness of the closed-loop system, and it keeps the control torques within the permitted range to meet the application requirement. At last, numerical simulations are carried out to support the validity of the proposed controller, whose results are satisfactory even when the thrust and torques are saturated.

关键词：飞行器跟踪器人工智能发展现状

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Seeking the Analytical Approximation of the Stance Dynamics of the 3D Spring-Loaded Inverted Pendulum Model By Using Perturbation Approach

Seeking the Analytical Approximation of the Stance Dynamics ...

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2019 IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Haitao Yu Shengjun Wang Kaizheng Shan Jun Li Lixian Zhang Haibo Gao State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

The Spring-Loaded Inverted Pendulum (SLIP) has been widely exploited in both biomechanical and robotics research due to its simple form in mathematics and high accuracy in fitting experimental biology data. However the intrinsic nonlinearity of the SLIP dynamics makes accurate analytical representation unavailable. Traditional methods take advantage of numerical integration to handle this issue while several existing analytical approximations focusing on 2D-SLIP model. The 3D-SLIP suitable to physical reality is rarely investigated. This paper presents a novel perturbation-based approach to obtain the closed-form analytical approximations of the 3D-SLIP model in stance phase. In contrast to existing work ignoring the gravitational forces, the proposed approach just relies on assumptions of small leg compression and small leg swept angle. The performance of the derived approximations has been evaluated via comprehensive numerical analysis. The quality of accurate apex prediction promises the approximation as an advantageous and reliable tool for locomotion control of legged robots.

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Research on PMSM Vector control System Based on Fuzzy PI Parameter Self-Tuning

Research on PMSM Vector Control System Based on Fuzzy PI Par...

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IEEE International Conference on Power and Energy systems (ICPES)

作者： Jianhua Ding Tao Zhang Ran Tao Anna Wang Northeastern University Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Dalian University of Technology Dalian China

ISBN: (数字)9781665404945

ISBN: (纸本)9781665404952

Based on the analysis of the permanent magnet synchronous motor (PMSM) mathematical model, a PMSM rotor field-oriented double closed-loop vector control system is constructed. Aiming at the defects of slow speed response, large overshoot, severe torque ripple, and poor anti-disturbance ability in the traditional PI controller used in the system speed loop, a fuzzy PI parameter self-tuning controller is proposed. The controller can set the two parameters of proportional and integral online according to fuzzy control rules. The system simulation model is built based on Matlab/Simulink. The simulation results show that the fuzzy PI parameter self-tuning controller has the advantages of fast dynamic response, high steady-state precision and strong anti-disturbance capability.

关键词： PI control systems simulation Steady-state Mathematical model Torque measurement Machine vector control Matlab

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