检索结果-内蒙古大学图书馆

第41届中国控制会议

作者： Kui Jie Wangyong He Renjie Gui School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

At present,rehabilitation robots usually work together with patients and train them to achieve therapeutic effects by assisting them to complete movement within a certain *** this paper,it analyzes the average length and proportion of Chinese human lower limbs,as well as the range of extreme motion and comfortable motion of each joint of human lower *** on the error transfer matrix of rigid body connecting rod,the three-DOF lower limb rehabilitation robot human lower limb static pose error model and human/machine integration model are *** D-H method was used to solve the kinematic function between the angle of each joint and the position of the end of human lower *** analysis of the kinematics of human lower limbs is to calculate its inverse kinematics *** the motion control of rehabilitation robots,the inverse kinematics is more important than the forward kinematics,which is the basis for rehabilitation robot to realize trajectory planning under the training mode of passive trajectory traction,as well as the basis for compliant ***,a simulation model is established with Matlab software,and the simulation results show the feasibility and safety of the rehabilitation training process.

关键词： Lower limb rehabilitation robot Range of motion Human kinematics

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Design of a Mesh Crawling Robot with Beetle-Inspired Variable Stiffness Tarsus

Design of a Mesh Crawling Robot with Beetle-Inspired Variabl...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chen, Hao Hu, Kai Hu, Longlong Zhou, Ziqi Li, Yao Li, Bing Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9781665481090

Compared with large robots, micro-robots have the advantages of small size, low power consumption, and high concealment. For complex terrain, the crawling performance of micro-robots will be significantly reduced. In this study, the mesh surface was used as the crawling base of the robot, and a variable stiffness tarsus was designed with the beetle as a reference. This tarsus composed of multiple bending parts achieves a large range of stiffness changes, 0.070.495 N/mm. We have achieved stiffness control of the tarsus in a single actuation by trajectory planning of the claw ends. The proposed robot can achieve a big stiffness of the tarsus to resist the deformation of the tarsus due to external forces, which means that the robot can increase the adhesion ability when crawling at the stance phase. Therefore, even when the load was increased from 10g to 40g, the average crawling speed of the robot was not significantly reduced. This new tarsus can improve the crawling performance of the micro-robot on the mesh. © 2024 IEEE.

关键词： Microrobots

来源：评论

学校读者我要写书评

暂无评论

Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

引用

Petroleum Science 2023年第2期20卷 1142-1154页

作者： Yun-Peng He Chuan-Zhi Zang Peng Zeng Ming-Xin Wang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangLiaoning 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyangLiaoning 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyangLiaoning 110169China University of Chinese Academy of Sciences Beijing100049China Shenyang University of Technology ShenyangLiaoning 110870China School of Automation and Electrical Engineering Shenyang Ligong UniversityShenyangLiaoning 110159China

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

关键词： Few-shot learning Indicator diagram Meta-learning Soft thresholding Sucker-rod pumping system Time–frequency signature Working condition recognition

来源：评论

学校读者我要写书评

暂无评论

MADDPG Based Radar Interference Resource Allocation Decision

MADDPG Based Radar Interference Resource Allocation Decision

引用

2024 China automation Congress, CAC 2024

作者： Jiang, Sen Wang, Bo School of HDU-ITMO Research Center for Intelligent Systems and Robotics Hangzhou Dianzi University Hangzhou310018 China School of Automation International Joint Research Laboratory for Autonomous Robotic Systems Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9798350368604

For the problem of jamming penetration under the one-to-many scenario with jammer, a real-time radar interference resource allocation method based on the Multi-agent deep deterministic policy gradient (MADDPG) algorithm is proposed. This method describes the interference resource allocation model as a Markov Decision Process (MDP), and designed the state space, action space and reward function for interference resource allocation problem. The jammer is divided into three heterogeneous agents, each responsible for selecting jamming targets, jamming patterns, and jamming power, respectively. These three agents coordinate to enhance the convergence ability of the high-dimensional action space algorithm. Simulation results indicate that the jamming resource allocation method designed in this paper provides better jamming effects on radar positions, higher stability, and effectively improves the operational performance of the jammer. © 2024 IEEE.

关键词： Radar interference

来源：评论

学校读者我要写书评

暂无评论

A Weighting Factors Autotuning Strategy for Model Predictive Torque Control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm 42

A Weighting Factors Autotuning Strategy for Model Predictive...

引用

42nd Chinese Control Conference, CCC 2023

作者： Zhou, Zixiang Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Temperature Rising Model of Tubular Permanent Magnet Linear Synchronous Motor Based on Transfer Learning-Deep Neural Network 42

Temperature Rising Model of Tubular Permanent Magnet Linear ...

引用

42nd Chinese Control Conference, CCC 2023

作者： Wang, YiFei Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

High temperature rise of permanent magnet linear synchronous motor can lead to irreversible demagnetization of the motor permanent magnet, which can negatively affect the motor performance. To address this problem, a thermal modeling analysis method based on Transfer learning-Deep neural network (TL-DNN) was proposed in this paper. Its specific implementation steps include (1) corresponding to different heat source inputs, the equivalent thermal circuit method and the finite element analysis was adopted based on the structure and main parameters of PMLSM including overall average temperature rise, coil temperature rise and permanent magnet temperature rise from the data sets of the motor;(2) TL-DNN was used to fit the functional relationship between the input source features and the output targets based on the characteristics of the sample data sets. In order to verify the accuracy of the prediction model with small sample data sets, this paper divided the proportion of the data set and compared the results with other classic nonparametric models (random forest, support vector machine, and deep neural network). The results show that the TL-DNN model outperforms other machine learning models and has better robustness and generalization ability when the training datasets are insufficient, and achieves an organic combination of physical field path model and data-driven model, which provides a feasible solution for PMLSM modeling in the case of small samples. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

A Battery Control Strategy for Sequential Utilization of Energy Storage systems in Power Batteries 7

A Battery Control Strategy for Sequential Utilization of Ene...

引用

7th IEEE Advanced Information Technology, Electronic and automation Control Conference, IAEAC 2024

作者： Li, Bowen Cui, Shijie Zhu, Lizhong Shenyang Ligong University College of Automation and Electrical Engineering Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350339161

With the widespread adoption of energy storage systems utilizing power batteries, battery lifespan degradation has become a primary constraint on system performance. To address this issue, this study proposes a lifespan-optimized battery control strategy. Firstly, a battery lifespan calculation model for the energy storage system is established, taking into detailed consideration key parameters such as battery State of Charge (SOC). Secondly, a control strategy based on SOC for charging and discharging is designed, aiming to minimize battery lifespan consumption to the greatest extent possible. Finally, experimental results demonstrate that the proposed control strategy significantly improves the lifespan of the energy storage system compared to existing strategies. This research provides an effective means of control for the long-term stable operation of power battery systems. © 2024 IEEE.

关键词： Charging (batteries)

来源：评论

学校读者我要写书评

暂无评论

Mechanical Properties Inside Origami-Inspired Structures: An Overview

引用

Applied Mechanics Reviews 2025年第1期77卷 011001页

作者： Yan, Peng Huang, Hailin Meloni, Marco Li, Bing Cai, Jianguo Department of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518052 China Harbin Institute of Technology Shenzhen518052 China Key Laboratory of C & PC Structures of Ministry of Education National Prestress Engineering Research Center Southeast University Nanjing211189 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen518052 China Key University Laboratory of Mechanism Machine Theory and Intelligent Unmanned Systems of Guangdong Habin Institute of Technology Shenzhen518052 China

In recent decades, origami has transitioned from a traditional art form into a systematic field of scientific inquiry, characterized by attributes such as high foldability, lightweight frameworks, diverse deformation modes, and limited degrees-of-freedom. Despite the abundant literature on smart materials, actuation methods, design principles, and manufacturing techniques, comprehensive reviews focusing on the mechanical properties of origami-inspired structures are relatively rare and unsystematic. This review aims to fill this void by analyzing and summarizing the significant studies conducted on the mechanical properties of origami-inspired structures from 2013 to 2023. We begin with an overview that includes essential definitions of origami, classical origami patterns, and their associated tessellated or stacked structures. Following this, we delve into the principal dynamic modeling method for origami and conduct an in-depth analysis of the key mechanical properties of origami-inspired structures. These properties include tunable stiffness, bistability and multistability, metamechanical properties demonstrated by origami-based metamaterials, and bio-inspired mechanical properties. Finally, we conclude with a comprehensive summary that discusses the current challenges and future directions in the field of origami-inspired structures. Our review provides a thorough synthesis of both the mechanical properties and practical applications of origami-inspired structures, aiming to serve as a reference and stimulate further research. © 2025 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Degrees of freedom (mechanics)

来源：评论

学校读者我要写书评

暂无评论

Feature Space Augmentation and Old Class Space Preservation for Class Incremental Learning 42

Feature Space Augmentation and Old Class Space Preservation ...

引用

42nd Chinese Control Conference, CCC 2023

作者： Zeng, Ming Li, Siying Liu, Jiazhe Li, Yuanhao Institute of Robotics and Automation Systems School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China

ISBN: (纸本)9789887581543

The ability of continuously learning new knowledge without forgetting old ones is crucial to adapt to an ever-changing world. This scenario becomes more challenging when the previous data are not available. Current class incremental learning (CIL) approaches tend to incorporate new classes with backward compatibility, i.e., maintaining discriminability of old ones. By contrast, we focus on the extensibility and compatibility for future new classes in the early stage. Our proposed method achieves this by augmenting feature space. In detail, a large number of pseudo-new classes are generated via real example mixture and then train the initial spatially augmented model using pseudo-new classes and the base classes. Besides, considering the fact that it is impossible to maintain backward compatibility with only one prototype for each old class, the updated model also needs to preserve old class space in incremental stages. We employ a certain perturbation to the old class prototypes to effectively avoid old class space from being over-squeezed by the samples of new classes. The experiments on CIFAR-100 and ImageNet-Subset (100 classes) demonstrate that our method substantially reduces the overlap of old and new classes, outperforming state-of-the-art various baselines. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Catastrophic forgetting Class incremental learning Feature space augmentation Old class space preservation Pseudo-new classes

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：