检索结果-内蒙古大学图书馆

Multisource Domain Metalearning Network for Battery State-of-Health Estimation under Multitarget Working Conditions

IEEE Transactions on Power Electronics 2025年第7期40卷 9786-9799页

作者： Miao, Mengqi Xiao, Chaoang Yu, Jianbo Tongji University School of Mechanical Engineering Shanghai201804 China Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Shanghai201804 China

State of health (SOH) estimation is important in battery health prognostics. The discrepancy in working conditions gives rise to the phenomenon of domain shift, which presents a significant obstacle to the accurate estimation of battery SOH. Domain adaptation (DA) has been widely used to solve the domain shift problem in battery SOH estimation by minimizing the distribution discrepancy between different domains. However, the multitarget domain shift problem is not be addressed well for existing methods. Most existing DAs only consider a single target domain, which means that the model needs to be retrained when new scenarios emerge, which differ from the original target working condition. In this article, multisource domain metalearning network (MSDMLN) is proposed for battery SOH estimation under multiple target working conditions. A novel metalearning method, multisource domain metalearning (MSDML) strategy is developed for enhancing the generalization of the network by diversifying battery health degradation features based on meta fusion block. Empirical mode decomposition-densely connected recurrent-convolution network is developed to extract global degradation tendency and local fluctuation features of Li-ion batteries. The effectiveness of MSDMLN is verified on the combined Li-ion battery dataset. The results demonstrate that MSDMLN achieved low mean absolute error (i.e., 0.0474) and normalized root mean square error (i.e., 0.2187) for three different target operating conditions, which is better than other state-of-the-art methods. This illustrates the outperformance of MSDMLN in generalizing the estimation of battery SOH under multitarget working conditions, due to the integration of MSDML and the meta fusion block. © 1986-2012 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

On Graph Reduction in Consensus Control of Multi-agent Systems: A Preliminary Study

On Graph Reduction in Consensus Control of Multi-agent Sys...

引用

27th RoboCup International Symposium, 2024

作者： Setayeshi, Amirali Babi, Zeynab Ezzati Saadati, Ali Sadeghnejad, Soroush Tehran Iran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran Tehran Iran

ISBN: (纸本)9783031858581

Since the use of multi-agent systems has significantly increased over the past few decades, it is crucial to study the methods used in this area and take implementation-related practical issues into consideration. For instance, in the formulation of the consensus problem, the communication between the agents is depicted using a graph, where each edge represents a communication link between the agents. In practical terms, there will be significant operational challenges and costs associated with implementing each of these communication channels in various forms. Therefore, in this study, the graph reduction problem has been presented as an optimization problem, accompanied by six distinct cost functions. The objective is to reduce the size of a graph without compromising its fundamental characteristics. Hence, the cost functions provided are formulated to minimize the number of edges in the resulting graph while ensuring that the consensus error remains bounded. Ultimately, simulations were performed to demonstrate the effectiveness of the proposed approach. The outcomes derived from the specified set of cost functions were then compared to several conventional topologies in multi-agent systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Controllability analysis of mechanical multibody dynamics control systems based on lie symmetry

引用

Alexandria engineering Journal 2025年 127卷 374-379页

作者： Mingliang, Zheng School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Human-computer collaborative robot Joint Laboratory of Anhui Province Huainan232038 China

To quantitatively characterize the dynamic controlled performance of mechanical multibody systems and design collaborative control strategies, this paper investigates the controllability of mechanical multibody dynamic control systems. Firstly, under the affine connection framework of Lagrange mechanical control systems, we establish the Euler-Poincaré equations of unconstrained mechanical multibody dynamics control systems by differential geometry method;Further, we transform the Euler-Poincaré equations into the classical state space form of nonlinear control systems by augmented vector method;Secondly, by introducing Lie group representation theory, the definition and the solution of generalized Lie symmetry for mechanical multibody dynamics control systems are given, and the necessary and sufficient conditions for state controllability (local controllability) are given by using Lie symmetry;Finally, an application example of dynamic control of a single degree of freedom manipulator with basic vibration is provided, it explains the effectiveness and correctness of the Lie symmetry method in this paper. The research has shown that using Lie symmetry to analyze the controllability problem of mechanical multibody dynamics control systems can be transformed into its low-dimensional quotient space analysis, and if the quotient space is controllable at a point, then the system can be controllable for all points on the orbit where that point at. © 2025

关键词： Controllability

来源：评论

学校读者我要写书评

暂无评论

KINEMATICS ANALYSIS AND SIMULATION OF LASER WELDING robot FOR SOLAR PANEL BUSBAR

International Journal of Mechatronics and Applied Mechanics

引用

International Journal of Mechatronics and Applied Mechanics 2025年第19期1卷 198-204页

作者： Peng, Wang Mingliang, Zheng School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Human-computer collaborative robot Joint Laboratory of Anhui Province Huainan232038 China

To overcome the insufficient quality stability of the overlap welding joints of solar panel busbar, using laser brazing technology, a new type of serial gantry robot with five degrees of freedom (three translations and two rotations) is designed. Firstly, the structure scheme of the gantry laser welding robot with five degrees of freedom for solar panel busbar is introduced. Secondly, the D-H linkage coordinate system of the welding robot is established, and the kinematics forward and inverse solutions and the velocity Jacobian matrix are solved. Finally, the kinematics forward and inverse solutions are verified by using robotics toolbox in Matlab;the reachable space of the robot is calculated by Monte-Carlo method;the kinematics simulation of the laser welding robot end effector is carried out by using Adams software. The results show that the displacement of the end effector of the gantry laser welding robot with five degrees of freedom for solar panel busbar is non-interference and the velocity curves change smoothly, which verifies the rationality of this structural design. By making a prototype and building a test platform for experimental verification, the robot ran smoothly, the weld seam layout was efficient and accurate, and the error at the end of the robot welding gun was within 0.28 mm. © 2025 The Author(s).

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

A Nonlinear MPC-Net Optimization Framework for Wheeled humanoid robots with Whole Body Dynamics

引用

IEEE Transactions on Automation Science and engineering 2025年

作者： Li, Guoxin Liu, Xingjian Wu, Xiaoyu Tang, Qirong Zhang, Hao Li, Zhijun Shi, Peng Tongji University School of Mechanical Engineering Translational Research Center Shanghai YangZhi Rehabilitation Hospital Shanghai Sunshine Rehabilitation Center Shanghai200092 China Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Shanghai201804 China State Key Laboratory of High-Performance Precision Manufacturing Dalian116024 China Tongji University School of Mechanical Engineering Shanghai201804 China National University of Singapore Department of Biomedical Engineering 117583 Singapore Tongji University Department of Control Science and Engineering Shanghai201804 China The University of Adelaide School of Electrical and Mechanical Engineering SA5005 Australia Obuda University Budapest1034 Hungary

The task performance of mobile manipulators can be significantly enhanced by whole-body control and optimization in complex scenarios. Due to the nonlinear properties of whole-body dynamics and parameter uncertainty, modeling accurate system dynamics is essential in addition to designing an effective control strategy. However, traditional control methods have high computational costs and fail to deal with the parameter errors caused by model linearization. To address these issues, we propose a model predictive control (MPC)-Net, a learning-based approach that facilitates rapid online optimization by combining deep learning with multiple MPCs. Firstly, we develop a parameter identification algorithm based on a deep neural model to estimate the unknown dynamics parameters. Although the control performance of the MPC approach positively correlated with the prediction horizon, a long horizon would result in additional computational costs. Thus, MPC-Net is constructed by combining multiple sub-MPC issues, and the nonlinear coefficients are obtained by using a deep neural network-based optimization framework. Furthermore, MPC-Net generates the solution by combining the outputs of multiple sub-MPC problems using the nonlinear transformation of learned coefficients. Experiments are conducted on a mobile manipulator, which demonstrates the proposed MPC-Net-based optimization control offers fast efficient computation and low tracking error performance. © 2004-2012 IEEE.

关键词： Predictive control systems

来源：评论

学校读者我要写书评

暂无评论

Effect of the configuration and concentration of B-doping on the thermal properties and structural stability of graphene: A theoretical study

引用

Diamond and Related Materials 2025年 156卷

作者： Li, Dongbo Da, Liangguo Huang, Kaifeng Li, Dong Yu, Liang Wang, Haini Yu, Yaqi Wu, Long Tang, Yunqing School of Mechanical and Electrical Engineering Huainan Normal University Huainan232038 China Human-computer collaborative robot Joint Laboratory of Anhui Province Huainan232038 China School of Mechanical Engineering Shandong University Jinan250061 China State Key Laboratory of Advanced Equipment and Technology for Metal Forming Shandong University Jinan250061 China Key Laboratory of High Efficiency and Clean Mechanical Manufacture Ministry of Education Shandong University Jinan250061 China

The thermal properties and structural stability of B-doped graphene were investigated by employing density functional theory (DFT), ab initio molecular dynamics (AIMD), and molecular dynamics (MD) simulations, with a focus on the effects of doping configuration and concentration. DFT calculations indicate that B-doping reduces the cohesive energy of graphene, consequently diminishing its structural stability. Among the three B double-doping configurations, only the para configuration exhibits a phonon dispersion without imaginary frequencies, whereas both meta and ortho configurations show imaginary frequencies, indicating structural instability. The AIMD results further demonstrate that B-doped graphene preferentially undergoes cleavage at B[sbnd]B bonds, leading to decreased structural stability. MD results show that B-doping significantly reduces the thermal conductivity of graphene. At a doping concentration is 0.6 %, the thermal conductivity of meta and para configurations decreases to 48.08 % and 54.6 % of that of the pristine graphene, respectively. The results of phonon properties show that B-doping reduces the phonon participation rate and induces strong phonon localization at the B-doped site. These results and conclusions will provide valuable theoretical insights for the thermal design of graphene-based semiconductor devices. © 2025 Elsevier B.V.

关键词： Temperature distribution

来源：评论

学校读者我要写书评

暂无评论

Autonomous robotic Assembly and Sequence Planning Based on YOLOv8 11

Autonomous Robotic Assembly and Sequence Planning Based on Y...

引用

11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Babi, Zeynab Ezzati Khomami, Navid Asadi Masouleh, Mehdi Tale Kalhor, Ahmad University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran School of Mechanical Engineering Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9798350308105

This study contributes to autonomous assembly by introducing a robotic building system designed to observe its workspace, plan building sequences, determine appropriate grasps and manipulator motions, and operate hardware in real-time. This study involves the creation of a wooden brick dataset and employs a YOLOv8 deep learning model for object segmentation in two implemented real-time algorithms, namely, Desired Construction Object Detection (DCOD) and robot Current Frame Object Detection (RCFOD). The DCOD algorithm is designed for the desired structure, while the RCFOD algorithm is utilized for detecting objects within the operational environment of the robot. By comparing the outputs of these two algorithms, sequences of objects for assembly are formulated, and the appropriate grasp positions are determined. Subsequently, the robot's motion planning for both grasping and construction tasks is executed. Due to the limitations of using a single RGB gripper-mounted camera, various issues, such as failing to recognize items with the same cross-section but varying heights, have been addressed in this study. The results of this study indicate the effective learning of the YOLOv8 model, as shown by a loss value below 0.2 and an accuracy over 90% for 17 out of the total 18 classes. Practical implementation is done by a common industrial Delta parallel robot, a 2-finger gripper, and a simple RGB camera. Overview of practical implementation system is shown in Fig. 1. The proposed robotic assembly method demonstrates its effectiveness in autonomously constructing structures utilizing a reduced and cost-efficient configuration. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

AGILE: Approach-based Grasp Inference Learned from Element Decomposition 11

AGILE: Approach-based Grasp Inference Learned from Element D...

引用

11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Koosheshi, Mohammadhossein Hosseini, Hamed Masouleh, Mehdi Tale Kalhor, Ahmad Yazdi, Mohammad Reza Hairi University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Iran University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Iran University of Tehran School of Mechanical Engineering College of Engineering Iran

ISBN: (纸本)9798350308105

humans, this species expert in grasp detection, can grasp objects by taking into account hand-object positioning information. This work proposes a method to enable a robot manipulator to learn the same, grasping objects in the most optimal way according to how the gripper has approached the object. Built on deep learning, the proposed method consists of two main stages. In order to generalize the network on unseen objects, the proposed Approach-based Grasping Inference involves an element decomposition stage to split an object into its main parts, each with one or more annotated grasps for a particular approach of the gripper. Subsequently, a grasp detection network utilizes the decomposed elements by Mask R-CNN and the information on the approach of the gripper in order to detect the element the gripper has approached and the most optimal grasp. In order to train the networks, the study introduces a robotic grasping dataset collected in the Coppeliasim simulation environment. The dataset involves 10 different objects with annotated element decomposition masks and grasp rectangles. The proposed method acquires a 90% grasp success rate on seen objects and 78% on unseen objects in the Coppeliasim simulation environment. Lastly, simulation-to-reality domain adaptation is performed by applying transformations on the training set collected in simulation and augmenting the dataset, which results in a 70% physical grasp success performance using a Delta parallel robot and a 2 -fingered gripper. © 2023 IEEE.

关键词： Grippers

来源：评论

学校读者我要写书评

暂无评论

Design and Fabrication of an Optimized Six-Axis Force-Torque Sensor 11

Design and Fabrication of an Optimized Six-Axis Force-Torque...

引用

11th RSI International Conference on robotics and Mechatronics, ICRoM 2023

作者： Ehsani, Amirhossein Khomami, Navid Asadi Ghaneie, Meysam Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

Force-torque sensors hold significant applications across various industries, including industrial automation, robotics, aerospace, medicine, and laboratory settings. In this paper the purpose is to optimize, simulate, and fabricate a six-axis force-torque sensor capable of measuring forces and torques along x, y and z axes. This endeavor faces challenges, including the meticulous installation of strain gauges, the design of an optimal structure and the creation of a sensor which is not excessively complex to fabricate. Careful attention is devoted to precise installation of strain gauges due to their sensitivity and crucial role in accurate measurement. Furthermore, the sensor structure is strategically designed to be optimal yet not intricate to fabricate, balancing between accuracy, optimality and feasibility of fabrication. Utilizing a genetic optimization algorithm with multi-objective functions instead of single-objective functions, this paper aims to determine the optimal dimensions. The application of multi-objective functions allows for more nuanced and flexible optimization process, catering to the complex requirements of the sensor design. Subsequently, the final design is simulated using ANSYS software to create a finite element model, providing a detailed analysis of the sensor's behavior under various conditions. This approach ensures a comprehensive understanding of the sensor's characteristics and limitations. A comprehensive analysis of the results is carried out, with the primary objective of minimizing manufacturing costs while ensuring that performance characteristics, such as an accuracy level of lOmN for force axes and 3.5mNm for torques, are demonstrated by the sensor. In order to sense strains, 16 Double strain gauges are employed. Sensor circuits are configured using six Wheatstone bridges, and calibration procedure is operated using a setup constructed in human and robot interaction laboratory. © 2023 IEEE.

关键词： human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Kinematic analysis of an under-constrained cable-driven robot using neural networks 28

Kinematic analysis of an under-constrained cable-driven robo...

引用

28th Iranian Conference on Electrical engineering, ICEE 2020

作者： Zare, Soroush Haghighi, Morteza Shahamiri Hairi Yazdi, Mohammad Reza Kalhor, Ahmad Masouleh, Mehdi Tale School of Mechanical Engineering Human and Robot Interaction Laboratory University of Tehran Tehran Iran School of Electrical and Computer Engineering Human and Robot Interaction Laboratory University of Tehran Tehran Iran School of Mechanical Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781728172965

In this paper, three types of neural networks including, multilayer perceptron, radial basis function, and Local Linear Model Trees, are considered based on adaptability with the significant behavior of data to solve the forward and inverse kinematics of the under-constrained cable-driven parallel robot. The practical workspace of the robot is a rectangular cube with dimensions of 360cm × 220c× 160cm. Forward kinematics problem of the under-constrained cable-driven parallel robot is challenging to solve by reason of complexity and nonlinearity of the robot kinematic equations. The typical approach utilizes a numerical method to solve these equations, which are computationally expensive and very time-consuming. Resorting to the neural network approaches results in the feasible orientation, which confirms that all the cables are in tension. The trained neural network gives a feasible inverse kinematic problem solution and the running time of the optimal trained neural network in the control loop, obtained about 12 microseconds, pales in comparison to the sampling time of the control loop that facilitates the real-time control of the robot. Obtained results reveal that the multilayer perceptron has the mean average error order of about 2 millimeters for the position and 0.78 degrees for orientation, which makes a case for precise control in the high-speed motion of the robot. © 2020 IEEE.

关键词： Multilayer neural networks

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：