检索结果-内蒙古大学图书馆

作者： Zu, Hongfei Chen, Xuwen Chen, Zhangwei Wang, Zhirong Zhang, Xiang School of Mechanical Engineering & Automation Zhejiang Sci-Tech University China Zhejiang Premax Technology Co. Ltd Ningbo315048 China State Key Laboratory of Fluid Power and Mechatronics Systems Zhejiang University China Hangzhou ECON Technology Co. Ltd Hangzhou310015 China School of Computer Science Hangzhou Dianzi University Hangzhou310000 China

Positioning accuracy is of great significance for industrial robots in high-end industries. In addition to kinematic parameter errors, there are also some dynamic parameter errors, which are nonlinear. This paper proposes a novel method to improve the positioning accuracy of industrial robot, which takes both kinematics and dynamics parameter errors into account. Firstly, the method uses improved Denavit-Hartenberg (DH) model to establish kinematics model and identifies the geometric errors. Then, the deformation of the joint is analysed, and the angle deviation of each joint due to the end load is compensated. Finally, the accuracy improvement experiment is carried out on 6R robot. The experimental results show that the method is very effective. © 2021

关键词： Industrial robots

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Synergistic Toughening of Graphene Films by Addition of Hydroxylated Carbon Nanotube

Synergistic Toughening of Graphene Films by Addition of Hydr...

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European Microelectronics and Packaging Conference, EMPC

作者： Sihua Guo Jin Chen Yuanyuan Wang Shujin Chen Maomao Zhang Johan Liu SMIT Center School of Mechatronics Engineering and Automation Shanghai University Shanghai P. R. China Electronics Materials and Systems Laboratory Chalmers University of Technology Gothenburg Sweden SHT Smart High-Tech AB Kemivägen 6 Gothenburg Sweden

Graphene attracts great attention due to its excellent properties. However, the mechanical of assembled graphene-based film is usually inferior than its inherent mechanical properties. Herein, we construct a high-performance graphene-based film via vacuum filtration process by using graphene as matrix and hydroxylated Carbon Nanotube (CNT) as reinforcement agent. The synergistic interaction of hydrogen bonds between CNT and graphene Oxide (GO) and ionic bonds between Fe 2+ on CNT and GO significantly improve the mechanical properties of free-standing and flexible rGO/CNT film. Scanning Electron Microscopic (SEM) imaging and stress transfer mechanism analysis show that the introduction of CNT can hinder the slippage of GO sheets and promote the stress transfer under the continuous loading. The obtained rGO/CNT film shows high toughness of 3 MJ/m 3 , which is 3.6 times higher than that of GO sheets. This facile and scalable strategy can pave the way for the fabrication of high-performance graphene-based film in various applications.

关键词： Fabrication Scanning electron microscopy Filtration Microscopy Graphene Loading Hydrogen

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Parallel Distance: A New Paradigm of Measurement for Parallel Driving

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1169-1178页

作者： Teng Liu Hong Wang Bin Tian Yunfeng Ai Long Chen the Vehicle Intelligence Pioneers Inc. Qingdao 266109 the Department of Automotive Engineering Chongqing UniversityChongqing 400044China the Mechanical and Mechatronics Engineering Department Waterloo UniversityN2L 3G1Canada the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the School of Data and Computer Science Sun Yat-sen UniversityGuangzhou 510006China

In this paper, a new paradigm named parallel distance is presented to measure the data information in parallel driving system. As an example, the core variables in the parallel driving system are measured and evaluated in the parallel distance framework. First, the parallel driving 3.0 system included control and management platform, intelligent vehicle platform and remote-control platform is introduced. Then,Markov chain(MC) is utilized to model the transition probability matrix of control commands in these systems. Furthermore, to distinguish the control variables in artificial and physical driving conditions, different distance calculation methods are enumerated to specify the differences between the virtual and real signals. By doing this, the real system can be guided and the virtual system can be im-proved. Finally, simulation results exhibit the merits and multiple applications of the proposed parallel distance framework.

关键词： Artificial and physical system parallel distance parallel driving 3.0 parallel system rotational and accelerator signal

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An Erasmus+ project: Interactive Course for Control Theory (ICCT)

An Erasmus+ project: Interactive Course for Control Theory (...

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IEEE International Conference on E-Learning in Industrial Electronics, ICELIE

作者： Primož Podržaj Miha Finžgar Zan Pirnar Sandi Ljubic Michele Lanzetta Lorenzo Pollini Pietro Venturini Bertalan Pizag Agnes Urbin Peter Korondi Jozsef Graff Csaba Budai Laboratory for Mechatronics Production Systems and Automation Faculty of Mechanical Engineering University of Ljubljana Ljubljana Slovenia Faculty of Engineering University of Rijeka Rijeka Croatia University of Pisa Pisa Italy Optics and Mechanical Engineering Informatics Faculty of Mechanical Engineering Budapest University of Technology and Economics Budapest Hungary

ISBN: (纸本)9781665414210

The paper presents an overview and the main results of the Erasmus+ project titled Interactive Course for Control Theory - ICCT. The project was started by four European Universities when they identified by a survey that students find Control Theory more challenging to understand compared to other subjects. The project's main goal was to develop a platform, which would offer examples from the field of Control Theory in an interactive way - ICCT. Frequently asked questions (FAQ) and test exam questions were added as well. To support the course, an accompanying textbook was prepared. At this point, the course and the accompanying textbook are available in English and the languages of the partner universities; since both of them are publicly available, we assume they will be offered in other languages in future. The benefits of implementing our interactive course are already visible in better survey results and improved grades in Control Theory-related subjects.

关键词： Industrial electronics Electronic learning Attitude control Conferences Europe Control theory

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An EMG-Based Objective Function for Human-in-the-Loop Optimization

An EMG-Based Objective Function for Human-in-the-Loop Optimi...

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IEEE International Conference on Rehabilitation Robotics (ICORR)

作者： María Alejandra Díaz Sander De Bock Philipp Beckerle Jan Babič Tom Verstraten Kevin De Pauw Human Physiology and Sports Physiotherapy Research Group Brussels Human Robotic Research Center Vrije Universiteit Brussel Brussels Belgium Department of Electrical Engineering and the Department of Artificial Intelligence in Biomedical Engineering Institute of Autonomous Systems and Mechatronics Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Department of Automation Biocybernetics and Robotics Laboratory for Neuromechanics and Biorobotics Jožef Stefan Institute Ljubljana Slovenia Faculty of Electrical Engineering University of Ljubljana Ljubljana Slovenia Robotics and Multibody Mechanics Research Group Vrije Universiteit Brussel and Flanders Make Brussels Belgium

Advancements in wearable robots aim to improve the users' motion, performance, and comfort by optimizing, mainly, energetic cost (EC). However, EC is a noisy measurement with a physiological delayed response that requires long evaluation periods and wearing an uncomfortable mask. This study aims to estimate and minimize an EMG-based objective function that describes the natural energetic expenditure of individuals walking. This objective is assessed by combining multiple electromyography (EMG) variables from the EMG intensity and muscle synergies. To evaluate this objective function simply and repeatedly, we prescribed step frequency (SF) via a metronome and optimized this frequency to minimize muscle activity demands. Further, a linear mixed-effects model was fitted for EC, with the EMG variables as fixed-effects and a random intercept that varies by participant. After the model was fitted to the data, a cubic polynomial was used to identify the optimal SF that reduces the overall EMG-based objective function. Our analysis outlines that the proposed objective function is comparable to the EC during walking, the primary objective function used in human-in-the-loop optimization. Thus, this EMG-based objective function could be potentially used to optimize wearable robots and improve human-robot interaction.

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Evacuation Control of Crowds of Pedestrians: Distributed or Decentralized? ⁎

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IFAC-PapersOnLine 2020年第5期53卷 318-323页

作者： Kecai Cao YangQuan Chen Chenglin Liu Nanjing Institute of Technology Nanjing 211167 China Mechatronics Embedded Systems and Automation Lab School of Engineering University of California Merced CA USA 95343 Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi 214122 China

Evacuation of crowds in a corridor with only one exit has been considered in this paper where distributed controllers have been constructed to regulate the crowd’s evacuation speed so that stampede tragedy can be avoided. Macroscopic model for crowds of pedestrians has been firstly derived based on inspiration of LWR (Lighthill-Whitham and Richards) model and Greenshields model from traffic system where finite volume method has been introduced to simplify the obtained PDEs into finite ODEs. Distributed evacuation controllers have been constructed based on inspiration of multi-agent system and stability analysis of obtained closed-loop system has been simplified to linear system with the delicate controllers proposed. Comparisons between distributed evacuation controllers and previous evacuation controllers have also been presented to show the advantages and disadvantages of different controllers under different initial density of crowds so that tragedy of crowd stampede can be effectively avoided with appropriate selection of different controllers.

关键词： Distributed evacuation controller Decentralized evacuation controller Stampede

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Parallel Planning:A New Motion Planning Framework for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human ***, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies motion planning parallel planning

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Decision-Making in Driver-automation Shared Control:A Review and Perspectives

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1289-1307页

作者： Wenshuo Wang Xiaoxiang Na Dongpu Cao Jianwei Gong Junqiang Xi Yang Xing Fei-Yue Wang IEEE California PATH University of CaliforniaBerkeleyCA 94720 USA Department of Engineering University of CambridgeCambridge CB21PZU.K. Mechanical and Mechatronics Engineering University of WaterlooWaterloo N2L3G1Canada Department of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Research Center for Military Computational Experiments and Parallel Systems TechnologyNational University of Defense TechnologyChangsha 410073China

Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to *** human driver,as an essential agent in the driver-vehicle shared control systems,should be precisely modeled regarding their cognitive processes,control strategies,and decision-making *** interactive strategy design between drivers and automated driving agents brings an excellent challenge for human-centric driver assistance systems due to the inherent characteristics of *** open-ended questions arise,such as what proper role of human drivers should act in a shared control scheme?How to make an intelligent decision capable of balancing the benefits of agents in shared control systems?Due to the advent of these attentions and questions,it is desirable to present a survey on the decision making between human drivers and highly automated vehicles,to understand their architectures,human driver modeling,and interaction strategies under the driver-vehicle shared ***,we give a further discussion on the key future challenges and *** are likely to shape new potential research directions.

关键词： Automated vehicle decision-making human driver human-vehicle interaction shared control

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Rule-Based Energy Management Strategy of Fuel Cell/Ultracapacitor/Battery Vehicles: winner of the IEEE VTS Motor Vehicles Challenge 2020

Rule-Based Energy Management Strategy of Fuel Cell/Ultracapa...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Alessandro Ferrara Christoph Hametner Division of Process Control and Automation TU Wien Institute of Mechanics and Mechatronics Vienna Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

ISBN: (数字)9781728189598

ISBN: (纸本)9781728189604

This paper focuses on the energy management of fuel cell/ultracapacitor/battery hybrid vehicles. A robust rule-based strategy is proposed to effectively reduce hydrogen consumption, increase vehicle lifetime, and handle multiple constraints. This strategy won the IEEE VTS Motor Vehicles Challenge 2020. The formulation of the control rules is heavily based on the vehicle model and the analysis of the assigned cost function. A stochastic generation of driving scenarios is proposed to deal with the limited information provided by the challenge, guarantying a robust design of the energy management strategy. The results are analyzed on a large set of synthetic driving cycles.

关键词： Hydrogen Stochastic processes Fuel cells Supercapacitors Propulsion Batteries Fuels

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Probabilistic Consensus of Multi-agent System under Joint Control of SMC and Minimum Entropy Compensation

Probabilistic Consensus of Multi-agent System under Joint Co...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Xuerou Zhang Jing Wang Jinglin Zhou Yangquan Chen Cunwu Han College of Information Science and Technology Beijing University of Chemical Technology Beijing China Key Laboratory of Beijing for Fieldbus Technology and Automation North China University of Technology Beijing China Mechatronics Embedded Systems and Automation Lab University of California Merced USA

ISBN: (数字)9781728182162

ISBN: (纸本)9781728182179

Due to the stochastic of multi-agent systems, it is difficult to achieve strict consensus. In this paper, consensus in the sense of probability is achieved by reducing the output error entropy of multi-agent system. Sliding mode controller is the core to keep the system stability and probability density function(PDF) compensator is used to reduce the chattering effect of sliding mode and compensate the random part of the system. Radial basis function neural network combined with the minimum entropy criterion is used to model the PDF compensator, and the output error entropy of the system is minimized through the training of weights, so as to optimize the control effect. Finally, the simulation results verify the effectiveness of the method.

关键词： Training Simulation Stochastic processes Probability density function Control systems Entropy Multi-agent systems

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