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IEEE International Conference on automation Science and engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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Infrastructure-dependent ramp-metering control for METANET-s

Infrastructure-dependent ramp-metering control for METANET-s

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IEEE Conference on Decision and control

作者： Ayda Kamalifar Carlo Cenedese Michele Cucuzzella Antonella Ferrara Department of Electrical Computer Science and Biomedical Engineering University of Pavia Pavia Italy Department of Information Technology and Electrical Engineering ETH Zürich Zürich Switzerland Center for Systems and Control ENTEG Faculty of Science and Engineering (FSE) University of Groningen (UG) Nijenborgh 4 Groningen the Netherlands

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we propose a novel infrastructure-dependent ramp-metering control for the recently proposed METANET with service station (METANET-s) model, i.e., a second-order macroscopic traffic model that, compared to the classical METANET, incorporates the dynamics of service stations on highways. We study the effect of a ramp-metering control scheme on a highway stretch with a service station and show that it is capable of actively regulate internal traffic demand attempting to exit the service station via its on-ramp, on top of contributing to decrease the traffic congestion on the mainstream. In fact, the proposed control scheme effectively prevents the backlog of vehicles attempting to merge back onto the mainstream. This dynamic control mechanism is further endowed by a route guidance control strategy increasing the share of vehicles stopping at the service station during main-stream congestion periods, e.g. via incentives. The combined effect of our control schemes allows to take full advantage of the presence of service stations, reducing the overall traffic congestion. Simulation results demonstrate the effectiveness of the proposed control strategies.

关键词： Simulation Merging Numerical models Vehicle dynamics Traffic congestion

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Broadband electrical Impedance Matching of Sandwiched Piezoelectric Ultrasonic Transducers for Structural Health Monitoring of the Rail In-Service

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SSRN 2023年

作者： Yang, Yahui Wei, Xiaoyuan Yao, Wenqing Lan, Jianping Institute of Automotive Engineers Hubei University of Automotive Technology Shiyan442002 China Department of Electrical and Information Engineering Lanzhou University of Technology Lanzhou730050 China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou730050 China Faculty of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China

To achieve high power transmission efficiency and high signal-to-noise ratio of sandwiched piezoelectric ultrasonic transducers (SPUTs) over a wide bandwidth, broadband electrical impedance matching (EIM) is investigated in-depth. Firstly, L type, T type, III type, IV type and V type EIM networks are designed and the corresponding component parameters are determined by the Smith chart with a quality factor Q constraint. Secondly, the above EIM networks are compared by reflection coefficient S11, transducer power gain (TPG) and active power. It is shown that they can effectively improve the TPG, and active power by two times and greatly reduce S11. Then the emitted voltage and received voltage under different excitation frequencies and EIM networks are analyzed. It is shown that the III type network presents optimal performance, which can make the aforementioned voltage values increase by two times over entire frequency range of interest. Finally, the effect of III type and IV type networks on electromechanical characteristics is studied by using the PSpice model of SPUTs. Compared to non-matching, the electro-acoustical gain ratio is improved almost two times, while the electro-acoustical power ratio is greatly reduced. © 2023, The Authors. All rights reserved.

关键词： Ultrasonic transducers

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Design and Analysis of a Knee Exoskeleton with Self-alignment Capability

Design and Analysis of a Knee Exoskeleton with Self-alignmen...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Huijuan Lu Tingting Su Guotao Li Xu Liang Shengda Liu Wendong Xiao Shoulie Xie Jie Zhang Guangping He Department of Mechanical and Electrical Engineering North China University of Technology Beijing China Faculty of Information Technology Beijing University of Technology Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Intelligence Beijing Jiaotong University Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing China Institute for Infocomm Research A*Star Singapore

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

The knee exoskeleton can assist patients for knee rehabilitation exercises. In this paper, a novel knee exoskeleton with self-alignment capability is proposed. First, the structure of the knee exoskeleton is designed, which has one active and four passive joints. The four passive joints are used to realize the self-alignment function of the knee exoskeleton. Second, the kinematic model is established and analysed. Third, simulations are conducted to validate the rotation ranges of human knee and hip joints. The simulation results demonstrate that the knee exoskeleton can meet the rehabilitation needs of the patients.

关键词： Training Mechatronics Simulation Pulleys Machine vision Exoskeletons Kinematics Hip

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Study on spiral winding swimming motion control of a slender legless creature model

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High technology Letters 2021年第4期27卷 415-421页

作者： Lu Zhenli Ma Zhipeng Marko Pencic Maja Cavic Borovac Branislav Roumiana Ilieva Bojan Nemec Marjan Mernik School of Electrical Engineering and Automation Changshu Institute of TechnologyChangshu 215500P.R.China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116P.R.China Faculty of Technical Sciences University of Novi SadNovi Sad 621000Serbia Faculty of Management Technical University of SofiaSofia 1000Bulgaria Department of Automatics Biocybernetics and RoboticsJožef Stefan InstituteLjubljana 1000Slovenia Faculty of Electrical Engineering and Computer Science University of MariborMaribor 462000Slovenia

Through the observation and analysis of the motion trajectory of spiral winding motion for slender legless biological creatures in water,V-REP software is adopted to build a dynamic simulator to study on the mechanism of spiral winding swimming(SWS)*** using the output of spiral function(SF),the dynamic simulation model of slender legless creature(SLC)realizes the SWS motion in *** corresponding experiments under the control of different bending angle of SF to control the dynamic model are also carried out to analyze the water performance of SWS in still *** with the output of two different bending angles of the spiral function,the dynamic model can be used to realize SWS and up/down *** work provides technical reserve and experimental platform for the corresponding study in related fields.

关键词： V-REP spiral winding swimming(SWS) motion control slender legless creature(SLC)

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Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization

Real-time Pricing Mechanism for V2G Using Distributed Bileve...

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IEEE Conference on Decision and control

作者： Jiawei You Xinliang Dai Yuning Jiang Haoyu Yin Yuanming Shi Colin N. Jones School of Information Science and Technology ShanghaiTech University China EPFL Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Automatic Control Laboratory EPFL Switzerland Department of Electrical and Systems Engineering Washington University in St. Louis USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as power consumers and suppliers, coupled with their energy storage capabilities. We propose an advanced real-time pricing model for the electricity market, employing a novel distributed bilevel optimization framework. This framework distinguishes between the distribution system operator (DSO) at the upper level and the EVs at the lower level, each aiming to optimize profit margins. The optimization includes power flow constraints at the upper level to ensure efficient operation within safe system limits, while model predictive control (MPC) is used to optimize lower-level EV responses. Additionally, we provide a rigorous convergence analysis of the proposed bilevel optimization method. Detailed convergence studies and simulation results demonstrate the effectiveness and superiority of the proposed algorithm.

关键词： Vehicle-to-grid Simulation Pricing Prediction algorithms Real-time systems Robustness Convergence Load flow Energy storage Predictive control

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Design and Analysis of Individually Demagnetized Power Converter for Switched Reluctance Motors

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 8439-8449页

作者： Liu, Hemiao Chen, Hao Wang, Xing Gorbounov, Yassen Wheeler, Patrick Anuchin, Alecksey Demidova, Galina Korovkin, Nikolay Liudmila, Sakhno Shenzhen Research Institute China University of Mining and Technology Shenzhen515100 China China University of Mining and Technology School of Electrical Engineering Xuzhou221116 China Xinjiang Institute of Engineering Ürümqi830000 China International Joint Research Center of Central and Eastern European Countries on New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China International Cooperation Joint Laboratory of New Energy Power Generation and Electric Vehicles of Jiangsu Province Colleges and Universities Xuzhou221008 China Xuzhou Key Laboratory of New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China Mining Production University of Mining and Geology "St. Ivan Rilski " Department of Automation Sofia1700 Bulgaria The University of Nottingham Power Electronics Machines and Control Group NottinghamNG7 2RD United Kingdom Electric Drives Department Moscow111250 Russia Saint-Petersburg National Research University of Information Technologies Mechanics and Optics Faculty of Control Systems and Robotics Engineer Saint Petersburg197101 Russia Peter the Great St. Petersburg Polytechnic University Institute of Energy Saint Petersburg195251 Russia

Switched reluctance motors (SRMs) are capable of operating at high speeds and high loads. The large back EMF results in the excitation winding current being demagnetized more slowly, which, in turn, reduces the efficiency and output of the motor system. This study proposes a novel individually demagnetization power converter (IDPC) specifically designed for SRMs to effectively use the demagnetization energy through an independent demagnetization circuit. Compared with traditional converters, the IDPC can accept direct current (dc) and high-frequency ac inputs while achieving fast demagnetization and energy recovery. The topology and working principle of the IDPC are analyzed in detail in this article using a three-phase 12/8 SRM as the research object. In addition, the influence of the winding demagnetization voltage on the negative torque during the demagnetization phase was studied, as well as the functional implementation and logic control strategy of the IDPC. Simulation and experimental results confirm the validity of the proposed topology and high-frequency ac drive characteristics, as well as their advantages in terms of efficiency, output capacity, and dynamic performance. © 2015 IEEE.

关键词： Reluctance motors

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Offline Reinforcement Learning via Sequence Modeling for Vision-Based Robotic Grasping

Offline Reinforcement Learning via Sequence Modeling for Vis...

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IEEE International Conference on Cyber technology in automation, control, and Intelligent Systems

作者： Sheng Zeng Xiao Sun Kang Chen Weibing Huang Yi Chen Dan Chen Zhezhuang Xu Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China Evomotion Co. Ltd. Shenzhen Guangdong China

High cost of environmental interaction and low data efficiency limit the development of reinforcement learning in robotic grasping. This paper proposes an end-to-end robotic grasping method based on offline reinforcement learning via sequence modeling. It considers the most recent n-step history to assist the agent in making decisions, where a predictive model learns to directly predict actions from raw image inputs. The experimental results show that our method can achieve higher grasping success rate with less training data than traditional reinforcement learning algorithms in offline setting.

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear Systems Against Actuator Faults

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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International Symposium on Autonomous Systems (ISAS)

作者： Shanlin Liu Yingwei Zhang Xudong Zhao Hesheng Wang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China Department of Automation 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 Engineering Research Center of IntelligentControl and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent.

关键词： Actuators Backstepping Fault tolerant systems Process control Artificial neural networks control systems Approximation error

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Predicting the State of Crane Spreader for Steel Bar Delivery Based on Machine Learning

Predicting the State of Crane Spreader for Steel Bar Deliver...

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IEEE International Conference on Cyber technology in automation, control, and Intelligent Systems

作者： Zibin Liu Zhezhuang Xu Jian Chen Chen Cui Boyu Chen Qingdong Zhang Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing Education College of Electrical Engineering and Automation Fuzhou University Fuzhou China Sansteel Minguang Co. Ltd Sanming Fujian China

Deducing the twisting pattern of spreader is very important for crane operators in steel warehouse, since crane spreaders have to be rotated repeatedly at steel bar transport sites. To improve the efficiency of the steel bar delivery, the state prediction for crane spreaders is necessary. In order to fulfill this requirement, the HTSK-LN-ReLU model prediction method based on Optuna optimization is applied in this paper. We deploy the IMU on the spreader surface, and then obtain the state data during the operation of the crane spreader by wireless transmission. The data are first denoised through fourier filtering, and then the Optuna framework is used to optimize the HTSK-LN-ReLU model's hyperparameters. The evaluation index of mean square error is used for model evaluation, and finally the optimal hyperparameter combination of the model is selected from 200 comparison experiments. Experimental results demonstrate superior performance of the HTSK-LN-ReLU model in predicting the state of crane spreader for steel bar delivery.

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