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IEEE Transactions on Intelligent Vehicles 2024年第8期9卷 5250-5254页

作者： Hailong Huang Jiangcheng Su Fei-Yue Wang Department of Aeronautical and Aviation Engineering Hong Kong Polytechnic University Hong Kong China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Many megacities, such as London, New York, Paris, Tokyo, Beijing, and Shanghai, have been born due to urban- ization. While citizens enjoy the convenience of city life, such cities suffer from drawbacks of transportation: the average commute time has been increasing over the past years. With the maturity of electric vertical take-off and landing (eVTOL) aircraft technology, decision-makers have started to look upward to the low-altitude airspace. This blue space has the potential to reshape the transportation system and shorten the average travel time in daily life. To explore this emerging area, we held a Distributed/Decentralized Hybrid Workshop on Sustain- ability for Transportation and Logistics (DHW-STL), and this letter summarizes the outcomes of our discussion. Here, we first pinpoint the pain issues of conventional transportation. Then, we present the emerging low-altitude airspace transportation option, followed by a discussion on how such a new transportation option can integrate with the conventional ground-based transportation system. Some thoughts about the pathway to further development of the integrated transportation system are shared finally.

关键词： Aircraft Transportation Urban areas Air traffic control Traffic congestion Meters Aircraft propulsion Motors Logistics Indexes

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Multiple linear regression of metro ridership in the context of football events: a case study of Metro de Lisboa

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Transportation Research Procedia 2025年 86卷 151-158页

作者： Paulo Fernandes Luis Santos Jorge M. Bandeira Eloisa Macedo Department of Mechanical Engineering/Centre for Mechanical Technology and Automation (TEMA) University of Aveiro Campus Universitário de Santiago 3810-193 Aveiro Portugal LASI – Intelligent Systems Associate Laboratory Portugal

Special events, such as sports games, concerts, and festivals, pose significant challenges for efficient operational management, leading to disruptions in public transport systems, particularly urban metros. While existing studies have focused on predicting metro passenger flows during sport events based on weather or opponent type variables, little is known about the impacts of competition type, team form, position in the competition, or game results on both game attendance and metro demand. This study examined inbound and outbound passenger flows at the station-level in the Lisbon metro during football games. The database comprised 186 events spanning from 2017 to 2022, including 15-minute mobility data from three metro stations serving two stadiums in the city. Multiple linear regression (MLR) was applied to estimate attendance games. Results revealed statistical differences in game attendance based on competition and opponent types, as well as team situation in the competition. Also, there was an increase in metro demand up to 3,600 passengers on event days compared to non-event days. The MLR models incorporating all the variables retained significantly more data information than other model variants for both teams. Some significant attendance model predictors were related to opponent and competition types, and team’s situation before the games.

关键词： Metro systems Predicting Passengers Flows Football Events Multiple Linear regression

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Online Residual Learning from Offline Experts for Pedestrian Tracking

arXiv

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arXiv 2024年

作者： Vlachos, Anastasios Tsiamis, Anastasios Karapetyan, Aren Balta, Efe C. Lygeros, John The Automatic Control Laboratory Department of Information Technology and Electrical Engineering ETH Zürich Zürich8092 Switzerland THe Control and Automation Group Inspire AG Zürich8005 Switzerland The Automatic Control Laboratory Switzerland

In this paper, we consider the problem of predicting unknown targets from data. We propose Online Residual Learning (ORL), a method that combines online adaptation with offline-trained predictions. At a lower level, we employ multiple offline predictions generated before or at the beginning of the prediction horizon. We augment every offline prediction by learning their respective residual error concerning the true target state online, using the recursive least squares algorithm. At a higher level, we treat the augmented lower-level predictors as experts, adopting the Prediction with Expert Advice framework. We utilize an adaptive softmax weighting scheme to form an aggregate prediction and provide guarantees for ORL in terms of regret. We employ ORL to boost performance in the setting of online pedestrian trajectory prediction. Based on data from the Stanford Drone Dataset, we show that ORL can demonstrate best-of-both-worlds performance. © 2024, CC BY.

关键词： Prediction models

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Effect of Positive Temperature Coefficient Materials on the AC Breakdown Strength and Dielectric Properties of Epoxy Composites 4th

Effect of Positive Temperature Coefficient Materials on the ...

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4th International Symposium on Insulation and Discharge Computation for Power Equipment, IDCOMPU 2023

作者： Teng, Chenyuan Li, Shuo Zhou, Yuanxiang Zhang, Ling Zhang, Yunxiao Huang, Meng College of Information Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819974122

In operation, the negative temperature coefficient (NTC) electrical resistivity characteristics of polymeric insulating materials causes DC electric field distortion within power equipment insulation and lead to the failure. The doping of positive temperature coefficient (PTC) ceramic particles can suppress the NTC characteristics of the composites, but the electrical properties under AC voltages are unrevealed. In this paper, epoxy composites (0–20 wt%) doped with polydopamine-coated PTC particles were prepared, whose AC breakdown strength and dielectric properties were tested. The results shows that the decrease of AC dielectric strength is smaller than that under DC voltages after the doping PTC particles, and the coating of polydopamine can enhance the AC dielectric strength. As the doping content increases, the dielectric constant and tanδ of the epoxy composites increases, and the maximum increase of dielectric loss power is about 2% of the loss power caused by the current-carrying conductor. The research provides a theoretical basis for the optimization of the insulating performance of the equipment under the AC-DC composite voltages. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Epoxy resins

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A Reinforcement Learning Approach for Robust Restoration of Generators in Power System

A Reinforcement Learning Approach for Robust Restoration of ...

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2022 Chinese automation Congress, CAC 2022

作者： Li, Huimiao Yang, Xiaozhou Zhai, Chao Hubei Key Laboratory of Advanced Control and Intelligent Automation Fo Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Future Resilient Systems Singapore-ETH Centre Create Campus Singapore

ISBN: (纸本)9781665465335

In the past decades, cascading blackouts have caused serious damages to power systems and affected the normal operation of society, so it is crucial to quickly restore the damaged power system to normal state. In this paper, a reinforcement learning (RL) approach is developed to achieve the robust restoration of generators in power systems. Firstly, the performance recovery of damaged power system is modeled as markov decision process, and constraints such as line voltage and active power output of generators are considered. Secondly, a RL algorithm is proposed to search the optimal control strategy for generator units recovery. Based on the proposed restoration approach, Q-learning algorithm is employed to obtain the optimal strategy for power supply of generaors in power grids. Finally, numerical simulations are carried out on IEEE 9-bus system under different scenarios of external disturbances and certainties. The simulation results demonstrate the effectiveness and feasibility of the proposed approach. © 2022 IEEE.

关键词： Reinforcement learning

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Utilization of Energy Storage and Hydrogen in Power and Energy systems:Viewpoints from Five Aspects

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CSEE Journal of Power and Energy systems 2023年第1期9卷 1-7页

作者： Yonghua Song Mohammad Shahidehpour Saifur Rahman Nigel Brandon Kai Strunz Jin Lin Yuxuan Zhao State Key Laboratory of Internet of Things for Smart City University of MacaoTaipaMacao 999078China Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Galvin Center for Electricity Innovation Illinois Institute of TechnologyChicagoIL 60616USA Department of Advanced Research Institute Virginia Polytechnic Institute and State UniversityArlingtonVA 22203USA Department of Earth Science and Engineering Imperial College LondonLondon SW72AZU.K Department of Sustainable Electric Networks and Sources of Energy Technische Universitt Berlin10587 BerlinGermany State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Decarbonizing power systems is crucial to mitigating climate change impacts and achieving carbon *** renewable energy supply can reduce greenhouse gas emissions and accelerate the decarbonization ***,renewable energy sources(RESs)such as wind and solar power are characterized by intermittency and often non-dispatchability,significantly challenging their high-level integration into power *** storage is acknowledged as a vital indispensable solution for mitigating the intermittency of renewables such as wind and solar power and boosting the penetrations of *** the CSEE JPES Forum,five well-known experts were invited to give keynote speeches,and the participating experts and scholars had comprehensive exchanges and discussions on energy storage ***,the views on the design,control,performance,and applications of new energy storage technologies,such as the fuel cell vehicle,water electrolysis,and flow battery,in the coordination and operation of power and energy systems were *** experts also provided experience that could be used to develop energy storage for constructing and decarbonizing new power systems.

关键词： Electrolysis electric vehicle energy storage flow battery fuel cell electric vehicle hydrogen energy

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Attitude Takeover control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning

arXiv

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arXiv 2023年

作者： Liu, Yuhan Wang, Pengyu Lee, Chang-Hun Tóth, Roland The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands The Flight Dynamics and Control Laboratory Department of Aerospace Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of The Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

One major challenge for autonomous attitude takeover control for on-orbit servicing of spacecraft is that an accurate dynamic motion model of the combined vehicles is highly nonlinear, complex and often costly to identify online, which makes traditional model-based control impractical for this task. To address this issue, a recursive online sparse Gaussian Process (GP)-based learning strategy for attitude takeover control of noncooperative targets with maneuverability is proposed, where the unknown dynamics are online compensated based on the learnt GP model in a semi-feedforward manner. The method enables the continuous use of on-orbit data to successively improve the learnt model during online operation and has reduced computational load compared to standard GP regression. Next to the GP-based feedforward, a feedback controller is proposed that varies its gains based on the predicted model confidence, ensuring robustness of the overall scheme. Moreover, rigorous theoretical proofs of Lyapunov stability and boundedness guarantees of the proposed method-driven closed-loop system are provided in the probabilistic sense. A simulation study based on a high-fidelity simulator is used to show the effectiveness of the proposed strategy and demonstrate its high performance. © 2023, CC BY-NC-SA.

关键词： Maneuverability

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Correlating driving behavior with safety performance: from the heart to the pedals with a driving simulator

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Transportation Research Procedia 2023年 69卷 217-224页

作者： Diogo Reis Ricardo Tomás Margarida C. Coelho Eloisa Macedo University of Aveiro Department of Mechanical Engineering / Centre for Mechanical Technology and Automation 3810-193 Aveiro Portugal LASI - Intelligent Systems Associate Laboratory Portugal

Driving behavior significantly affects road safety, pollutant emissions, and fuel consumption, and an in-depth analysis is crucial for any accurate evaluation of a transport system. To develop a comprehensive study, it is important to consider different variables and traffic conditions, the presence of vulnerable road users, road singularities, as well as driving behavior profiles (e.g., gear-shift strategy, acceleration style). In this research, fixed-based driving simulation tests were carried out to allow a global evaluation of driving behavior under two different traffic conditions (urban and highway). The main objective is to understand driver-road interaction and associated impacts in terms of the adopted gear-shift strategy, vehicle dynamics profile, driving volatility profile (a safety-related indicator), driver's heart rate monitoring (a driving comfort-related variable), and pollutant emissions modeling. Drivers’ performance was assessed for each case study and a database was created for different segment types and considering different drivers, using statistical data mining models. This work is relevant for a better understanding of driving behavior both from the viewpoint of policymaking as well as for driver awareness about the relative impact associated with his/her driving behavior.

关键词： driving behavior simulator safety performance VSP

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A long prediction horizon fcs-mpc algorithm with disturbance preview for three-phase inverters

A long prediction horizon fcs-mpc algorithm with disturbance...

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2023 Jiangsu Annual Conference on automation, JACA 2023

作者： He, Xianghui Huang, Saijin Li, Guanjun Li, Haoyuan Wang, Xiangyu School of Automation Southeast University No. 2 Si Pai Lou Nanjing Jiangsu210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China Jiangsu Engineering Technology Research Center for Energy Storage Conversion Application China Electric Power Research Institute Nanjing Jiangsu210003 China

ISBN: (纸本)9781839539848

This paper derives an efficient control algorithm to deal with the output voltage tracking control problem of threephase inverters with multiple disturbances (including parametric perturbations of filter, abrupt disturbances caused by load switching and harmonic disturbances brought by unbalanced loads and nonlinear loads). This accomplishment is realized through the long prediction horizon finite-control-set model predictive control (FCS-MPC) and the integration of a composite disturbance observer (CDO) and a disturbance preview model into the sphere decoding algorithm (SDA). This integration facilitates the estimation and prediction of future disturbance behaviors within the inverter system, which addresses the poor disturbance-rejection limitations inherent in conventional SDA approaches employed in previous studies. The algorithm also improves the dynamic performances of the output voltage. Simulations studies are illustrated to demonstrate the feasibility and effectiveness of the proposed control algorithm. Based on the presented results, the algorithm achieves good disturbance rejection capability and maintains small tracking error. © The Institution of engineering & technology 2023.

关键词： Disturbance rejection

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A method based on rotated object detection to detect defects regarding distance in strain clamps 3

A method based on rotated object detection to detect defects...

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2022 3rd International Conference on Electrical technology and Automatic control, ICETAC 2022

作者： Du, Qiliang Zhou, Huangze Qu, Fengrui Tian, Lianfang School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou China Sino-Singapore International Joint Research Institute Guangdong Guangzhou China Key Laboratory of Autonomous Systems and Network Control of Ministry of Education China Research Institute of Modern Industrial Innovation South China University of Technology Guangdong Guangzhou China

Strain clamps in the transmission line have a vital role. With X-ray inspection in the transmission line, X-ray images to check defects of the tensioning line clip method have already become the mainstream method. In this paper, we concentrate on the strain clamps' steel anchor end and strand distance defects. We propose a method based on the rotated object detection model RoI Transformer with KFIoU loss to extract the diameter of the steel anchor tube as a reference to determine whether the distance is too long. We first obtain the rotated bounding boxes of the steel anchor and the strand, then calculate the distance between the steel anchor end and the strand and the diameter of the steel anchor by rotated bounding boxes, and finally determine whether there is a defect. Through the study of this essay, the defect detection of strain clamps realizes with high accuracy which has an essential reference for the quality inspection of tension clamp crimping in engineering applications. © Published under licence by IOP Publishing Ltd.

关键词： Defects

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