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IEEE International Conference on Robotics and automation (ICRA)

作者： Zhen Li Yawen Deng Qiang Ye Weihong Yu Haoxiang Qi Yaliang Liu Zhangguo Yu Gui-Bin Bian School of Electronic and Information Engineering Tongji University Shanghai China Institute of Automation Chinese Academy of Sciences Beijing China School of Mechatronic Engineering Beijing Institute of Technology Beijing China Department of Ophthalmology Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Internal limiting membrane (ILM) peeling is a vital vitreoretinal surgery procedure. However, due to the thickness of just 1-2 micrometers and the intricacies associated with its varying density and adhesion, the difficulty of manipulation exceeds the physiological limits of human perception and operation. Surgical robot is characterized by high precision and stability. However, navigating intricate intraocular environments and handling minuscule high-precision areas remain enormous challenges. These include issues of uneven lighting, field-of-view loss, and motion blur. This paper proposed a perception method named ‘Multimodal Surgical Process Recognition based on Domain Knowledge and Segmentation (MSPR-DKS),’ designed to address these challenges and provide input for the precise control of robots. Moreover, a comprehensive dataset focused on ILM peeling during macular hole surgeries was established. Experimental results underscore the efficacy of this approach, with segmentation accuracies exceeding 99.27% for instruments and macular holes and an average accuracy of 98.97% in recognizing surgical processes. This study paves the way for leveraging domain knowledge and image segmentation to improve robot-assisted manipulation of soft tissues in ophthalmology.

关键词： Image segmentation Visualization Accuracy Medical robotics Motion segmentation Surgery Lighting

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Consensus Analysis of Multi-Agent systems with Uncertain Switching Topology in Finite Frequency Domain 7

Consensus Analysis of Multi-Agent Systems with Uncertain Swi...

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7th International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2020

作者： Xu, Nuo Zhu, Yanzheng Yang, Rongni Chen, Xinkai The College of Mechanical Engineering and Automation Huaqiao University Xiamen361021 China School of Control Science and Engineering Shandong University Jinan Shandong250061 China Shibaura Institute of Technology The Department of Electronic and Information Systems Saitama Japan

ISBN: (纸本)9781728162461

In this paper, the issue of consistency analysis is investigated for a class of multi-agent system (MAS) with time-varying delay and uncertain switching topology in finite frequency domain. The dynamic topology is represented by continuous Markov switching state. The frequency bands of external noise interference are divided into low frequency, medium frequency and high frequency. The noise interference information is fully utilized to guarantee the stability of MAS. At the same time, the affine Bessel-Legendre inequality method is used when carrying out the consistency analysis. The obtained results are represented as the form of linear matrices inequalities. Finally, a series of simulations are illustrated to show the effectiveness and applicability of developed approaches in this paper. © 2020 IEEE.

关键词： Multi agent systems

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Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Gri...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Junyi Zhai Xinliang Dai Yuning Jiang Ying Xue Veit Hagenmeyer Colin N. Jones Xiao-Ping Zhang College of New Energy China University of Petroleum (UPC) China Karlsruhe Institute of Technology (KIT) Institute for Automation and Applied Informatics Germany Automatic Control Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Switzerland School of Electric Power Engineering South China University of Technology (SCUT) China Department of Electronic Electrical and Systems Engineering University of Birmingham (UBir) Birmingham United Kingdom

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses significant challenges in dealing with the resulting optimal power flow (OPF) problem. In this paper, a recently proposed nonconvex distributed optimization algorithm — Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN), is tailored to solve the nonconvex AC/DC OPF problem for emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid systems. The proposed scheme decomposes this AC/DC hybrid OPF problem and handles it in a fully distributed way. Compared to the existing state-of-art Alternating Direction Method of Multipliers (ADMM), which is in general, not applicable for nonconvex problems, ALADIN has a theoretical convergence guarantee. Applying these two approaches to VSC-MTDC coupled with an IEEE benchmark AC power system illustrates that the tailored ALADIN outperforms ADMM in convergence speed and numerical robustness.

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Optimal control for Water Distribution Networks with Unknown Dynamics

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IFAC-PapersOnLine 2020年第2期53卷 6577-6582页

作者： Jorge Val Rafał Wisniewski Carsten S. Kallesøe Department of Electronic Systems Automation and Control Aalborg University 9210 Aalborg Denmark Grundfos A/S Poul Due Jensens Vej Bjerringbro Denmark

Optimal control for Water Distribution Networks (WDN) is subject to complex system models. Typically, detailed models are not available or the implementation is too expensive for small utilities. Reinforcement Learning (RL) methods are well known techniques for model-free control. This paper proposes a model-free controller for WDNs based on RL methods and presents experimental evidence of the practicality of the design.

关键词： Water Distribution Networks Level control Reinforcement Learning

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Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

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IEEE Transactions on Evolutionary Computation 2024年

作者： Diao, Yiya Li, Changhe Zeng, Sanyou Yang, Shengxiang Coello, Carlos A. Coello China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Anhui University of Sciences and Technology School of Artificial Intelligence Hefei China China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan China De Montfort University School of Computer Science and Informatics LeicesterLE1 9BH United Kingdom Department of Computer Science CINVESTAV-IPN 07360 Mexico Tecnologico de Monterrey Faculty of Excellence The School of Engineering and Sciences N.L. Monterrey Mexico

Fitness landscape analysis (FLA) is quite important in evolutionary computation. In this paper, we propose a novel FLA method, the nearest-better network (NBN), which uses the nearest-better relationship to simplify the original fitness landscape of continuous optimization problems. We introduce an efficient algorithm to calculate NBN for continuous problems. We also propose four numerical measurements and a 3D visualization method based on NBN. Experiments show that compared to the other main FLA methods, the four numerical measurements proposed here can effectively measure the four intended features: neutrality, ruggedness, modality, and basin of attraction, respectively, and common features of the fitness landscape can be maintained in 3D NBN visualization, regardless of the scale of the problem. NBN also provides a view of how algorithms search in high-dimensional problems with the help of the 3D NBN visualization. © 1997-2012 IEEE.

关键词： Optimization algorithms

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Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

arXiv

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arXiv 2022年

作者： Zhai, Junyi Dai, Xinliang Jiang, Yuning Xue, Ying Hagenmeyer, Veit Jones, Colin N. Zhang, Xiao-Ping Qingdao China City & Energy Research Institute Suzhou China Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Automatic Control Laboratory EPFL Switzerland School of Electric Power Engineering South China University of Technology Guangzhou China Department of Electronic Electrical and Systems Engineering University of Birmingham Birmingham United Kingdom

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses significant challenges in dealing with the resulting optimal power flow (OPF) problem. In this paper, a recently proposed nonconvex distributed optimization algorithm—Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN), is tailored to solve the nonconvex AC/DC OPF problem for emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid systems. The proposed scheme decomposes this AC/DC hybrid OPF problem and handles it in a fully distributed way. Compared to the existing state-of-art Alternating Direction Method of Multipliers (ADMM), which is in general, not applicable for nonconvex problems, ALADIN has a theoretical convergence guarantee. Applying these two approaches to VSC-MTDC coupled with an IEEE benchmark AC power system illustrates that the tailored ALADIN outperforms ADMM in convergence speed and numerical robustness. Copyright © 2022, The Authors. All rights reserved.

关键词： Constrained optimization

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Dual Role of Pulmonary Surfactant Corona in Modulating Carbon Nanotube Toxicity and Benzo[A]Pyrene Bioaccessibility

SSRN

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SSRN 2023年

作者： Luo, Zhen Xu, Dongfang Xu, Yan Zhao, Jian Hu, Guoqing Yue, Tongtao Department of Engineering Mechanics State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Institute of Coastal Environmental Pollution Control Key Laboratory of Marine Environment and Ecology Ministry of Education Frontiers Science Center for Deep Ocean Multispheres and Earth System Ocean University of China Qingdao266100 China College of Electronic Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

Inhaled carbon nanotubes (CNTs) can deposit in the deep lung, where they interact with pulmonary surfactant (PS) to form coronas, potentially altering the fate and toxicity profile of CNTs. However, the presence of other contaminants in combination with CNTs may affect these interactions. In this study, we investigated the effects of coexisting contaminants, specifically benzo[a]pyrene (BaP), on the interaction between CNTs and PS. We used passive dosing and fluorescence-based techniques to demonstrate that PS increases the solubility of BaP pre-adsorbed on CNTs. Subsequently, molecular dynamics simulations were performed to gain insight into the intricate interactions between CNTs, BaP, and PS. Our results suggest that the PS corona plays a dual role in modulating the toxicity of CNTs. First, it mitigates toxicity by reducing the hydrophobicity and apparent aspect ratio of CNTs. Second, it exacerbates toxicity due to energetically dominant PS-BaP interactions, which increase the solubility and thus bioaccessibility of BaPs. Importantly, these interactions are strongly influenced by the size and aggregation state of the CNTs. Our findings highlight the need to consider the bioaccessibility of coexisting contaminants when assessing the inhalation toxicity of PS-modified CNTs. © 2023, The Authors. All rights reserved.

关键词： Toxicity

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The Combination of Two control Strategies for Series Hybrid Electric Vehicles

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IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 596-608页

作者： Can Luo Zhen Shen Simos Evangelou Gang Xiong Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Cloud Computing Center Chinese Academy of Sciences IEEE Department of Electrical and Electronic Engineering Imperial College London Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries

With most countries paying attention to the environment protection, hybrid electric vehicles have become a focus of automobile research and development due to the characteristics of energy saving and low emission. Power follower control strategy(PFCS) and DC-link voltage control strategy are two sorts of control strategies for series hybrid electric vehicles(HEVs). Combining those two control strategies is a new idea for control strategy of series hybrid electric vehicles. By tuning essential parameters which are the defined constants under DClink voltage control and under PFCS, the points of minimum mass of equivalent fuel consumption(EFC) corresponding to a series of variables are marked for worldwide harmonized light vehicles test procedure(WLTP). The fuel economy of series HEVs with the combination control schemes performs better compared with individual control scheme. The results show the effects of the combination control schemes for series HEVs driving in an urban environment.

关键词： DC-Link voltage control power follower control strategy series hybrid electric vehicles tuning

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Collaborative Learning of High-Precision Quantum control and Tomography

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Physical Review Applied 2021年第1期16卷 014056-014056页

作者： Hai-Jin Ding Bing Chu Bo Qi Re-Bing Wu Department of Automation Tsinghua University Beijing 100084 People’s Republic of China School of Electronic and Computer Science University of Southampton SO17 1BJ United Kingdom Key Laboratory of Systems and Control ISS and National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science CAS Beijing 100190 People’s Republic of China

In the hardware implementation of quantum computation, the control pulses for quantum states and gate operations must be calibrated to correct errors induced by unknown drifts of system parameters. The calibration can be iteratively done by checking the control precision, but the required randomized benchmarking or quantum tomography is experimentally expensive. In this paper, we propose that the control calibration and the quantum tomography can be taken as two separate but collaborative learning processes. Combining the gradient-descent pulse engineering and the adaptive tomography, the resulting c-GRAPE algorithm can substantially reduce the high cost of measurements without sacrificing the control accuracy. The effectiveness is demonstrated by numerical simulation examples.

关键词： Machine learning Quantum control Quantum tomography

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Innovative Competency-Based Electrical Engineering Curriculum

Innovative Competency-Based Electrical Engineering Curriculu...

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Frontiers in Education (FIE) Conference

作者： Gustavo P. Rehder Ariana L. C. Serrano José B. Grimoni Anarosa A. F. Brandão Magno M. T. Silva Henrique T. Moriya Cristiano M. Panazio Edson Barbero Marco I. Alayo Irineu G. N. Gianesi Antonio C. Seabra Electronic Systems Department of the Escola Politécnica Universidade de São Paulo São Paulo Brazil Electric Automation and Energy Dept. of the Escola Politécnica Universidade de São Paulo São Paulo Brazil Computer Engineering and Digital Systems Department of the Escola Politécnica Universidade de São Paulo São Paulo Brazil Telecommunications and Control Dept. of the Escola Politécnica Universidade de São Paulo São Paulo Brazil Professional Master's in Administration - Á lvares Penteado School of Commerce Foundation São Paulo Brazil Instituto Mauá de Tecnologia São Paulo Brazil

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

The Electrical Engineering undergraduate program of the Escola Politécnica of the Universidade de São Paulo has created an alternative innovative curriculum path for its freshmen students in 2024. The Competency-based Path emphasizes the development of competencies and skills for the unprecedented technological advancements that necessitate a holistic education for future electrical engineers, preparing them with practical skills for real-world challenges. The program was designed using an innovative methodology and centers around semester-long or year-long integrative projects. These projects bridge the gap between theory and practice, as students deal with real-world challenges while fostering social responsibility.

关键词： Electrical engineering Education

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