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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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A Graph-Based Self-Calibration Technique for Cable-Driven Robots with Sagging Cable

A Graph-Based Self-Calibration Technique for Cable-Driven Ro...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： M. R. Dindarloo A. S. Mirjalili S. A. Khalilpour R. Khorrambakht Stephan Weiss H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Tandon School of Engineering Control/Robotics Research Laboratory New York University Brooklyn NY Department of Smart Systems Technologies University of Klagenfurt Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

关键词： Meters Accuracy Perturbation methods Kinematics Robot sensing systems End effectors Software Calibration Sensors Finite element analysis

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Anisotropy of two-dimensional ReS_(2)and advances in its device application

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Rare Metals 2021年第12期40卷 3357-3374页

作者： Ya-Di Cao Ying-Hui Sun Su-Fei Shi Rong-Ming Wang Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface ScienceSchool of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing100083China Department of Chemical and Biological Engineering Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic InstituteTroyNY 12180USA

Two-dimensional(2D)transition metal dichalcogenides(TMDCs)have attracted growing interest regarding their potential applications in next-generation electronic and optoelectronic *** to their atomic thickness and tunable bandgap,they exhibit unique mechanical,electrical,and optical *** a specific member of the TMDC family,rhenium disulfide(ReS_(2))has stimulated intensive interest due to its anisotropic crystal structure,weak inter-layer coupling,and anisotropic electrical and optical *** this review,we summarize the distinct crystal structure and intrinsic anisotropic properties of ReS_(2),followed by an introduction to its synthesis *** current applications of ReS_(2)and its heterojunctions are presented based on its anisotropic *** review not only provides a timely summary of the current applications of ReS_(2)and its heterojunctions,but also inspires new approaches to develop other innovative devices based on 2D materials with a low lattice symmetry.

关键词： Transition metal dichalcogenides(TMDCs) Rhenium disulfide Anisotropic property Heterojunction Functional device

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Reliability Assessment of Solder Ball Joints Using Finite Element Analysis and Machine Learning techniques

Reliability Assessment of Solder Ball Joints Using Finite El...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： H. Reddad M. Zemzami N. El Hami N. Hmina N-Q. Nguyen Advanced Systems Engineering Laboratory ENSA Ibn Tofail University Kenitra Morocco ENSAM Mohamed V University Rabat Morocco Science and Engineering Laboratory ENSA University Ibn Tofail Kenitra Morocco Chaire Connected Innovation Computer Sciences and Digital Society Laboratory Universite de Technologie de Troyes Troyes Cedex France

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper presents a comprehensive approach for reliability assessment and optimization of ball joints by combining finite element analysis (FEA) method with machine learning algorithms, in particular by exploiting the power of the XGBoost machine learning algorithm. FEA simulations were carried out using ANSYS to generate a dataset encompassing various solder joint geometrical parameters configurations. Key input parameters, including geometric dimensions, were identified by sensitivity analysis and used as features for training the XGBoost model. The trained model demonstrated solid performance. Feature importance analysis revealed critical factors influencing solder joint reliability and provided insights for optimization strategies. This research provides practical recommendations for optimizing solder joint and material design to improve reliability and performance in electronic packaging applications.

关键词： Training Support vector machines Machine learning algorithms Reliability engineering Fatigue Finite element analysis Reliability Copper Soldering Electronics packaging

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P-11.13: Organic-Perovskite Bilayer Color Conversion Media for Full-Color Displays

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SID Symposium Digest of Technical Papers 2024年第S1期55卷 1329-1331页

作者： Siyang Liu Bryan Siu Ting Tam Mingchao Zhu Fanghao Ye Fion Sze Yan Yeung Guijun Li Shou-Cheng Dong State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen University Shenzhen China Institute for Advanced Study Hong Kong University of Science and Technology Kowloon Hong Kong WISPO Advanced Materials (Suzhou) Co. Ltd. Suzhou China

Color conversion media (CCM) are crucial for realizing cost-effective, high-resolution micro-LED and OLED displays. In this work, we developed green and red organic-perovskite bilayer CCM that combine the PLQY and color purity of perovskite quantum dots (PeQDs) and the strong blue absorption of perylene-based organic emitters. The bilayer with thickness of 300 nm showed over 99% blue absorption and PLQY of 77% and 61% for green and red CCM, respectively.

关键词： Color conversion perovskites organic emitters OLEDs micro-LEDs

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Multidimensional Voronoi Constellations vs. Short Blocklength Probabilistic Shaping: A Comparison for Multilevel Coding Approach

Multidimensional Voronoi Constellations vs. Short Blocklengt...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Yajie Sheng Bin Chen Yi Lei Jingxin Deng Jiwei Xu Mengfan Fu Qunbi Zhuge Shen Li Department of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Electronic Engineering State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China Department of Electrical and Computer Engineering Centre of Optics Photonics and Lasers (COPL) Université Laval Québec Canada

Performance of concatenated multilevel coding with probabilistic shaping (PS) and Voronoi constellations (VCs) is analysed over AWGN channel. Numerical results show that VCs provide up to 1.3 dB SNR gains over PS-QAM ... 详细信息

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

关键词： AWGN channels Wireless communication Optical fibers Probabilistic logic Optical fiber communication Encoding Complexity theory Gain Photonics Signal to noise ratio

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Efficient and high precision target-driven fluid simulation based on spatial geometry features

Efficient and high precision target-driven fluid simulation ...

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作者： Zhou, Xiangyang Liu, Sinuo Zeng, Haokai Wang, Xiaokun Ban, Xiaojuan Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems University of Science and Technology Beijing Beijing China School of Computer Science Peking University Beijing China National Centrefor Computer Animation Bournemouth University Poole United Kingdom Institute of Materials Intelligent Technology Liaoning Academy of Materials Shenyang China

We proposed a novel target-driven fluid simulation method based on the weighted control model derived from the spatial geometric features of the target shape. First, the spatial geometric characteristics of the target model are taken into account to set the color field weights of control particles. This enabled the full expression of geometric characteristics of the target model, and improve the shape accuracy of controlled fluid. Then, the fluid is controlled to form the target shape under driving constraints, wherein we proposed a new adaptive constraint mechanism that enables efficient target shape generation. Finally, a new density constraint between the control particles and the controlled fluid particles is proposed to ensure the incompressibility of fluid during control. Compared to the state-of-the-art target-driven fluid control methods, our method achieves higher precision fluid control with higher efficiency. © 2023 John Wiley & Sons Ltd.

关键词： Hydrodynamics

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Enhancing Fault Diagnosis of Uncertain Grid-Connected Photovoltaic systems using Deep GRU-based Bayesian optimization

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IFAC-PapersOnLine 2024年第4期58卷 449-454页

作者： Zahra Yahyaoui Mansour Hajji Majdi Mansouri Abdelmalek Kouadri Kais Bouzrara Hazem Nounou Research Unit Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine 1200 Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Signals and Systems Laboratory Institute of Electrical and Electronics Engineering University M Hamed Bougara of Boumerdes Boumerdes Algeria Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir Tunisia

The efficacy of photovoltaic systems is significantly impacted by electrical production losses attributed to faults. Ensuring the rapid and cost-effective restoration of system efficiency necessitates robust fault detection and diagnosis (FDD) procedures. This study introduces a novel interval-gated recurrent unit (I-GRU) based Bayesian optimization framework for FDD in grid-connected photovoltaic (GCPV) systems. The utilization of an interval-valued representation is proposed to address uncertainties inherent in the systems, the GRU is employed for fault classification, while the Bayesian algorithm optimizes its hyperparameters. Addressing uncertainties through the proposed approach enhances monitoring capabilities, mitigating computational and storage costs associated with sensor uncertainties. The effectiveness of the proposed approach for FDD in GCPV systems is demonstrated using experimental application.

关键词： Bayesian optimization fault detection fault diagnosis gated recurrent units grid-connected PV systems interval-data representation uncertainties

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Peridynamic-based modeling of elastoplasticity and fracture dynamics

Peridynamic-based modeling of elastoplasticity and fracture ...

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作者： Wang, Haoping Wang, Xiaokun Xu, Yanrui Zhang, Yalan Yao, Chao Guo, Yu Ban, Xiaojuan School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Faculty of Science and Engineering University of Groningen Groningen Netherlands School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Beijing Advanced Innovation Center for Materials Genome Engineering School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing China Institute of Materials Intelligent Technology Liaoning Academy of Materials Shenyang China

This paper introduces a particle-based framework for simulating the behavior of elastoplastic materials and the formation of fractures, grounded in Peridynamic theory. Traditional approaches, such as the Finite Element Method (FEM) and Smoothed Particle Hydrodynamics (SPH), to modeling elastic materials have primarily relied on discretization techniques and continuous constitutive model. However, accurately capturing fracture and crack development in elastoplastic materials poses significant challenges for these conventional models. Our approach integrates a Peridynamic-based elastic model with a density constraint, enhancing stability and realism. We adopt the Von Mises yield criterion and a bond stretch criterion to simulate plastic deformation and fracture formation, respectively. The proposed method stabilizes the elastic model through a density-based position constraint, while plasticity is modeled using the Von Mises yield criterion within the bond of particle paris. Fracturing and the generation of fine fragments are facilitated by the fracture criterion and the application of complementarity operations to the inter-particle connections. Our experimental results demonstrate the efficacy of our framework in realistically depicting a wide range of material behaviors, including elasticity, plasticity, and fracturing, across various scenarios. © 2024 John Wiley & Sons Ltd.

关键词： Elastoplasticity

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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