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arXiv 2023年

作者： van der Ploeg, Chris Nyberg, Truls Sánchez, José Manuel Gaspar Silvas, Emilia van de Wouw, Nathan Netherlands Organisation for Applied Scientific Research Integrated Vehicle Safety Group Helmond5700 AT Netherlands Eindhoven University of Technology Dynamics and Control Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands Eindhoven University of Technology Control Systems Technology Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands KTH Royal Institute of Technology Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science Stockholm100 44 Sweden Scania CV AB Södertälje151 87 Sweden

As vehicle automation advances, motion planning algorithms face escalating challenges in achieving safe and efficient navigation. Existing Advanced Driver Assistance systems (ADAS) primarily focus on basic tasks, leaving unexpected scenarios for human intervention, which can be error-prone. Motion planning approaches for higher levels of automation in the state-of-the-art are primarily oriented toward the use of risk- or anti-collision constraints, using over-approximates of the shapes and sizes of other road users to prevent collisions. These methods however suffer from conservative behavior and the risk of infeasibility in high-risk initial conditions. In contrast, our work introduces a novel multi-objective trajectory generation approach. We propose an innovative method for constructing risk fields that accommodates diverse entity shapes and sizes, which allows us to also account for the presence of potentially occluded objects. This methodology is integrated into an occlusion-aware trajectory generator, enabling dynamic and safe maneuvering through intricate environments while anticipating (potentially hidden) road users and traveling along the infrastructure toward a specific goal. Through theoretical underpinnings and simulations, we validate the effectiveness of our approach. This paper bridges crucial gaps in motion planning for automated vehicles, offering a pathway toward safer and more adaptable autonomous navigation in complex urban contexts. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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HOW LEARNING control SUPPORTS INDUSTRY 4.0 IN SEMICONDUCTOR MANUFACTURING 6

HOW LEARNING CONTROL SUPPORTS INDUSTRY 4.0 IN SEMICONDUCTOR ...

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6th ASPE Spring Topical Meeting on Design and control of Precision Mechatronic systems

作者： Veen, Gijs Van Der Stokkermans, Joep Mooren, Noud Oomen, Tom Equipment & Automation Technologies Nexperia Nijmegen Netherlands Department Of Mechanical Engineering Control Systems Technology Group Eindhoven University Of Technology Eindhoven Netherlands

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Frequency response data based LPV controller synthesis applied to a control moment gyroscope

arXiv

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arXiv 2021年

作者： Bloemers, Tom Tóth, Roland Oomen, Tom The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Control Systems Technology Department of Mechanical Engineering Eindhoven University of Technology The Systems and Control Laboratory Institute for Computer Science and Control Kende u. 13-17 BudapestH-1111 Hungary

control of systems with operating condition-dependent dynamics, including control moment gyroscopes, often requires operating condition-dependent controllers to achieve high control performance. The aim of this paper is to develop a frequency response data-driven linear parameter-varying control design approach for single-input single-output systems, which allows improved performance for a control moment gyroscope. A stability theory using closed-loop frequency response function data is developed, which is subsequently used in a synthesis procedure that guarantees local stability and performance. Experimental results on a control moment gyroscope demonstrate the performance improvements. Copyright © 2021, The Authors. All rights reserved.

关键词： controllers

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Data-driven feedback linearisation using model predictive control

arXiv

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arXiv 2022年

作者： Floren, Merijn Classens, Koen Oomen, Tom Noël, Jean-Philippe nic System Dynamics Division Celestijnenlaan 300 Leuven3001 Belgium Eindhoven University of Technology Department of Mechanical Engineering Control Systems Technology Group PO Box 513 MB Eindhoven5600 Netherlands

Linearising the dynamics of nonlinear mechanical systems is an important and open research area. In this paper, we adopt a data-driven and feedback control approach to tackle this problem. A model predictive control architecture is developed that builds upon data-driven dynamic models obtained using nonlinear system identification. The overall methodology shows a high degree of performance combined with significant robustness against imperfect modelling and extrapolation. These findings are demonstrated using large set of synthetic experiments conducted on a asymmetric Duffing oscillator and using an experimental prototype of a high-precision motion system. © 2022, CC BY.

关键词： Model predictive control

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Networked Supervisory control Synthesis of Timed Discrete-Event systems

arXiv

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arXiv 2021年

作者： Rashidinejad, Aida Reniers, Michel Fabian, Martin The Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands Department of Electrical Engineering Chalmers University of Technology Sweden

—Conventional supervisory control theory assumes full synchronization between the supervisor and the plant. This assumption is violated in a networked-based communication setting due to the presence of delays, and this may result in incorrect behavior of a supervisor obtained from conventional supervisory control theory. This paper presents a technique to synthesize a networked supervisor handling communication delays. For this purpose, first, a networked supervisory control framework is provided, where the supervisor interacts with the plant through control and observation channels, both of which introduce delays. The control channel is FIFO, but the observation channel is assumed to be non-FIFO so that the observation of events may not necessarily be received by the supervisor in the same order as they occurred in the plant. It is assumed that a global clock exists in the networked control system, and so the communication delays are represented in terms of time. Based on the proposed framework, a networked plant automaton is achieved, which models the behavior of the plant under the effects of communication delays and disordered observations. Based on the networked plant, the networked supervisor is synthesized, which is guaranteed to be (timed networked) controllable, nonblocking, time-lock free, (timed networked) maximally permissive, and satisfies control requirements for the plant. Copyright © 2021, The Authors. All rights reserved.

关键词： Discrete event simulation

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Frontiers in high entropy alloys and high entropy functional materials

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Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao Zhang Xue-Qian Wang Feng-Qi Zhang Xiao-Ya Cui Bing-Bing Fan Jia-Ming Guo Zhi-Min Guo Rui Huang Wen Huang Xu-Bo Li Meng-Ru Li Yan Ma Zhi-Hua Shen Yong-Gang Sun De-Zhuang Wang Fei-Yang Wang Li-Qiang Wang Nan Wang Tian-Li Wang Wei Wang Xiao-Yang Wang Yi-Han Wang Fu-Jie Yu Yu-Zhen Yin Ling-Kun Zhang Yi Zhang Jian-Yang Zhang Qi Zhao Yu-Ping Zhao Xin-Dong Zhu Yasir Sohail Ya-Nan Chen Tao Feng Qi-Long Gao Hai-Yan He Yong-Jiang Huang Zeng-Bao Jiao Hua Ji Yao Jiang Qiang Li Xiao-Ming Li Wei-Bing Liao Huai-Jun Lin Hui Liu Qi Liu Qing-Feng Liu Wei-Di Liu Xiong-Jun Liu Yang Lu Yi-Ping Lu Wen Ma Xue-Fei Miao Jie Pan Qing Wang Hong-Hui Wu Yuan Wu Tao Yang Wei-Ming Yang Qian Yu Jin-Yu Zhang Zhi-Gang Chen Liang Mao Yang Ren Bao-Long Shen Xun-Li Wang Zhe Jia He Zhu Zhen-Duo Wu Si Lan School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and EngineeringSoutheast UniversityNanjing 211189China Department of Physics City University of Hong KongHongKong 999077China School of Materials Science and Engineering Tianjin UniversityTianjin 300072China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China Department of Mechanical Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 100872China Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Institute of Advanced Wear&Corrosion Resistance and Functional Materials Jinan UniversityGuangzhou 510632China School of Mechanics and Civil Engineering China University of Mining and TechnologyXuzhou 221116China School of Physical Sciences Great Bay UniversityDongguan 523000China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical EngineeringNanjing Tech UniversityNanjing 211816China Beijing Advanced Innovation Center for Materials Genome Engineering Research Institute for Carbon NeutralityUniversity of Science and Technology BeijingBeijing 100083China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China School of Computing Macquarie UniversitySydney 2113Australia Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laborato

Owing to their exceptional properties,high-entropy alloys(HEAs)and high-entropy materials have emerged as promising research areas and shown diverse ***,the recent advances in the field are comprehensively reviewed,organized into five *** first section introduces the background of HEAs,covering their definition,significance,application prospects,basic properties,design principles,and *** subsequent section focuses on cutting-edge high-entropy structural materials,highlighting developments such as nanostructured alloys,grain boundary engineering,eutectic systems,cryogenic alloys,thin films,micro-nano-lattice structures,additive manufacturing,high entropy metallic glasses,nano-precipitate strengthened alloys,composition modulation,alloy fibers,and refractory *** the following section,the emphasis shifts to functional materials,exploring HEAs as catalysts,magneto-caloric materials,corrosion-resistant alloys,radiation-resistant alloys,hydrogen storage systems,and materials for ***,the review encompasses functional high-entropy materials outside the realm of alloys,including thermoelectric,quantum dots,nanooxide catalysts,energy storage materials,negative thermal expansion ceramics,and high-entropy wave absorption *** paper concludes with an outlook,discussing future directions and potential growth areas in the *** this comprehensive review,researchers,engineers,and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： High entropy alloys Cutting-edge structural materials Cutting-edgefunctional materials

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An 2-consistent event-triggered control policy for linear systems

引用

Automatica 2021年 125卷 109412-109412页

作者： Balaghiinaloo, Mohammadhadi Antunes, Duarte J. Heemels, W.P.M.H. [Maurice] Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology P.O. Box 513 MB EindhovenNL-5600 Netherlands

In this article, we consider the design of an event-triggered 2-control policy, for a setting where a scheduler is arbitrating state transmissions from the sensors to the controller of a discrete-time linear system. We start by introducing a periodic time-triggered 2-controller for different transmission time-periods with a given 2-gain bound using the minimax game-theoretical approach. After that, we propose an 2-consistent event-triggered controller in the sense that it guarantees at least the same 2-gain bound as the designed periodic time-triggered 2-controller, however with a larger, or at most equal, average inter-transmission time. In practice, for typical disturbances, the proposed event-triggered scheme can lead to significant gains, both in terms of communication savings and disturbance attenuation, compared to periodic time-triggered policies, which is illustrated through a numerical example. © 2020 Elsevier Ltd

关键词： Networked control systems

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On exploration requirements for learning safety constraints

arXiv

引用

arXiv 2021年

作者： Massiani, Pierre-François Heim, Steve Trimpe, Sebastian Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany

Enforcing safety for dynamical systems is challenging, since it requires constraint satisfaction along trajectory predictions. Equivalent control constraints can be computed in the form of sets that enforce positive invariance, and can thus guarantee safety in feedback controllers without predictions. However, these constraints are cumbersome to compute from models, and it is not yet well established how to infer constraints from data. In this paper, we shed light on the key objects involved in learning control constraints from data in a model-free setting. In particular, we discuss the family of constraints that enforce safety in the context of a nominal control policy, and expose that these constraints do not need to be accurate everywhere. They only need to correctly exclude a subset of the state-actions that would cause failure, which we call the critical set. Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamical systems

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Neural Network Training Using Closed-Loop Data: Hazards and an Instrumental Variable (IVNN) Solution

arXiv

引用

arXiv 2022年

作者： Kon, Johan Heertjes, Marcel Oomen, Tom Control Systems Technology Group Departement of Mechanical Engineering Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands ASML Mechatronics System Development Veldhoven Netherlands Delft Center for Systems and Control Delft University of Technology P.O. Box 5 Delft2600 AA Netherlands

An increasing trend in the use of neural networks in control systems is being observed. The aim of this paper is to reveal that the straightforward application of learning neural network feedforward controllers with closed-loop data may introduce parameter inconsistency that degrades control performance, and to provide a solution. The proposed method employs instrumental variables to ensure consistent parameter estimates. A nonlinear system example reveals that the developed instrumental variable neural network (IVNN) approach asymptotically recovers the optimal solution, while pre-existing approaches are shown to lead to inconsistent estimates. Copyright © 2022, The Authors. All rights reserved.

关键词： Feedforward neural networks

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Feedback Optimization with State Constraints through control Barrier Functions

arXiv

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arXiv 2025年

作者： Delimpaltadakis, Giannis Mestres, Pol Cortés, Jorge Heemels, W.P.M.H. Control Systems Technology group Eindhoven University of Technology Netherlands Department of Mechanical and Aerospace Engineering University of California San Diego United States

Recently, there has been a surge of research on a class of methods called feedback optimization. These are methods to steer the state of a control system to an equilibrium that arises as the solution of an optimization problem. Despite the growing literature on the topic, the important problem of enforcing state constraints at all times remains unaddressed. In this work, we present the first feedback-optimization method that enforces state constraints. The method combines a class of dynamics called safe gradient flows with high-order control barrier functions. We provide a number of results on our proposed controller, including well-posedness guarantees, anytime constraint-satisfaction guarantees, equivalence between the closed-loop’s equilibria and the optimization problem’s critical points, and local asymptotic stability of optima. Copyright © 2025, The Authors. All rights reserved.

关键词： Feedback control

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