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3rd International Congress on Optics, Electronics, and Optoelectronics, ICOEO 2022

作者： Azarova, O.A. Krasnobaev, K.V. Lapushkina, T.A. Kravchenko, O.V. Federal Research Center Computer Science and Control The Russian Academy of Sciences Vavilova str. 40 Moscow119333 Russia Lomonosov Moscow State University Faculty of Mechanics and Mathematics Leninskiye Gory Main Building GSP-1 Moscow119991 Russia Ioffe Institute Politekhnicheskaya str. 26 St Petersburg194021 Russia

The results of experiments and numerical simulations of the interaction of a plane shock wave with an area of ionization strata formed by a glow gas discharge are presented. For the experimentally obtained phenomena transformations of kinetic and internal energy have been studied numerically using Euler and Navier-Stokes approaches under the assumption that ionization unstable plasma has stratified gas temperature. Energy transfer between a region of layered energy deposition and heated gas zone behind the shock wave was considered. It has been established that a layered energy deposition can provide the distortion and destruction of a shock wave front and in addition, to create a lot of zones with higher internal and kinetic energy beyond it. These phenomena were shown to be connected with generation in many points of the Richtmyer-Meshkov instability resulting from the interaction of thermal strata with a front of the shock wave. © Published under licence by IOP Publishing Ltd.

关键词： Shock waves

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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research on Train Operation control Strategy Based on Particle Swarm Optimization Algorithm 25

Research on Train Operation Control Strategy Based on Partic...

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Proceedings of the 2025 International Conference on Intelligent Systems, Automation and control

作者： Youbing Zhang Haihong E Ling Liu Zhiqiang Chen Jianmin Wang Pengyu Bao Research Institute of Safety Control Technology Beijing National Railway Research & Design Institute of Signal & Communication Co. Ltd. Beijing China Graduate College for Engineers Beijing University of Posts and Telecommunications Beijing China School of Computer Science Beijing University of Posts and Telecommunications Beijing China Beijing National Railway Research & Design Institute of Signal & Communication Co. Ltd. Beijing China Research Institute of Safety Control Technology Beijing National Railway Research & Design Institute of Signal & Communication Co. Ltd. Beijing China

ISBN: (纸本)9798400715198

To solve the problems of long running time and high energy consumption of existing high-speed railways, intercity railways and other trains between stations. The study adopts a four-phase operation control strategy to drive trains, and investigates the impact of operating condition transition points on running time and energy consumption. The particle swarm optimization algorithm is used to find the global optimal solution that balances running time and energy consumption in the solution space of operating condition transition points. The research results indicate that a method has been designed to determine the four-phase train operation control strategy by only solving the speed of two points: acceleration-cruising transition point and coasting-braking transition point. This reduces the particle dimension of particle swarm optimization algorithm and improves the efficiency of using particle swarm optimization algorithm to solve the four-phase train operation control strategy. An equivalent method for calculating energy consumption during the cruising phase is proposed to ensure more accurate calculation of energy consumption during train running. By configuring appropriate time and energy consumption coefficients and using particle swarm optimization algorithm, the four-phase train operation control strategy can be solved to obtain the optimal position and speed of the operating condition transition point. This can achieve dual objective optimization of running time and energy consumption, reducing train running energy consumption while ensuring on-time operation. Using the line data from Xinmin North Station to Heishan North Station on the Beijing Shenyang High speed Railway, with CR400BF-A high-speed multiple unit parameters as input, a time coefficient of 0.6 and an energy consumption coefficient of 0.4, the four-phase train operation control strategy solved by particle swarm optimization algorithm was used to drive the train. The running time was 1010 seconds

关键词： Four-phase control strategy

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Improving Constants in Esseen–Rozovskii Type Inequalities for Identically Distributed Random terms

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Moscow University Computational Mathematics and Cybernetics 2023年第4期46卷 222-232页

作者： Maksimova, A. V. Shevtsova, I. G. Faculty of Computational Mathematics and Cybernetics Moscow State University Moscow Russia Hangzhou Dianzi University Hangzhou China Institute of Informatics Problems Federal Research Center of Computer Science and Control Russian Academy of Sciences Moscow Russia

Constants in Esseen–Rozovskii type inequalities proposed by Gabdullin, Makarenko, and Shevtsova (2018) are improved for one of the most important special cases: independent identically distributed random summands. The considered inequalities are used to estimate the uniform distance between the distribution function of the standardized sum of independent identically distributed random summands with finite second moments and the standard normal distribution function. As in the work by Gabdullin, Makarenko, and Shevtsova (2018), an estimate is made in terms of a truncated algebraic third-order moment and the tail of the second-order moment of the general distribution of random summands.

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FeatSense – A Feature-Based Registration Algorithm with GPU-Accelerated TSDF-Mapping Backend for NVIDIA Jetson Boards

FeatSense – A Feature-Based Registration Algorithm with GPU...

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IEEE International Conference on Robotic Computing (IRC)

作者： Julian Gaal Thomas Wiemann Alexander Mock Mario Porrmann Institute of Computer Science Osnabrück University Osnabrück Germany Fulda University of Applied Sciences Applied Computer Science Fulda Germany German Research Center for Artificial Intelligence (DFKI) Plan-based Robot Control Osnabrück Germany

This paper presents FeatSense, a feature-based GPU-accelerated SLAM system for high-resolution LiDARs, combined with a map generation algorithm for real-time gener-ation of large Truncated Signed Distance Fields (TSDFs) on em-bedded hardware. FeatSense uses LiDAR point cloud features for odometry estimation and point cloud registration. The registered point clouds are integrated into a global Truncated Signed Distance Field (TSDF) representation. FeatSense is intended to run on embedded systems with integrated GPU-accelerator like NVIDIA Jetson boards. In this paper, we present a real-time capable TSDF-SLAM system specially tailored for closely coupled CPU/GPU systems. The implementation is evaluated in various structured and unstructured environments and benchmarked against existing reference datasets. The main contribution of this paper is the ability to register up to 128 scan lines of an Ouster OS1-128 LiDAR at 10Hz on a NVIDIA AGX Xavier while achieving a TSDF map generation speedup by a factor of 100 compared to previous work on the same power budget.

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How grey wolf optimization affects remanufacturing

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Procedia CIRP 2024年 126卷 927-932页

作者： Barna Gal Christine Zeh Ádám Szaller Fraunhofer Austria Research GmbH Theresianumgasse 7 A-1040 Wien Austria Institute for Computer Science and Control Kende str. 13-17 1111 Budapest Hungary EPIC InnoLabs Nonprofit Ltd. Kende str. 13-17 1111 Budapest Hungary

While in 1971 the Earth Overshoot Day was on December 25th, in 2022 this day for Austria was already reached on July 28th. And since uncertainties in the remanufacturing production planning occur, companies are forced to take in trade-offs like increased production capacity available at short notice. These uncertainties result in financial losses and production waste, as well as bottlenecks in the supply of materials for gas engine assembly. For this reason, this paper explores the use of a grey wolf optimizer for the reduction of the cycle time of a gas engine remanufacturer. A discrete event simulation is used for evaluation purposes and the results from the scheduler are compared with benchmarks of the current production planning of manufacturers.

关键词： Sustainable Manufacturing Circular Economy Remanufacturing Production Planning Grey Wolf Optimizer

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Platoons Coordination Based on Decentralized Higher Order Barrier Certificates

Platoons Coordination Based on Decentralized Higher Order Ba...

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Mediterranean Conference on control and Automation (MED)

作者： Maryam Sharifi Dimos V. Dimarogonas ABB Corporate Research Västerås Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

This paper presents control strategies based on time-varying convergent higher order control barrier functions for the coordination of networks of platoons. This network could be modelled by a class of leader-follower multi-agent systems, where the leaders have knowledge on the associated tasks and control the performance of their platoon involved vehicles. The followers are not aware of the tasks, and do not have any control authority to reach them. They follow their platoon leader commands for the task satisfaction. Signal temporal logic (STL) tasks are defined for the platoons coordination. Robust solutions for the task satisfaction, based on the leader’s accessibility to the follower vehicles’ states are suggested. In addition, using the notion of higher order barrier functions, decentralized barrier certificates for each vehicle evolving in a formation dynamic structure are proposed. Our approach finds solutions to guarantee the satisfaction of STL tasks independent of the agents’ initial conditions.

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Distribution-Free Inference for the Regression Function of Binary Classification

arXiv

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arXiv 2023年

作者： Tamás, Ambrus Csáji, Balázs Csanád SZTAKI The Institute for Computer Science and Control ELKH: Eötvös Loránd Research Network 13-17 Kende utca Budapest1111 Hungary Budapest Hungary

One of the key objects of binary classification is the regression function, i.e., the conditional expectation of the class labels given the inputs. With the regression function not only a Bayes optimal classifier can be defined, but it also encodes the corresponding misclassification probabilities. The paper presents a resampling framework to construct exact, distribution-free and non-asymptotically guaranteed confidence regions for the true regression function for any user-chosen confidence level. Then, specific algorithms are suggested to demonstrate the framework. It is proved that the constructed confidence regions are strongly consistent, that is, any false model is excluded in the long run with probability one. The exclusion is quantified with probably approximately correct type bounds, as well. Finally, the algorithms are validated via numerical experiments, and the methods are compared to approximate asymptotic confidence ellipsoids. Copyright © 2023, The Authors. All rights reserved.

关键词： Numerical methods

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When Circular Economy Meets the Smart City Ecosystem: Defining the Smart and Circular City

arXiv

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arXiv 2024年

作者： Mylonas, Georgios Kalogeras, Athanasios Petersen, Sobah Abbas Muñoz, Luis Chatzigiannakis, Ioannis Industrial Systems Institute Athena Research Center Patras Greece Dpt. of Computer Science Norwegian University of Science and Technology Trondheim Norway Dpt. of Communications Engineering Universidad de Cantabria Santander Spain Dpt. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

Smart cities have been a very active research area in the past 20 years, while continuously adapting to new technological advancements and keeping up with the times regarding sustainability and climate change. In this context, there have been numerous proposals to expand the scope of smart cities, focusing on resilience and sustainability, among other aspects, resulting in terms like smart sustainable cities. At the same time, there is an ongoing discussion regarding the degree in which smart cities put people at their centre. In this work, we argue toward expanding the current smart city definition by integrating the circular economy as one of its central pillars and adopting the term smart (and) circular city. We discuss the ways a smart and circular city encompasses both sustainability and smartness in an integral manner, while also being well-positioned to foster novel business activity and models and helping to place citizens at the heart of the smart city. In this sense, we also argue that previous research in smart cities and technologies, such as those related to Industry 4.0, can serve as a cornerstone to implement circular economy activities within cities, at a scale that exceeds current activities that are based on more conventional approaches. We also outline current open challenges in this domain and research questions that still need to be addressed. Copyright © 2024, The Authors. All rights reserved.

关键词： Circular economy

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