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7th Scientific School: Dynamics of complex Networks and their Applications, DCNA 2023

作者： Semenov, Aleksandr Fradkov, Alexander Institute for Problems in Mechanical Engineering Control of Complex Systems Saint Petersburg Russia

ISBN: (纸本)9798350305746

In paper the problem of identifying the parameters of the generalized Lotka-Volterra model is studied. We found conditions under which the discrete algorithm ''Stripe"proposed by V. A. Yakubovich achieves the identification goals. It is proved that the conditions are not essentially restrictive. The notion of a nonhyperplanar trajectory is introduced. It is proved that for any recurrent nonhyperplanar trajectory, the persistent excitation condition is satisfied. © 2023 IEEE.

关键词： Trajectories

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Functional identification of the parameters multispecies Lotka-Volterra model 6

Functional identification of the parameters multispecies Lot...

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6th Scientific School "Dynamics of complex Networks and their Applications", DCNA 2022

作者： Fradkov, Alexander Semenov, Aleksandr Institute for Problems in Mechanical Engineering Control of Complex Systems Saint Petersburg Russia

ISBN: (数字)9781665461740

ISBN: (纸本)9781665461740

In this paper we set and solve the problem of functional identification of parameters of the Lotka-Volterra multispecies model using the 'Stripe' algorithm developed by V.A. Yakubovich. Assertions about some properties of the model are formulated and proved. The theoretical results are supported by modeling. © 2022 IEEE.

关键词： Multi agent systems

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Data-driven finite-time adaptive attitude tracking control for spacecraft

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Advances in Space Research 2025年第12期75卷 8780-8791页

作者： Wang, Jianhui He, Guangping Bian, Guibin Geng, Shixiong College of Mechanical & Energy Engineering Beijing University Of Technology Beijing100124 China Department of Mechanical and Electrical Engineering North China University of Technology Beijing100144 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the disturbance unit matrix is introduced, and the parameter estimation law in the form of algebraic equations is presented, which realizes the arbitrarily small convergence of parameter estimation error. The convergence of parameter estimation errors is verified through stability analysis. Globally non-singular fast terminal sliding mode control is designed to achieve finite-time arrival of the sliding surface and convergence of the system state error. The stability analysis of the closed-loop system demonstrates the effectiveness of the proposed method. Furthermore, the effectiveness and superiority of the proposed method are verified through numerical simulations of spacecraft attitude tracking control. © 2025 COSPAR

关键词： Attitude control

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Foundation Vehicles: From Foundation Intelligence to Foundation Transportation for Future Mobility

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年 1-5页

作者： Wang, Fei-Yue Lv, Chen The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore

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Adaptive observer for a LTV system with partially unknown state matrix and delayed measurements 14

Adaptive observer for a LTV system with partially unknown st...

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14th International Congress on Ultra Modern Telecommunications and control systems and Workshops, ICUMT 2022

作者： Bobtsov, Alexey Nikolaev, Nikolay Slita, Olga Kozachek, Olga Oskina, Olga Itmo University Institute of Problems of Mechanical Engineering Laboratory 'Control of Complex Systems' Department of Control Systems and Robotics Saint-Petersburg Russia Itmo University Department of Control Systems and Robotics Saint-Petersburg Russia

ISBN: (数字)9798350398663

ISBN: (纸本)9798350398663

Problem of adaptive state observer synthesis for linear time-varying (LTV) system with unknown time-varying parameter and delayed output measurements is considered. State observation problem has attracted the attention of many researchers [1]. In this paper the results proposed in the [2]-[4] are developed. It is supposed that the state matrix can be represented as sum of known and unknown parts. Output vector is measured with known constant delay. An adaptive identification algorithm which reconstructs unknown state and unknown time-varying parameter is proposed. © 2022 IEEE.

关键词： Time varying control systems

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Synchronized UAV Group Flight control under Data Rate Limitations and Actuator Saturation 7

Synchronized UAV Group Flight Control under Data Rate Limita...

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7th Scientific School: Dynamics of complex Networks and their Applications, DCNA 2023

作者： Andrievsky, Boris Zaitceva, Luliia St. Petersburg State University Control of Complex Systems Lab. Institute for Problems in Mechanical Engineering of Ras Department of Applied Cybernetics Saint Petersburg Russia St. Petersburg State University St. Petersburg Electrotechnical University ''LETI" Control of Complex Systems Lab. Institute for Problems in Mechanical Engineering of Ras Department of Applied Cybernetics Saint Petersburg Russia

ISBN: (纸本)9798350305746

This work specifically addresses the challenges associated with information transfer between agents in pursuit of desired control objectives. Seamless communication is crucial, especially during formation synchronization, as delays can lead to disintegration. Additionally, large-scale systems may face string or mesh instability, where state deviations increase. This work aims to advance decentralized control in multi-agent systems with complex information graph structures, considering nonlinear limitations on the control signal. A sequential nonlinear corrective unit is employed to mitigate this effect. The present study incorporates data rate limitations on information exchange between UAVs in formation. An adaptive coding/decoding procedure is utilized for data transfer, and the minimal data transmission rate required for maintaining formation stability is numerically evaluated. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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Parameters identification of the multispecies Lotka-Volterra model using discrete algorithm

Parameters identification of the multispecies Lotka-Volterra...

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School on Dynamics of complex Networks and their Application in Intellectual Robotics (DCNAIR)

作者： Aleksandr Semenov Alexander Fradkov Control of Complex Systems Institute for Problems in Mechanical Engineering Saint Petersburg Russia

In paper the problem of identifying the parameters of the generalized Lotka-Volterra model is studied. We found conditions under which the discrete algorithm ’’Stripe" proposed by V. A. Yakubovich achieves the identification goals. It is proved that the conditions are not essentially restrictive. The notion of a nonhyperplanar trajectory is introduced. It is proved that for any recurrent nonhyperplanar trajectory, the persistent excitation condition is satisfied.

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Pavement Cracks Coupled With Shadows:A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1593-1607页

作者： Lili Fan Shen Li Ying Li Bai Li Dongpu Cao Fei-Yue Wang School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Civil Engineering Tsinghua UniversityBeijing 100084China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body and the College of Mechanical and Vehicle Engineering Hunan UniversityChangsha 410082China School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Automatic pavement crack detection is a critical task for maintaining the pavement stability and driving *** task is challenging because the shadows on the pavement may have similar intensity with the crack,which interfere with the crack detection *** to the present,there still lacks efficient algorithm models and training datasets to deal with the interference brought by the *** fill in the gap,we made several contributions as ***,we proposed a new pavement shadow and crack dataset,which contains a variety of shadow and pavement pixel size *** also covers all common cracks(linear cracks and network cracks),placing higher demands on crack detection ***,we designed a two-step shadow-removal-oriented crack detection approach:SROCD,which improves the performance of the algorithm by first removing the shadow and then detecting *** addition to shadows,the method can cope with other noise ***,we explored the mechanism of how shadows affect crack *** on this mechanism,we propose a data augmentation method based on the difference in brightness values,which can adapt to brightness changes caused by seasonal and weather ***,we introduced a residual feature augmentation algorithm to detect small cracks that can predict sudden disasters,and the algorithm improves the performance of the model *** compare our method with the state-of-the-art methods on existing pavement crack datasets and the shadow-crack dataset,and the experimental results demonstrate the superiority of our method.

关键词： Automatic pavement crack detection data augmentation compensation deep learning residual feature augmentation shadow removal shadow-crack dataset

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Distributed algorithm for nonuniform deployment of the agents on the segment 5

Distributed algorithm for nonuniform deployment of the agent...

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5th Scientific School on Dynamics of complex Networks and their Applications, DCNA 2021

作者： Semenov, Aleksandr Control of Complex Systems Institute of problems in mechanical engineering Saint Petersburg Russia

ISBN: (纸本)9781665442824

The paper presents for the first time an asymptotically stable distributed algorithm that provides nonuniform deployment of agents on a segment. It is shown that neither delays in information transfer between agents, nor changes in the network configuration - switches - affect the achievement of the goal using the proposed algorithm. © 2021 IEEE

关键词： Multi agent systems

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