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Designing novel adaptive dynamic event-triggered protocols for uncertain multi-agent systems

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Science China(Information Sciences) 2024年第1期67卷 310-311页

作者： Bin CHENG Bin HE College of Electronics and Information engineering Tongji University Frontiers Science Center for Intelligent autonomous systems

Multi-agent systems (MASs) have garnered widespread attention and have been investigated by numerous researchers in recent years, primarily due to their broad applications in industry, transportation, agriculture, and astronomy. While studying the cooperative control of MASs, numerous researchers place emphasis on reducing the frequency of communication among neighboring agents.

关键词： Directed graphs

Mixed H_(∞)/Passive Exponential Synchronization for Delayed Memristive Neural Networks with Switching Event-Triggered Control

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Journal of systems Science & Complexity 2024年第1期37卷 294-317页

作者： WU Wenhuang GUO Lulu CHEN Hong Shanghai Research Institute for Intelligent autonomous systems Tongji UniversityShanghai 200092China Department of Control Science and engineering Tongji UniversityShanghai 201804China

This paper is devoted to event-triggered synchronization of delayed memristive neural networks with H∞and passivity *** aim is to guarantee the exponential synchronization and mixed H∞and passivity control for memristive neural networks by using event-triggered ***,a switching system is constructed under the event-triggered control ***,by adopting a piece-wise Lyapunov functional,a sufficient condition is established for the exponential synchronization and mixed H_(∞)and passivity ***,an event-triggered controller design scheme is proposed using matrix decoupling ***,the effectiveness of the designed controller is exemplified by a numerical example.

关键词： Event-triggered control exponential synchronization memristive neural networks time delays.

Sampling-efficient path planning and improved actor-critic-based obstacle avoidance for autonomous robots

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Science China(Information Sciences) 2024年第5期67卷 197-214页

作者： Yefeng YANG Tao HUANG Tianqi WANG Wenyu YANG Han CHEN Boyang LI Chih-yung WEN Department of Aeronautical and Aviation engineering The Hong Kong Polytechnic University Center for Control Theory and Guidance Technology Harbin Institute of Technology School of engineering The University of Newcastle Research Center for Unmanned autonomous systems The Hong Kong Polytechnic University

autonomous robots have garnered extensive utilization in diverse fields. Among the critical concerns for autonomous systems, path planning holds paramount importance. Notwithstanding considerable efforts in its development over the years, path planning for autonomous systems continues to grapple with challenges related to low planning efficiency and inadequate obstacle avoidance response in a timely *** study proposes a novel and systematic solution to the path planning problem within intricate office buildings. The solution consists of a global planner and a local planner. To handle the global planning aspect, an adaptive clustering-based dynamic programming rapidly exploring random tree(ACDP-RRT) algorithm is proposed. ACDP-RRT effectively identifies obstacles on the map by leveraging geometric *** obstacles are then represented as a collection of sequentially arranged convex polygons, optimizing the sampling region and significantly enhancing sampling efficiency. For local planning, a network decoupling actor-critic(ND-AC) algorithm is employed. The proposed ND-AC simplifies the local planner design process by integrating planning and control loops into a neural network(NN) trained via an end-to-end model-free deep reinforcement learning(DRL) framework. Moreover, the adoption of network decoupling(ND) techniques leads to an improved obstacle avoidance success rate when compared to conventional actor-critic(AC)-based methods. Extensive simulations and experiments are conducted to demonstrate the effectiveness and robustness of the proposed approach.

关键词： rapidly exploring random tree (RRT) adaptive clustering network decoupling actor critic (AC) path planning

Cybersecurity Landscape on Remote State Estimation:A Comprehensive Review

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 851-865页

作者： Jing Zhou Jun Shang Tongwen Chen the Department of Electrical and Computer engineering University of AlbertaEdmonton AB T6G 1H9Canada the Department of Control Science and engineering and Shanghai Research Institute for Intelligent autonomous systems Tongji UniversityShanghai 200092China

Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control *** state estimation(RSE)is an indispensable functional module of ***,it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels of RSE,leading to severe estimation performance *** paper aims to present an overview of recent advances in cyber-attacks and defensive countermeasures,with a specific focus on integrity attacks against ***,two representative frameworks for the synthesis of optimal deception attacks with various performance metrics and stealthiness constraints are discussed,which provide a deeper insight into the vulnerabilities of ***,a detailed review of typical attack detection and resilient estimation algorithms is included,illustrating the latest defensive measures safeguarding RSE from ***,some prevalent attacks impairing the confidentiality and data availability of RSE are examined from both attackers'and defenders'***,several challenges and open problems are presented to inspire further exploration and future research in this field.

关键词： Cyber-attacks Kalman filtering remote state estimation unreliable transmission channels

Reinforcement Learning-Based MAS Interception in Antagonistic Environments

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 270-272页

作者： Siqing Sun Defu Cai Hai-Tao Zhang Ning Xing the School of Artificial Intelligence and Automation the MOE Engineering Research Center of Autonomous Intelligent Unmanned Systemsthe Guangdong Engineering Technology Research Center of Fully Autonomous Unmanned Surface VehiclesHuazhong University of Science and TechnologyWuhan 430074China the State Grid Hubei Electric Power Research Institute Wuhan 430074China IEEE

Dear Editor, As a promising multi-agent systems(MASs) operation, autonomous interception has attracted more and more attentions in these years, where defenders prevent intruders from reaching *** far, most of the relevant methods are applied in ideal environments without agent damages. As a remedy, this letter proposes a more realistic interception method for MASs suffered by damages.

关键词： agent MAS destination

Control of 2-D Semi-Markov Jump systems:A View from Mode Generation Mechanism

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 258-260页

作者： Yunzhe Men Jian Sun Jie Chen the National Key Laboratory of autonomous Intelligent Unmanned systems the School of AutomationBeijing Institute of TechnologyBeijing 100081 the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China the Department of Control Science and engineering Tongji UniversityShanghai 201804 the National Key Laboratory of autonomous Intelligent Unmanned systems Beijing Institute of TechnologyBeijing 100081China

Dear Editor,Two-dimensional(2-D) systems have wide applications in image data processing,gas absorption and fluid dynamics analysis [1]-[3].When there exist abrupt changes in 2-D systems,they are usually modeled by 2-D Markov jump systems(MJSs) or 2-D semi-Markov jump systems(SMJSs).This letter investigates the control of 2-D SMJSs based on a novel mode generation mechanism,which could avoid mode ambiguousness phenomenon caused by the evolution of system mode in two different *** criterion that guarantees the almost surely exponential stability of the system is obtained.A thermal process is studied to demonstrate the availability of the proposed method.

关键词： Markov mode system

Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li Fei-Yue Wang the State Key Laboratory for Management and Control of Complex systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and autonomous systems Institute(TASI)and the Department of Electrical and Computer engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

Equalizer Zero-Determinant Strategy in Discounted Repeated Stackelberg Asymmetric Game

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Journal of systems Science & Complexity 2024年第1期37卷 184-203页

作者： CHENG Zhaoyang CHEN Guanpu HONG Yiguang Key Laboratory of systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Electrical engineering and Computer Science KTH Royal Institute of Technology10044 StockholmSweden. Department of Control Science and engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent autonomous systems Tongji UniversityShanghai 210201China

This paper focuses on the performance of equalizer zero-determinant(ZD)strategies in discounted repeated Stackelberg asymmetric *** the leader-follower adversarial scenario,the strong Stackelberg equilibrium(SSE)deriving from the opponents’best response(BR),is technically the optimal strategy for the ***,computing an SSE strategy may be difficult since it needs to solve a mixed-integer program and has exponential complexity in the number of *** this end,the authors propose an equalizer ZD strategy,which can unilaterally restrict the opponent’s expected *** authors first study the existence of an equalizer ZD strategy with one-to-one situations,and analyze an upper bound of its performance with the baseline SSE *** the authors turn to multi-player models,where there exists one player adopting an equalizer ZD *** authors give bounds of the weighted sum of opponents’s utilities,and compare it with the SSE ***,the authors give simulations on unmanned aerial vehicles(UAVs)and the moving target defense(MTD)to verify the effectiveness of the proposed approach.

关键词： Discounted repeated Stackelberg asymmetric game equalizer zero-determinant strategy strong Stackelberg equilibrium strategy

Lead-free perovskites-based photonic synaptic devices with zero electric energy consumption

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Science China(Information Sciences) 2024年第6期67卷 433-441页

作者： Dandan HAO Di YANG Haixia LIANG Jia HUANG Fukai SHAN College of Electronics and Information Qingdao University Key Laboratory of Biofuels Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of Sciences School of Materials Science and engineering Tongji University National Key Laboratory of autonomous Intelligent Unmanned systems Tongji University

The von Neumann bottleneck is a critical limitation in synaptic devices. Therefore, artificial synaptic devices resembling biological neuromorphic synapses have been developed to overcome the von Neumann bottleneck. However, synaptic devices require voltages, which results in considerable energy consumption. Here, photonic synaptic devices with the vertical structure of indium tin oxide（ITO）/SnO2/Al2O3/CsBi3I10/Au are fabricated, which can work in the self-powered mode owing to the photovoltaic effect endowed by a vertical multilayer structure. Several fundamental synaptic functions, such as excitatory postsynaptic current, paired-pulse facilitation, short-term plasticity（STP）, long-term plasticity（LTP）, pulse-frequency-dependent plasticity, transition of STP to LTP, and the learning experience are emulated. Moreover, Morse-coded external light information is decoded by self-powered photonic synaptic devices. The results indicate that self-powered photonic synaptic devices based on lead-free perovskites exhibit great potential for efficient neuromorphic computing and optical wireless communication.

关键词： photonic synaptic devices lead-free perovskites zero energy consumption synaptic plasticity Morse code

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