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63rd IEEE Conference on Decision and control, CDC 2024

作者： Mavridis, Christos Kanellopoulos, Aris Sandberg, Henrik Johansson, Karl Henrik Kth Royal Institute of Technology Division of Decision and Control School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350316339

We investigate the problem of deceiving a malicious agent employing an identification method to estimate the closed-loop dynamics of a cyber-physical system. In particular, we propose a moving target defense mechanism that utilizes stochastic switching between linear closed-loop dynamics to drive a linear system identification process of a potential adversary to sub-optimal solutions with non-vanishing error. We provide a statistical analysis of the induced identification error and show that it is not possible for any linear system identification method to reconstruct the average dynamics of a stochastic switched linear system. Finally, we utilize the theory of Markov jump linear systems to guarantee asymptotic stability of the switching system, and formulate the switching control problem as an optimization problem that guarantees stability while taking into account the trade-off between security and switching effort. Simulation results showcase the efficacy of the proposed approach in inducing identification error for the adversary using minimal switching. © 2024 IEEE.

关键词： Markov processes

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Communication Countermeasure Strategy Decision-Making Based on Incomplete Information Game 27

Communication Countermeasure Strategy Decision-Making Based ...

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27th International Conference on Advanced Communications Technology, ICACT 2025

作者： Liu, Jinyue Gao, Xiang Yang, Haowei Zhang, Jihao Liu, Yuhan Gong, Peng National Key Laboratory of Mechatronic Engineering and Control School of Mechatronical Engineering Beijing Institute of Technology Beijing China Institute of Computer Application Technology Norinco Group Beijing China

ISBN: (纸本)9791188428137

In modern battlefields, the stability of wireless communications is crucial for intelligence transmission, command coordination, and maintaining strategic advantage. However, with the rapid advancement of communication technologies, the electromagnetic environment has become increasingly complex, making intelligent decision-making in communication countermeasures a prominent research focus. However, most existing studies adopt deep learning and reinforcement learning methods, which require extensive data samples and computational resources. To address these limitations, this paper proposes a game-theoretic model for intelligent radio communication countermeasures under incomplete information. It quantitatively evaluates common attack and defense tactcis used in communication countermeasures and explores the mixed-strategy equilibrium of the game when both the attackers and defenders consist of multiple types. Furthermore, simulation-based comparative analyses are conducted to assess the factors influencing the utility of both the attacker and defender. The findings offer theoretical insights and decision-making support for the deployment of communication countermeasure strategies in practical military operations, contributing to significant strategic value. © 2025 institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Deep reinforcement learning

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Annotated survey and perspectives on rail transport energy system RAMS evaluation technology

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Green Energy and Intelligent Transportation 2024年第3期3卷 75-90页

作者： Ruifeng Shi Lingzhi Zhang Feng Lin Jin Ning Limin Jia Kwang Y.Lee School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China China Institute of Energy and Transportation Integrated Development Beijing 102206China State Key Lab of Rail Traffic Control&Safety Beijing Jiaotong UniversityBeijing 100044China Department of Electrical and Computer Engineering Baylor UniversityWacoTX 76798USA

The rail transit system plays a crucial role in modern *** the increasing demand for clean and green energy in the transport sector,its energy system is expected to achieve low-carbon and highly efficient energy utilization in rail ***,the gradual development of the rail transport energy system has led to an increase in its complexity,and the rising difficulty of system assessment has faced the limitations of traditional assessment ***,it is essential to develop effective assessment *** paper begins by providing a systematic review of the development status of Reliability,Availability,Maintainability and Safety(RAMS)assessment and analyzing the shortcomings of traditional RAMS assessment technology in the context of rail transit energy ***,based on the four fundamental properties of RAMS,it summarizes the current state of key assessment technologies in the field of rail ***,the paper delves into the challenges and potential solutions concerning the implementation of RAMS assessment technology for rail transit energy ***,the paper offers an outlook on the future development of RAMS assessment for rail transport energy *** comprehensively analyzing these aspects,the paper aims to contribute valuable insights into optimizing the rail transit energy system,promoting its sustainable and efficient operation in the context of clean and green energy utilization.

关键词： Integration of energy and transportation RAMS evaluation Rail transit energy system

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A Registration and Fusion Method of 3D Cross-source Point Cloud Data for Modeling Accurate Models of Small Celestial Bodies

A Registration and Fusion Method of 3D Cross-source Point Cl...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： He, Xuan Zhao, Qingjie Lv, Xingchen Wang, Lei Liu, Wangwang School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering Beijing100190 China

ISBN: (纸本)9781665481090

High-precision three-dimensional models of small celestial bodies are important for deep space exploration tasks. The homologous point cloud obtained from a single sensor has limitations in terms of accuracy and density. For example, the point cloud obtained by RGB camera has rich information and high density, but low precision. The point cloud obtained by laser scanning has high precision but low density. Therefore, we hope to register and fuse the point clouds obtained from different sensors, synthesize the advantages of cross-source point clouds obtained from different source domains, and improve the density, accuracy and other aspects of small celestial point clouds. To solve the common problems of cross-source point clouds, we adopt an end-to-end feature measurement point cloud registration framework, which does not need to search the corresponding points between two point clouds, and reduces the difficulty of processing cross-source point cloud data. Aiming at the problem that some stray points on the registered point cloud surface affect the accuracy of the point cloud, a point cloud fusion optimization method based on Euclidean distance is proposed. The stray points around the point cloud are removed to reduce the loss of normal points. The accuracy of point cloud is improved by the fusion after registration. Experiments show that the proposed method can effectively improve the density and accuracy of small celestial body models. © 2024 IEEE.

关键词： Laser applications

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Multiple Robots Autonomous Task Planning Based on Improved Genetic Algorithm

Multiple Robots Autonomous Task Planning Based on Improved G...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Yang, Zhiyuan Zhao, Qingjie Lv, Xingchen Wang, Lei Liu, Wangwang School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering Beijing100190 China

ISBN: (纸本)9781665481090

This paper presents an autonomous task planning method for multiple collecting robots on improved genetic algorithm. Considering the limited capacity of collecting robots and the suitability of hopping robots in the microgravity environment of small celestial bodies, we developed a task planning model based on the Capacitated Vehicle Routing Problem (CVRP) and proposed an improved genetic algorithm to simultaneously allocate tasks and plan paths for multiple collecting robots. During robot movement, the A ∗ algorithm is employed for active obstacle avoidance when unknown obstacles are encountered. Experimental results demonstrated that our algorithm, can efficiently allocate tasks for the robot group, and each robot actively avoiding obstacles during movement. © 2024 IEEE.

关键词： Microrobots

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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2024年第2期16卷 1-18页

作者： PETRESCU, Alexandru TRUICA, Ciprian-Octavian APOSTOL, Elena-Simona PASCHKE, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania Fraunhofer Institute for Open Communication Systems Berlin Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors

关键词： Sentiment analysis

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Rice Variety Classification Based on Optimized Near-Infrared Spectral Classification Model

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Rice science 2024年第1期31卷 6-9,I0009-I0012页

作者： YANG Sen WANG Zhenmin ZHANG Houqing SONG Wenlong College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040China The 49th Research Institute of China Electronics Technology Group Corporation Harbin 150000China

Accurate classification of rice variety is essential to ensure the brand value of high-quality rice *** the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were *** enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).

关键词： sealing Infrared grinding

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A Note on the Local Observability of Uniform Hypergraphs

A Note on the Local Observability of Uniform Hypergraphs

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94th Annual Meeting of the International Association of Applied Mathematics and Mechanics, GAMM 2024

作者： Gerbet, Daniel Röbenack, Klaus Institute of Control Theory Faculty of Electrical and Computer Engineering TUD Dresden University of Technology Dresden Germany

Hypergraphs generalize graphs in such a way that edges may connect any number of nodes. If all edges are adjacent to the same number of nodes, the hypergraph is called uniform. Thus, a graph is a 2-uniform hypergraph. Each uniform hypergraph can be identified with an autonomous dynamical state-space system, whose vector field is composed of homogenous polynomials. We consider the observability of dynamical systems, which possess this special structure. In control theory, the observability of a dynamical system asks for the possibility to reconstruct the systems state from an output trajectory, where the output is a projective measurement of the systems state. In addition, one can ask for the observable subspace of the state. Nonlinear systems, although observable at almost all points in the state space, may possess not-locally observable ones. The existence and location of such states are important for observability analysis and observer design. Recently, the observability of these hypergraph systems has been studied for the general case. We apply an extended deterministic observability test to uniform hypergraphs and also compute the not-observable states for different linear output maps. We are able to confirm the results of the recent study, at least for graphs with a small number of nodes, due to the computational complexity of our method. In addition, the not-locally observable states are computed for different combinations of measured nodes. © 2025 The Author(s).

关键词： Dynamical systems

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Modeling of Trust in Social Relationships for Secure Communication in Social Internet of Things 4

Modeling of Trust in Social Relationships for Secure Communi...

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4th International Conference on Blockchain Technology and Information Security, ICBCTIS 2024

作者： Khan, Salabat Amin, Farhan Khan, Mansoor School of Computer and Information Engineering Qilu Institute of Technology Shandong Jinan China School of Computer Science and Engineering Yeungnam University Korea Republic of School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Shandong Jinan China

ISBN: (纸本)9798331528324

Herein, a social trust model is presented for investigating social relationships and social networks in the real world. Our proposal addresses the design of conceptual concepts to easily implement and develop complex applications that require direct interaction among objects. The secure social relationship paradigm guarantees network navigability, even if there are more objects on the traditional Internet of Things (IoT). This paradigm shift is very interesting, but very limited researchers have worked in this direction. Therefore, the core objective of our article is to study and classify these objects and emphasize the importance and the characteristics of trust in social objects and their relationships. Herein, five types of secure social relationships were identified and explained with real scenarios. Finding new social relationships and understanding different features and characteristics helps the researcher understand their structure and, thus, build trust between smart objects. Based on these social relationships we propose secure social relationship modeling. The achieved experimental result shows that our proposed model outperforms as compared to the state-of-the-art model. The efficiency is measured based on processing time and precision. We present a critical alternative vision based on the most recent literature. We discuss social relations along with strengths and weaknesses. Our critical analysis guides the reader to understand this paradigm in-depth and its impact on future technologies, i.e., artificial social intelligence. We also present the major ongoing research activities and highlight the most important technical and critical challenges associated with these objects, such as inter-object relations, support and definition of new communication primitives, and security and privacy concerns. © 2024 IEEE.

关键词： Secure relationships Secure social network analysis Security Social Network Analytics Social networks Trust

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A Novel Trajectory Planning Method Based on Trust Region Policy Optimization

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Ye, Bao-Lin Zhang, Jiajie Li, Lingxi Wu, Weimin Jiaxing Key Laboratory of Smart Transportations the School of Information Science and Engineering Jiaxing University China Elmore Family School of Electrical and Computer Engineering Purdue University Indianapolis USA State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Trajectory planning method is a research hotspot in autonomous driving. Existing reinforcement learning-based trajectory planning methods suffer from unstable performance due to the strong randomness of network weight parameter updates during the training process. Therefore, this paper proposes a novel trajectory planning method based on deep reinforcement learning trust region policy optimization (TRPO). Firstly, in order to enhance the robustness of the trajectory planning method based on deep reinforcement learning TRPO, a TRPO-LSTM based decision model was proposed. More specifically, a long short term memory (LSTM) based state feature extraction network was designed and embeded into a TRPO-based decision model to enhance the ability of TRPO to extract information from the environmental state space. Secondly, in order to make the planned trajectory adaptive to the dynamic changes of traffic environment, we presented a novel TRPO-LSTM trajectory fitting algorithm. To the best of our knowledge, this is the first work aiming at applying the TRPO-LSTM based decision model in the trajectory fitting process to search the optimal longitudinal trajectory speed. Finally, the proposed trajectory planning method was implemented and simulated on the CARLA simulator. The experimental results show that, compared with existing trajectory planning methods based on deep reinforcement learning algorithms, our proposed method achieves a cumulative reward improvement of over 28.9% in the scenario of four lane highway, and has better robustness. Meanwhile, the proposed method can achieve a lower collision rate of 0.93% while improving the average speed and comfort of vehicle driving. IEEE

关键词： Heuristic algorithms

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