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Innate Cyber-Immunity and Acquired Cyber-Immunity across Multi-Area Power systems

IEEE Transactions on Power systems 2025年

作者： Hou, Jiazuo Song, Yue Hou, Yunhe Peng, Jimmy Chih-Hsien National University of Singapore Department of Electrical and Computer Engineering Singapore Tongji University Department of Control Science and Engineering National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology Shanghai201804 China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518057 China

Organisms have evolved innate and acquired immune systems to defend against pathogens like coronaviruses. Similarly, power networks, threatened by cyber-attacks, desire cyber-immunity. Inspired by the immunology research, this study develops a cyber-immune strategy-characterizing innate cyber-immunity and establishing acquired cyber-immunity-for any selected portion of a power network (termed as power subnetwork) against stealthy false data injection (FDI) cyberattacks. Therein, without extrinsic protection and information asymmetry, this paper for the first time confirms the existence and provides closed-form conditions for power subnetworks that are innately immune to FDI cyber-attacks despite all measurements being compromised. Single-leader-multi-follower bi-level optimization models are then developed to strategically allocate measurement protection, leading to the acquired cyber-immunity, whose conditions for existence and the least cost are explicitly formulated. More importantly, a bi-directional cyber-immunity propagation mechanism is presented to provide the optimal spatial allocation of defense resources across adjacent subnetworks. It also explicitly determines the temporal allocation sequence, revealing its sequential and cumulative impacts on establishing cyber-immunity. This is achieved by designing recursive traversal algorithms, one of which is modelled as a post-order depth-first-search problem of a multi-fork tree. The proposed subnetwork-specific cyber-immune strategy is verified in a modified Australian National Electricity Market. © 1969-2012 IEEE.

关键词： Phishing

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Topology-Driven Attribute Recovery for Attribute Missing Graph Learning in Social Internet of Things

arXiv

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arXiv 2025年

作者： Li, Mengran Chen, Junzhou Yu, Chenyun Jiang, Guanying Zhang, Ronghui Shen, Yanming Song, Houbing Herbert School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen518107 China The Baidu Inc. Beijing100085 China The Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education The School of Electronic Information and Electrical Engineering Dalian University of Technology Dalian116024 China Department of Information Systems University of Maryland Baltimore County BaltimoreMD21250 United States

With the advancement of information technology, the Social Internet of Things (SIoT) has fostered the integration of physical devices and social networks, deepening the study of complex interaction patterns. Text Attribute Graphs (TAGs) capture both topological structures and semantic attributes, enhancing the analysis of complex interactions within the SIoT. However, existing graph learning methods are typically designed for complete attributed graphs, and the common issue of missing attributes in Attribute Missing Graphs (AMGs) increases the difficulty of analysis tasks. To address this, we propose the Topology-Driven Attribute Recovery (TDAR) framework, which leverages topological data for AMG learning. TDAR introduces an improved pre-filling method for initial attribute recovery using native graph topology. Additionally, it dynamically adjusts propagation weights and incorporates homogeneity strategies within the embedding space to suit AMGs’ unique topological structures, effectively reducing noise during information propagation. Extensive experiments on public datasets demonstrate that TDAR significantly outperforms state-of-the-art methods in attribute reconstruction and downstream tasks, offering a robust solution to the challenges posed by AMGs. The code is available at https://***/limengran98/TDAR. © 2025, CC BY.

关键词： Graph neural networks

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Dual-beam photothermal material trace detection method based on self-mixing interference

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Applied Optics 2025年第16期64卷 4549-4558页

作者： Yan Zhao Yunlong Zhi Hui Zhao Daming Dong Jigang Tong Chunling Tu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria 0188 South Africa

In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod excitation, and the refractive index changes cause the deviation of the probe beam, and the self-mixing interference (SMI) effect occurs when the modulated light returns to the cavity. By combining theoretical and experimental results, the power fluctuation of the SMI signal caused by the thermo-optic effect is linearly related to CV concentration and other parameters. At an excitation power of 24 mW, the detection limit can reach $8.0 \times {10^{- 8}}\;{\rm mol/L}$ . This method does not require labeling or complex CV pretreatment and has high sensitivity and flexibility, providing a guide for CV characterization in biological, environmental, and pharmaceutical research.

关键词： Gaussian beams Laser beams Optical fields Phase shift Refractive index Spatial resolution

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PTRL: Prior Transfer Deep Reinforcement Learning for Legged Robots Locomotion

arXiv

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arXiv 2025年

作者： Huang, Haodong Sun, Shilong Zhao, Zida Huang, Hailin Shen, Changqing Xu, Wenfu School of Robotics and Advanced Manufacturing Harbin Institute of Technology Shenzhen518055 China School of Rail Transportation Soochow University Suzhou215006 China Suzhou Boyata Industrial Internet Company Ltd. Suzhou215100 China Key University Laboratory of Mechanism and Machine Theory and Intelligent Unmanned Systems of Guangdong Guangdong Shenzhen518055 China

In the field of legged robot motion control, reinforcement learning (RL) holds great promise but faces two major challenges: high computational cost for training individual robots and poor generalization of trained models. To address these problems, this paper proposes a novel framework called Prior Transfer Reinforcement Learning (PTRL), which improves both training efficiency and model transferability across different robots. Drawing inspiration from model transfer techniques in deep learning, PTRL introduces a fine-tuning mechanism that selectively freezes layers of the policy network during transfer, making it the first to apply such a method in RL. The framework consists of three stages: pre-training on a source robot using the Proximal Policy Optimization (PPO) algorithm, transferring the learned policy to a target robot, and fine-tuning with partial network freezing. Extensive experiments on various robot platforms confirm that this approach significantly reduces training time while maintaining or even improving performance. Moreover, the study quantitatively analyzes how the ratio of frozen layers affects transfer results, providing valuable insights into optimizing the process. The experimental outcomes show that PTRL achieves better walking control performance and demonstrates strong generalization and adaptability, offering a promising solution for efficient and scalable RL-based control of legged robots. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Integrating mobile and fixed monitoring data for high-resolution PM2.5 mapping using machine learning

arXiv

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arXiv 2025年

作者： Xu, Rui Yao, Dawen Pian, Yuzhuang Cao, Ruhui Fu, Yixin Yang, Xinru Gan, Ting Liu, Yonghong School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China Guangdong Provincial Key Laboratory of Intelligent Transportation System Sun Yat-Sen University Guangzhou510275 China Guangdong Provincial Engineering Research Center for Traffic Environmental Monitoring and Control Guangdong Guangzhou510275 China

Constructing high resolution air pollution maps at lower cost is crucial for sustainable city management and public health risk assessment. However, traditional fixed-site monitoring lacks spatial coverage, while mobile low-cost sensors exhibit significant data instability. This study integrates PM2.5 data from 320 taxi-mounted mobile low-cost sensors and 52 fixed monitoring stations to address these limitations. By employing the machine learning methods, an appropriate mapping relationship was established between fixed and mobile monitoring concentration. The resulting pollution maps achieved 500-meter spatial and 5-minute temporal resolutions, showing close alignment with fixed monitoring data (+4.35% bias) but significant deviation from raw mobile data (-31.77%). The fused map exhibits the fine-scale spatial variability also observed in the mobile pollution map, while showing the stable temporal variability closer to that of the fixed pollution map (fixed: 1.12±0.73%, mobile: 3.15±2.44%, mapped: 1.01±0.65%). These findings demonstrate the potential of large-scale mobile low-cost sensor networks for high-resolution air quality mapping, supporting targeted urban environmental governance and health risk mitigation. © 2025, CC BY.

关键词： Environmental monitoring

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A Tutorial on Quantized Feedback control

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 5-17页

作者： Minyue Fu IEEE the School of System Design and Intelligent Manufacturing Shenzhen Key Laboratory of Control Theory and Intelligent Systems and Centre for Control Science and TechnologySouthern University of Science and TechnologyShenzhen 518055China

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

关键词： Consensus control high-precision control networked control quantized estimation quantized feedback control robust control

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Polytope Volume Monitoring Problem: Formulation and Solution via Parametric Linear Program Based control Barrier Function

arXiv

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arXiv 2025年

作者： Wu, Shizhen Dong, Jinyang Fang, Xu Sun, Ning Fang, Yongchun Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300353 China The Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China

Motivated by the latest research on feasible space monitoring of multiple control barrier functions (CBFs) as well as polytopic collision avoidance, this paper studies the Polytope Volume Monitoring (PVM) problem, whose goal is to design a control law for inputs of nonlinear systems to prevent the volume of some state-dependent polytope from decreasing to zero. Recent studies have explored the idea of applying Chebyshev ball method in optimization theory to solve the case study of PVM;however, the underlying difficulties caused by nonsmoothness have not been addressed. This paper continues the study on this topic, where our main contribution is to establish the relationship between nonsmooth CBF and parametric optimization theory through directional derivatives for the first time, so as to solve PVM problems more conveniently. In detail, inspired by Chebyshev ball approach, a parametric linear program (PLP) based nonsmooth barrier function candidate is established for PVM, and then, sufficient conditions for it to be a nonsmooth CBF are proposed, based on which a quadratic program (QP) based safety filter with guaranteed feasibility is proposed to address PVM problems. Finally, a numerical simulation example is given to show the efficiency of the proposed safety filter. © 2025, CC BY.

关键词： Chebyshev filters

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Brockett's Second Example:A FAS Approach Treatment

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Journal of systems Science & Complexity 2023年第5期36卷 1789-1808页

作者： DUAN Guang-Ren Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055China Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China

In this paper,several equivalent forms of the well-known Brockett's second example system are firstly *** stabilization of the system is then treated in the fully actuated system approach.A simple continuous time-invariant sub-stabilizing controller is designed,and the corresponding region of attraction is *** a result,all trajectories of the system starting from the characterized region of attraction are driven exponentially to the *** the region of attraction is very large,the designed sub-stabilizing controller can be directly useful in many practical *** cases where the initial values are indeed needed to be chosen out of the region of attraction,extremely simple pre-controllers can be designed,which drive the system trajectories into the designed region of attraction.A simulation of the designed control system is carried out to show the effect of the proposed approach.

关键词： Brockett integrator continuous time-invariant controllers fully actuated system approach region of attraction sub-stabilization

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High-Order Fully Actuated System Models for Strict-Feedback systems With Increasing Dimensions

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2451-2462页

作者： Xiang Xu Guang-Ren Duan Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055 the School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China

This paper mainly addresses control problems of strict-feedback systems(SFSs)with increasing *** with the commonly-considered SFSs where the subsystems have the same dimension,we aim to handle more complex cases,i.e.,the subsystems in the considered SFSs are assumed to have increasing *** transforming the systems into highorder fully-actuated system(HOFAS)models,the stabilizing controllers can be directly *** first-order SFSs,secondorder and high-order SFSs are also considered.

关键词： Increasing dimensions high-order fully-actuated system nonlinear systems strict-feedback systems

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Optimal Sensor Placement Using Combinations of Hybrid Measurements for Source Localization

arXiv

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arXiv 2025年

作者： Tang, Kang Xu, Sheng Yang, Yuqi Kong, He Ma, Yongsheng Shenzhen China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Computer Science University of Nottingham Nottingham United Kingdom Shenzhen Key Laboratory of Control Theory and Intelligent Systems SUSTech Shenzhen China

This paper focuses on static source localization employing different combinations of measurements, including time-difference-of-arrival (TDOA), received-signal-strength (RSS), angle-of-arrival (AOA), and time-of-arrival (TOA) measurements. Since sensor-source geometry significantly impacts localization accuracy, the strategies of optimal sensor placement are proposed systematically using combinations of hybrid measurements. Firstly, the relationship between sensor placement and source estimation accuracy is formulated by a derived Cramér-Rao bound (CRB). Secondly, the A-optimality criterion, i.e., minimizing the trace of the CRB, is selected to calculate the smallest reachable estimation mean-squared-error (MSE) in a unified manner. Thirdly, the optimal sensor placement strategies are developed to achieve the optimal estimation bound. Specifically, the specific constraints of the optimal geometries deduced by specific measurement, i.e., TDOA, AOA, RSS, and TOA, are found and discussed theoretically. Finally, the new findings are verified by simulation studies. Copyright © 2025, The Authors. All rights reserved.

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