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Sensor and Filter Attacks Against Distributed State Estimation with Dual Stealthiness

IEEE Transactions on Automatic Control 2024年

作者： Jin, Kaijing Ye, Dan The College of Information Science and Engineering Northeastern University Shenyang110819 China The State Key Laboratory of Synthetical Automation of Process Industries Northeastern University Shenyang110819 China

To reveal the security vulnerabilities of distributed estimation systems, we investigate the existence of false data injection attacks in this paper, where attacks can corrupt sensor data and filter data. Considering the innovation-based and consensus-based strict stealthiness, a successful attack should ensure the divergence of each local estimation and not affect innovation and consensus signals. By analyzing the null space of system matrices, the necessary and sufficient conditions for the existence of attacks with such dual strict stealthiness are derived. Furthermore, if attacks can only destroy filter or sensor data, we discuss the existence of filter attacks and obtain that there is no strictly stealthy sensor attack to cause divergent estimation. By introducing a relaxed dual stealthiness constraint, the corresponding existence condition of sensor attacks is developed. Based on the given attack existence conditions, some data protection strategies are offered to defend against the threat of attacks. Simulations are conducted to demonstrate the effectiveness of the theoretical results. ©1963-2012 IEEE.

关键词： consensus-based stealthiness Distributed state estimation false data injection attacks innovation-based stealthiness

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Low-Overhead Time Synchronization for Energy-Constraint Industrial Internet of Things 6

Low-Overhead Time Synchronization for Energy-Constraint Indu...

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6th International Symposium on Autonomous Systems, ISAS 2023

作者： Liu, Shuxin Dai, Xuewu Zong, Yan Jia, Zhian Zhou, Dong Cui, Dongliang Northeastern University The State Key Laboratory of Synthetical Automation for Process Industries Shenyang China Northumbria University Faculty of Engineering and Environment Newcastle upon TyneNE1 8ST United Kingdom Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing China Qiqihar Heavy Cnc Equipment.Ltd Qiqihar China

ISBN: (纸本)9798350316155

Time synchronization is of significance in the Industrial Internet of Things (IIoT). For the impact of energy-constrained batteries for power in IIoT, a novel low-overhead time synchronization algorithm via one-way single packet exchange, i.e., improved packet-coupled oscillators (I-PkCOs), is proposed in this paper, which mainly consists of time-information packet exchange protocol according to a time-division multiple access scheme and an adaptive proportional-integral feedback clock adjustment algorithm. For clock adjustment, a proportional-integral controller is used to generate the clock adjustment amount and an adaptive algorithm is introduced to adjust the clock offset first and the clock skew later. This algorithm schedules Sync packets to be transmitted in different time slots, which can avoid packet collision and channel sniffing. Moreover, a node only needs to send one Sync packet per synchronization cycle, which effectively reduces the communication overhead and energy consumption. Hardware experiments on the SAM R21 board of processing the 32.768 MHz oscillator show that the proposed method reduces packet transmission by 50% compared to the Time synchronization Protocol for Sensor Networks (TPSN). Moreover, it has better synchronization accuracy and stability than the Packet-Coupled Oscillators (PkCOs) protocol and PISync algorithm and can achieve 1.61μs synchronization accuracy in a single-cluster network. © 2023 IEEE.

关键词： Time division multiple access

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Energy-efficient Hot-rolling Scheduling of High-quality Steel Products

Energy-efficient Hot-rolling Scheduling of High-quality Stee...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Zhao, Ziyan Bian, Zikuo Wang, Chenglong Zou, Kun Liu, Shixin College of Information Science and Engineering Northeastern University Shenyang110819 China Shandong Iron & Steel Group Rizhao Co. Ltd Rizhao276800 China The State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China

ISBN: (纸本)9781665430654

Steel production involves many energy-intensive processes. Under the goal of carbon peak and carbon neutrality, it is essential to study the steel production scheduling problems aiming at energy saving to realize the green manufacturing of steel production processes. Aiming at the hot rolling process of high-quality steel products, a novel energy-saving production scheduling problem is studied in this paper. Unlike existing research, this paper additionally considers temperature constraints and the optimization of temperature-keeping equipment assignment in producing high-quality steel products. To solve it efficiently, this paper presents an improved simulated annealing algorithm where destruction and construction strategies from iterated greedy algorithms are embedded into it. Experimental results show that the presented algorithm has obvious advantages compared with other competitive peers. Its excellent solution performance means its great application potential. © 2023 IEEE.

关键词： destruction and construction Green manufacturing production scheduling simulated annealing algorithm temperature-keeping equipment assignment

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RIS-assisted Channel Prediction Model for Mine V2X Systems

RIS-assisted Channel Prediction Model for Mine V2X Systems

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Computer, Big Data and Artificial Intelligence (ICCBD+AI), International Conference on

作者： Yuanxun Cheng Qingsong Hu Yujia Luo Yuansheng Zhang School of Information and Control Engineering China University of Mining and Technology Xuzhou China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China

ISBN: (数字)9798331533991

ISBN: (纸本)9798331534004

The complex and dynamic environment of mines leads to time-variability and uncertainty in channel propagation, which affects the stability and reliability of Vehicle-to-Everything (V2X)communication in mine networks. Channel prediction can help mitigate these issues. Introducing reconfigurable intelligence surface (RIS) into the mine V2X system can enhance signal coverage and quality in the complex mine environment. To address the issue of long-term error accumulation in existing channel prediction models, this paper analyzes the prediction error of channel state information (CSI) in mine V2X systems. It was observed that the error distribution exhibits characteristics of an approximate normal distribution, revealing its predictability. Utilizing this characteristic, this paper proposes an error correction strategy to suppress long-term error accumulation during the prediction process. Furthermore, an adaptive method for optimizing RIS phases is designed based on the Snow Ablation Optimizer. Specifically, this paper utilizes a metaheuristic optimization algorithm and deep learning techniques to propose a mine V2X channel prediction model that incorporates the error correction strategy. Experimental results show that optimizing the RIS phase can effectively enhance channel gain, and the mine V2X channel prediction model incorporating the error correction strategy can effectively suppress cumulative errors during the prediction process, thereby improving prediction accuracy.

关键词： Deep learning Adaptation models Accuracy Predictive models Reconfigurable intelligent surfaces Gaussian distribution Prediction algorithms Approximation algorithms Error correction Vehicle-to-everything

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Data-driven fault-tolerant consensus control for constrained nonlinear multiagent systems via adaptive dynamic programming

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Information Sciences 2025年 705卷

作者： Zhang, Lulu Zhang, Huaguang Wang, Tianbiao Yue, Xiaohui College of Information Science and Engineering Northeastern University Liaoning Shenyang110004 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Liaoning Shenyang110004 China

In this paper, a data-driven fault-tolerant control (FTC) method is proposed to solve the consensus problem of constrained multiagent systems (MASs) with denial-of-service attacks. First, a resilient distributed observer is introduced to extract the leader's state in real-time for each follower, even in the presence of attacks. A nonlinear mapping is employed to transform the original system with state constraints into an equivalent constraint-free system, ensuring that the original system's states remain within prescribed limits. Then, an adaptive dynamic programming (ADP)-based FTC scheme is designed for the system to mitigate the effects of actuator faults, enabling the nominal system to balance cost and performance. The ADP algorithm is implemented using an actor-critic structure to solve the Hamilton-Jacobi-Bellman equation based on system data collected via the least-squares method. In this framework, the designed controller is data-driven rather than reliant on precise system information, which broadens the controller's applicability to systems with unknown dynamics. Finally, the effectiveness of the established controller is validated through two examples. © 2025

关键词： Dynamic programming

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Physics-guided graph learning soft sensor for chemical processes

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Chemometrics and Intelligent laboratory Systems 2024年 249卷

作者： Liu, Yi Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Chemical Engineering National Tsing Hua University Hsinchu300044 Taiwan

The surge in data-driven soft sensors for industrial processes is evident. However, most of them suffer from the limitation of being black-box models and this will hamper their widespread use. In response to this challenge, this study proposes a physics-guided graph-learning soft sensor that integrates a physical understanding of industrial processes by incorporating graph-based concepts with process physics. The soft sensor first constructs physical information based on causal relationships between variables using the conditional Granger causality test. Subsequently, it autonomously learns the unique sample information of each observation while employing a regularization loss to ensure the sparsity of the learned information. The model employs a two-stream structure for spatiotemporal encoding of both the physical and sample information. The modeling and prediction results on a penicillin fermentation process indicate that, using the proposed method, the knowledge gained from the data aligns with existing prior knowledge. This approach shows promise in filling the gap between data-driven and physics-based modeling in chemical processes. © 2024 Elsevier B.V.

关键词： Graphic methods

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Tracking performance limitations of MIMO discrete-time networked control systems with multiple constraints

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Science China(Information Sciences) 2023年第8期66卷 267-268页

作者： Xiaowei JIANG Bin ZHANG Xiangyong CHEN Huaicheng YAN School of Automation China University of Geosciences Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation and Electrical Engineering Linyi University Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education

Dear editor,Networked control systems(NCSs) have attracted widespread attention in some fields because they offer the advantages of reduced cabling, greater resource sharing,and ease of installation and maintenance [1]. However, in an unreliable network environment, network constraints can significantly limit the performance of NCSs.

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Design of Acquisition System Based on RGB-D-T Multi-Modal Images and Research on Alignment Techniques

Design of Acquisition System Based on RGB-D-T Multi-Modal Im...

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IEEE International Conference on Cyber Technology in automation, Control, and Intelligent Systems

作者： Yunhe Wu Tong Jia Bi Yang Wenhao Li Tao Yang Information Science and Engineering Northeastern University Shenyang China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Multimodal information fusion has become a research hotspot in the field of computer vision, especially RGB-D-T multimodal information can effectively improve the system's ability to perceive the environment, and then better accomplish the tasks of recognition, segmentation, and classification. In order to obtain more accurate RGB-D-T multimodal information, this paper proposes a multimodal image alignment and image enhancement method. Firstly, we build a RGB-D-T multimodal imaging system. Considering the problem of noise and holes in the original depth image, the IWJBF algorithm was proposed for depth image denoising. Meanwhile, in order to obtain clearer thermal infrared images, we further performed image enhancement on the original thermal infrared images. Finally, based on the internal and external parameters of the three modal cameras, the projection transformation algorithm is used to unify the three modal information into the same coordinate system to obtain accurate RGB-D-T alignment results.

关键词： Training Image segmentation Accuracy Image color analysis Noise reduction Cameras Information filters Intelligent systems Image enhancement Image denoising

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Optimal Control for Complex Systems

Optimal Control for Complex Systems

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第35届中国控制与决策会议

作者： Haoyan Zhang Yingwei Zhang Dan Ma School of Information Science and Engineering Northeastern University State Laboratory of Synthesis Automation of Process Industry Northeastern University

In this article,the adaptive optimal control problem for a class of switched nonlinear systems with Bouc-Wen hysteresis input is *** establishing an actor-critic(AC) dual networks architecture,the solution of the HamiltonJacobi-Bellman equation can be approximately ***,an adaptive AC optimal controller is designed,in which the actor and critic updating laws are synchronously tuned,rather than tuned *** on the Lyapunov extension theorem,All signals of the closed-loop system are proved to be bounded in the sense of uniformly ultimate boundedness(UUB).Finally,the efficacy of the proposed optimal control method is demonstrated via a practical inverted pendulum system.

关键词： actor-critic architecture adaptive optimal control switched nonlinear systems Bouc-Wen hysteresis input

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A Secure Transmission and Attack Detection Approach Based on Autoencoder

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IEEE Transactions on Network Science and engineering 2025年

作者： Ma, Zhen-Lei Li, Xiao-Jian Northeastern University College of Information Science and Engineering Liaoning Shenyang110819 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110819 China

This paper is concerned with the secure transmission and attack detection problem for cyber-physical systems with unknown dynamic matrices. The signals transmitted between physical and cyber layers can be eavesdropped and injected with the false data by adversary, which causes the information leakage and performance degradation. To tackle this problem, an integrated secure transmission and attack detection framework is proposed. The system information is first hidden as latent variables for secure transmission without information loss by using the designed stable image representation-aided autoencoder. Moreover, to further enhance the security of transmission, the chaotic oscillators are also embedded as a supplement. Then, an attack detector is designed based on the residual generated from the original data and the reconstructed data. Compared with the existing results, the proposed method shows better encoding ability and detection performance. Furthermore, the attack types are further analyzed and identified by using an explainable artificial intelligence technique. Finally, two examples are given to show the effectiveness of the proposed defense method. © 2013 IEEE.

关键词： Information leakage

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