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第三十二届中国控制会议

作者： YANG Dapeng LIU Xiangdong LI Zhongkui GUO Yaohua Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781479900305

This paper considers the distributed attitude tracking problem of multiple spacecraft with disturbances and unknown inertia matrices. Based on the relative attitudes and angular velocities of neighboring spacecraft, we design a distributed robust controller to each follower to guarantee that the attitude errors between the followers and the leader converge to zero for any communication graph containing a directed spanning tree with the leader as the root. To deal with the problem of parameters uncertainties, we further propose a distributed adaptive sliding mode controller, under which the system is globally robust with respect to external disturbances and inertia matrices uncertainties.

关键词： Multiple Spacecraft, Sliding Mode Control, Attitude Tracking, Distributed Control, Adaptive Control

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Terrain Estimation and Strategy for Quadruped Robot Body Posture and COG Adjustment 28

Terrain Estimation and Strategy for Quadruped Robot Body Pos...

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第28届中国控制与决策会议

作者： HE Yudong WANG Junzheng KE Xianfeng WANG Shoukun Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467397155

Quadruped robot has gained its popularity due to the adaptation ability of rough *** improve the walking stability and balance of quadrupeds,separate static walking methods are discussed based on specific known *** some unknown terrains,a uniform terrain model is established in this paper.A fuzzy logic based terrain estimation method is then proposed to estimate the terrain *** on the criterion of maximum working space,a body posture and center of gravity(COG) position adjusting strategy is proposed,and a method to adjust the posture and COG position is derived based on the kinematic *** show that the proposed methods can deal with different terrains and body posture and COG position can be tuned according to the terrain.

关键词： Quadruped Robots Terrain Estimation Body Posture and COG adjustment

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Preface——Special Issue to Celebrate the 30th Anniversary of Journal of systems Science and complexity

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Journal of systems Science & complexity 2017年第1期30卷 1-3页

作者： GAO Xiao-Shan CHEN Jie SHAO Jun WANG Shouyang Academy of Mathematics and Systems Science Chinese Academy of Sciences Key Laboratory of Intelligent Control and Design of Complex Systems Beijing Institute of Technology Department of Statistics University of Wisconsin-Madison

This special issue is dedicated to the 30th anniversary of Journal of systems Science and complexity(JSSC)which is under the auspices of the Institute of systems Science,Chinese Academy of *** of systems Science,Chinese Academy of Sciences was established in 1979 by scientists Chao-Chih Kwan,Wen-Tsun Wu,Guo-Zhi *** 1981,the Journal of systems

关键词：系统科学复杂性杂志中国科学院序言科学研究所

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Distributed multiple model filtering for markov jump systems with communication delays

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Journal of the Franklin Institute 2023年第4期360卷 3407-3435页

作者： Li, Hui Yan, Liping Xia, Yuanqing Zhang, Jinhui the Key Laboratory of Intelligent Control Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

In this paper, we study a distributed state estimation problem for Markov jump systems (MJS) over sensor networks, in which each sensor node connects with each other through wireless networks with communication delays. We assume that each sensor node maintains a buffer to store delayed data transmitted from neighbor nodes. A distributed multiple model filter is designed by using the interacting multiple model methods (IMM) and a recursive delays compensation method. In order to ensure the stability, two stability conditions are derived for boundedness of estimation errors and boundedness of error covariance. Finally, the effectiveness of the proposed methods is illustrated by simulations and experiments of maneuvering target tracking. © 2022 The Franklin Institute

关键词： Sensor nodes

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Adaptive Backdoor Attacks with Reasonable Constraints on Graph Neural Networks

arXiv

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arXiv 2025年

作者： Dong, Xuewen Li, Jiachen Li, Shujun You, Zhichao Qu, Qiang Kholodov, Yaroslav Shen, Yulong School of Computer Science and Technology Xidian University The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education China The Shaanxi Key Laboratory of Blockchain and Secure Computing Xi’an710071 China University of Kent CanterburyCT2 7NP United Kingdom Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Intelligent Transportation Systems Lab Innopolis University Innopolis Russia School of Computer Science and Technology Xidian University China The Shaanxi Key Laboratory of Network and System Security Xi’an710071 China

Recent studies show that graph neural networks (GNNs) are vulnerable to backdoor attacks. Existing backdoor attacks against GNNs use fixed-pattern triggers and lack reasonable trigger constraints, overlooking individual graph characteristics and rendering insufficient evasiveness. To tackle the above issues, we propose ABARC, the first Adaptive Backdoor Attack with Reasonable Constraints, applying to both graph-level and node-level tasks in GNNs. For graph-level tasks, we propose a subgraph backdoor attack independent of the graph’s topology. It dynamically selects trigger nodes for each target graph and modifies node features with constraints based on graph similarity, feature range, and feature type. For node-level tasks, our attack begins with an analysis of node features, followed by selecting and modifying trigger features, which are then constrained by node similarity, feature range, and feature type. Furthermore, an adaptive edge-pruning mechanism is designed to reduce the impact of neighbors on target nodes, ensuring a high attack success rate (ASR). Experimental results show that even with reasonable constraints for attack evasiveness, our attack achieves a high ASR while incurring a marginal clean accuracy drop (CAD). When combined with the state-of-the-art defense randomized smoothing (RS) method, our attack maintains an ASR over 94%, surpassing existing attacks by more than 7%. Copyright © 2025, The Authors. All rights reserved.

关键词： Graph neural networks

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An Overview of Distributed High-order Multi-agent Coordination

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IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 1-9页

作者： Jie Huang Hao Fang Lihua Dou Jie Chen the School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems the Fujian Institute of Education

Research on multi-agent systems has attracted much attention in the past two decades, and numerous results have been obtained. Its widespread applications include spacecraft,mobile robots, sensor networks, etc. Most previous research works on multi-agent systems studied the first- and second-order dynamics. However, in engineering, many systems are modeled by higher-order dynamics. This paper reviews the major results and progress in distributed high-order multi-agent *** the review, a short discussion section is included to summarize the existing research and propose several promising research directions along with some open problems that are deemed important for further investigations.

关键词： Multi-agent systems Protocols Linear systems Nonlinear systems Heuristic algorithms Laplace equations

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Set stability for switched Boolean networks with open-loop and closed-loop switching signals

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Science China(Information Sciences) 2018年第9期61卷 232-240页

作者： Xiaohua LI Jianquan LU Jianlong QIU Xiangyong CHEN Xiaodi LI Fuad E.ALSAADI School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University School of Mathematics and Statistics Shandong Normal University School of Mathematics Southeast University Department of Electrical and Computer Engineering King Abdulaziz University

This paper mainly analyzes the set stability of switched Boolean networks(SBNs) by considering two different methods of switching signals in the form of open-loop and closed-loop switching. First, the definitions of set stability are proposed for SBNs with such switching signals. Then, we propose two different algorithms to find the largest open-loop switching invariant set and largest closed-loop switching invariant set. Furthermore, the corresponding set stability conditions for SBNs are given in each case. In addition,the constructive procedures are presented to design the switching signal sequence to achieve set stability under the two different methods of switching signals. Finally, the effectiveness of the proposed algorithms and research results are demonstrated using two numerical examples.

关键词： switched Boolean network set stability semi-tensor product switching signal design

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Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection

arXiv

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arXiv 2025年

作者： Li, Yong Liu, Menglin Cui, Zhen Ding, Yi Zong, Yuan Zheng, Wenming Shan, Shiguang Guan, Cuntai School of Computer Science and Engineering The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Nanjing210096 China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China School of Artificial Intelligence Beijing Normal University Beijing100875 China Key Laboratory of AI Safety Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Key Laboratory of Child Development and Learning Science of Ministry of Education School of Biological Science and Medical Engineering Nanjing210096 China

Despite the impressive performance of current vision-based facial action unit (AU) detection approaches, they are heavily susceptible to the variations across different domains and the cross-domain AU detection methods are under-explored. In response to this challenge, we propose a decoupled doubly contrastive adaptation (D2CA) approach to learn a purified AU representation that is semantically aligned for the source and target domains. Specifically, we decompose latent representations into AU-relevant and AU-irrelevant components, with the objective of exclusively facilitating adaptation within the AU-relevant subspace. To achieve the feature decoupling, D2CA is trained to disentangle AU and domain factors by assessing the quality of synthesized faces in cross-domain scenarios when either AU or domain attributes are modified. To further strengthen feature decoupling, particularly in scenarios with limited AU data diversity, D2CA employs a doubly contrastive learning mechanism comprising image and feature-level contrastive learning to ensure the quality of synthesized faces and mitigate feature ambiguities. This new framework leads to an automatically learned, dedicated separation of AU-relevant and domain-relevant factors, and it enables intuitive, scale-specific control of the cross-domain facial image synthesis. Extensive experiments demonstrate the efficacy of D2CA in successfully decoupling AU and domain factors, yielding visually pleasing cross-domain synthesized facial images. Meanwhile, D2CA consistently outperforms state-of-the-art cross-domain AU detection approaches, achieving an average F1 score improvement of 6%-14% across various cross-domain scenarios. © 2025, CC BY-NC-SA.

关键词： Contrastive Learning

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A perturbation method to the tent map based on Lyapunov exponent and its application

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Chinese Physics B 2015年第10期24卷 78-85页

作者：曹绿晨罗玉玲丘森辉刘俊秀 Guangxi Key Laboratory of Multi-source Information Mining & Security Faculty of Electronic EngineeringGuangxi Normal University School of Computing and Intelligent Systems University of Ulster

Perturbation imposed on a chaos system is an effective way to maintain its chaotic features. A novel parameter perturbation method for the tent map based on the Lyapunov exponent is proposed in this paper. The pseudo-random sequence generated by the tent map is sent to another chaos function - the Chebyshev map for the post processing. If the output value of the Chebyshev map falls into a certain range, it will be sent back to replace the parameter of the tent map. As a result, the parameter of the tent map keeps changing dynamically. The statistical analysis and experimental results prove that the disturbed tent map has a highly random distribution and achieves good cryptographic properties of a pseudo-random sequence. As a result, it weakens the phenomenon of strong correlation caused by the finite precision and effectively compensates for the digital chaos system dynamics degradation.

关键词： perturbation tent map Lyapunov exponent finite precision

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Simplified outlier detection for improving the robustness of a fuzzy model

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Science China(Information Sciences) 2020年第4期63卷 218-220页

作者： Yali JIN Weihua CAO Min WU Yan YUAN School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,Fuzzy models have been widely employed in various fields, such as complex industrial process modeling, classification, function approximation, and time series prediction. Extracting fuzzy rules is very important as they determine the capabilities of the fuzzy model. In recent years, data-based methods such as fuzzy clustering, genetic algorithm, and neural networks [1–3], have been pro-

关键词： Simplified outlier detection for improving the robustness of a fuzzy model Gaussian

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