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2024 China automation Congress, CAC 2024

作者： Luo, Jialei Liu, Wei Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350368604

This paper deals with the robust output voltage tracking problem with prescribed performance for single-phase voltage source uninterruptible power supply inverters. We construct two linear internal models to reproduce the steady-state information, based on which we transform our problem into the robust stabilization problem with prescribed performance of an augmented system. Then, we incorporate a novel error transformation into the existing framework for the robust output regulation problem to design a stabilization controller, based on which we synthesize our control law to make the tracking error converge to zero asymptotically while always satisfying the prescribed performance. © 2024 IEEE.

关键词： Uninterruptible power systems

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From animal collective behaviors to swarm robotic cooperation

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National Science Review 2023年第5期10卷 82-99页

作者： Haibin Duan Mengzhen Huo Yanming Fan State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng Laboratory AVIC Shenyang Aircraft Design and Research Institute

The collective behaviors of animals,from schooling fish to packing wolves and flocking birds,display plenty of fascinating phenomena that result from simple interaction rules among *** emergent intelligent properties of the animal collective behaviors,such as self-organization,robustness,adaptability and expansibility,have inspired the design of autonomous unmanned swarm *** article reviews several typical natural collective behaviors,introduces the origin and connotation of swarm intelligence,and gives the application case of animal collective *** this basis,the article focuses on the forefront of progress and bionic achievements of aerial,ground and marine robotics swarms,illustrating the mapping relationship from biological cooperative mechanisms to cooperative unmanned cluster ***,considering the significance of the coexisting-cooperative-cognitive human-machine system,the key technologies to be solved are given as the reference directions for the subsequent exploration.

关键词： collective behaviors swarm intelligence cooperative robotics swarm human-machine system

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Differentially Private Distributed Parameter Estimation

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Journal of systems Science & Complexity 2023年第1期36卷 187-204页

作者： WANG Jimin TAN Jianwei ZHANG Ji-Feng School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China

Data privacy is an important issue in control systems,especially when datasets contain sensitive information about *** this paper,the authors are concerned with the differentially private distributed parameter estimation problem,that is,we estimate an unknown parameter while protecting the sensitive information of each ***,the authors propose a distributed stochastic approximation estimation algorithm in the form of the differentially private consensus+innovations(DP-CI),and establish the privacy and convergence property of the proposed ***,it is shown that the proposed algorithm asymptotically unbiased converges in mean-square to the unknown parameter while differential privacy-preserving holds for finite number of ***,the exponentially damping step-size and privacy noise for DP-CI algorithm is *** estimate approximately converges to the unknown parameter with an error proportional to the step-size parameter while differential privacy-preserving holds for all *** tradeoff between accuracy and privacy of the algorithm is effectively ***,a simulation example is provided to verify the effectiveness of the proposed algorithm.

关键词： Differential privacy distributed parameter estimation stochastic approximation

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Consensus control of second-order stochastic discrete-time multi-agent systems without velocity transmission

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control Theory and technology 2023年第4期21卷 591-601页

作者： Zi-Xuan Wang Xiaofeng Zong Ling-Jie Gai School of Automation China University of GeosciencesWuhan430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubeiChina Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhanHubeiChina

This article studies the almost-sure and the mean-square consensus control problems of second-order stochastic discrete-time multi-agent systems with multiplicative ***,a control law based on the absolute velocity and relative position information is ***,considering the existence of multiplicative noises and nonlinear terms with Lipschitz constants,the consensus control problem is solved through the use of a degenerated Lyapunov ***,for the linear second-order multi-agent systems,some explicit consensus conditions are ***,two sets of numerical simulations are performed.

关键词： Consensus control Multiplicative noises Second-order Discrete-time Multi-agent system

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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

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engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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Exploring Image Generation for UAV Change Detection

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1061-1072页

作者： Xuan Li Haibin Duan Yonglin Tian Fei-Yue Wang Peng Cheng Laboratory Shenzhen 518000China IEEE State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083 Department of Automation University of Science and Technology of ChinaHefei 230027 State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense TechnologyChangsha 410073China

Change detection(CD)is becoming indispensable for unmanned aerial vehicles(UAVs),especially in the domain of water landing,rescue and ***,even the most advanced models require large amounts of data for model training and ***,sufficient labeled images with different imaging conditions are *** by computer graphics,we present a cloning method to simulate inland-water scene and collect an auto-labeled simulated *** simulated dataset consists of six challenges to test the effects of dynamic background,weather,and noise on change detection ***,we propose an image translation framework that translates simulated images to synthetic *** framework uses shared parameters(encoder and generator)and 22×22 receptive fields(discriminator)to generate realistic synthetic images as model training *** experimental results indicate that:1)different imaging challenges affect the performance of change detection models;2)compared with simulated images,synthetic images can effectively improve the accuracy of supervised models.

关键词： Change detection computer graphics image translation simulated images synthetic images unmanned aerial vehicles(UAVs)

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Deep Co-Training Partial Least Squares Model for Semi-Supervised Industrial Soft Sensing

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3363-3371页

作者： Zheng, Junhua Zhou, Le Ye, Lingjian Ge, Zhiqiang Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou310023 China Huzhou University Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems School of Engineering Huzhou313000 China Southeast University School of Mathematics Nanjing210096 China

Data-driven soft sensing has become quite popular in recent years, which can provide real-time estimations of key variables in industrial processes. While the introduction of deep learning does improve the prediction performance, it is highly restricted to the number of labeled training data, as well as large computational burden and cumbersome parameter tuning procedures. How to break through the bottleneck of data-drive models in terms of limited labeled data and high computational complexity should be one of the main recent focuses in the field of industrial soft sensing. In this article, a deep co-training PLS (deep CT-PLS) model is proposed to extend the ordinary PLS model to the semi-supervised deep form. While the deep model can efficiently extract inherent natures of process data, the co-training strategy makes lots of unlabeled data useful through a two-view cross training and annotation process. In this case, the performance restriction of the deep PLS model can be greatly relieved, with the incorporation of additional unlabeled data, while at the same time the designed model structure keeps in a low computational complexity. Based on the case study on a real industrial production process, the deep CT-PLS model can significantly improve the soft sensing performance. © 2013 IEEE.

关键词： Self-supervised learning

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An ensemble multivariate detection method for steady-state drift in process industries

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Science China(Information Sciences) 2025年

作者： Wenshuo SONG Weihua CAO Yan YUAN Wenkai HU School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

In process industries, it is crucial to maintain operational parameters within a designated steady-state operating point to ensure product quality and operational efficiency. However,steady-state drift(a gradual shift in key parameters occurs over time even when the system is intended to be under stable conditions) can lead to significant production losses,safety risks, and increased operational costs. Therefore, accurately detecting steady-state drift is essential for maintaining stable, safe, and optimized operating conditions.

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Optimal Cooperative Secondary control for Islanded DC Microgrids via a Fully Actuated Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 405-417页

作者： Yi Yu Guo-Ping Liu Yi Huang Peng Shi IEEE Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Electrical and Mechanical Engineering the University of AdelaideSA 5005Australia Research and Innovation Centre Obuda University1034 BudapestHungary

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

关键词： DC microgrids distributed control high-order fully actuated system approach linear quadratic regulator microgrid modeling secondary control

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Deterministic Learning-Based Robust Practical Output Regulation for Second-Order Nonlinear systems

Deterministic Learning-Based Robust Practical Output Regulat...

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2024 International Annual Conference on Complex systems and Intelligent Science, CSIS-IAC 2024

作者： Hu, Qingxi Liu, Wei Key Laboratory of Autonomous Systems and Networked Control of Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798331504755

This article intends to investigate the semi-global robust practical output regulation problem for a class of second-order nonlinear systems with parametric and non-parametric uncertainties based on deterministic learning method. First, by constructing the internal models, the robust output regulation problem is transformed into the semi-global robust practical stabilization problem. Second, we propose an adaptive neural control (ANC) strategy to solve the stabilization problem and utilize the radial basis function neural networks (RBF NNs) to identify unknown dynamic. Moreover, under the persistently exciting (PE) property, the unknown dynamics can be identified and the learned knowledge is saved as some constant NN weights. Finally, we design an deterministic learning-based adaptive neural control (DLANC) law with the learned knowledge to solve the output regulation problem and improve control performance. © 2024 IEEE.

关键词： Contrastive Learning

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