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Adaptive dynamic surface control for quadrotor-slung load transportation system with uncertainties

Science China(Technological Sciences) 2023年第10期66卷 2917-2929页

作者： DING Feng HUANG Jian SUN Chong AI Yong XU WenXia YANG ChenGuang School of Computer Science South-Central Minzu UniversityWuhan 430074China Key Laboratory of Ministryof EducationforImage Processing and Intelligent ControlHubei Key Laboratoryof Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Engineering Wuhan Institute of TechnologyWuhan 430205China Key Laboratory of Ministry of Education for Autonomous Systems and Networked Control Guangdong Engineering Technology Research Center of Control of Intelligent SystemsCollege of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Quadrotors play a significant role in our lives and are transforming our *** cable-suspended loads is an unavoidable quadrotor application trend and a hot research topic in the control ***,the load swing and unpredictability pose significant challenges to the quadrotor's *** this paper,an anti-swing controller with an inner-outer control strategy for the quadrotor-slung load transportation system is *** facilitate the controller design,the outer position dynamics are restructured in the form of ***,a virtual controller is created to force the underactuated states to the dynamic surface to ensure the position subsystem's *** improve robustness,an adaptive law is used to eliminate the effects of uncertain cable ***,a dynamic surface controller for the inner attitude subsystem is presented to drive the actual force to the virtual *** is demonstrated that the control strategy can stabilize the quadrotor despite mass and cable length *** results are provided to demonstrate the efficacy and durability of the proposed method.

关键词： quadrotor-slung load transportation system dynamic surface control adaptive law cascade system model uncertainties

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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Computational Experiments for Complex Social systems:Experiment Design and Generative Explanation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1022-1038页

作者： Xiao Xue Deyu Zhou Xiangning Yu Gang Wang Juanjuan Li Xia Xie Lizhen Cui Fei-Yue Wang the School of Computer Software College of Intelligence and ComputingTianjin UniversityTianjin 300350China the School of Software and the Joint SDUNTU Centre for Artificial Intelligence Research(C-FAIR) Shandong UniversityJinan 250101China the Information School Xi’an University of Financial and EconomicsXi’an 710100China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Hainan University Haikou 570228China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 1001901China

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system *** address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating ***,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

关键词： Agent-based modeling computational experiments cyber-physical-social systems(CPSS) generative deduction generative experiments meta model

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Deep Learning-based Moving Object Segmentation:Recent Progress and research Prospects

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Machine Intelligence research 2023年第3期20卷 335-369页

作者： Rui Jiang Ruixiang Zhu Hu Su Yinlin Li Yuan Xie Wei Zou College of Information Engineering Shanghai Maritime UniversityShanghai201306China School of Computer Science and Technology East China Normal UniversityShanghai200062China Research Center of Precision Sensing and Control Institute of AutomationChinese Academy of SciencesBeijing100190China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China

Moving object segmentation(MOS),aiming at segmenting moving objects from video frames,is an important and challenging task in computer vision and with various *** the development of deep learning(DL),MOS has also entered the era of deep models toward spatiotemporal feature *** paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three ***,we present a more up-to-date categorization based on model characteristics,then compare and discuss each category from feature learning(FL),and model training and evaluation *** FL,the methods reviewed are divided into three types:spatial FL,temporal FL,and spatiotemporal FL,then analyzed from input and model architectures aspects,three input types,and four typical preprocessing subnetworks are *** terms of training,we discuss ideas for enhancing model *** terms of evaluation,based on a previous categorization of scene dependent evaluation and scene independent evaluation,and combined with whether used videos are recorded with static or moving cameras,we further provide four subdivided evaluation setups and analyze that of reviewed *** also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of ***,based on the above comparisons and discussions,we present research prospects and future directions.

关键词： Moving object segmentation(MOS) change detection background subtraction deep learning(DL) video understanding

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A LESO Based Backstepping controller Considering Coal Seam Hardness for Rotary Speed in Coal Mine Tunnel Drilling Process

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Journal of systems Science & Complexity 2024年第5期37卷 1789-1808页

作者： CHEN Luefeng LIU Xiao WU Min LU Chengda PEDRYCZ Witold HIROTA Kaoru School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R2G7Canada The Tokyo Institute of Technology Yokohama 226-8502Japan

In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of *** this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary ***,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is *** an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam *** on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary ***,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.

关键词： Backstepping extended state observer hydraulic tunnel drilling machine rotary speed

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Collaborative Decision-Making Processes Analysis of Service Ecosystem: A Case Study of Academic Ecosystem Involution 19th

Collaborative Decision-Making Processes Analysis of Service ...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Yan, Xiangpei Xue, Xiao Peng, Chao Liu, Donghua Feng, Zhiyong Xiao, Wang School of Computer Software College of Intelligence and Computing Tianjin University Tianjin China China Waterborne Transport Research Institute Tianjin China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783031545306

With the collaboration of several intelligent services, a crowd intelligence service network has been formed, and a service ecosystem has gradually emerged. As a novel service organization model, the Service Ecosystem (SE) can provide more sophisticated, precise, and thorough services and has attracted widespread attention. However, it also brings negative effects such as involution, and information cocoon room. Thus, how to analyze the collaborative decision-making mechanism between the SE regulation algorithm and the crowd intelligence group, exploring the reasons behind the negative effects, and finding effective intervention strategies have become problems in this field. To solve the challenges, we propose a Computational Experiments-based method Decision-making processes Analysis model in SE, namely CEDA. The proposed CEDA model consists of three modules: the autonomous evolution mechanism module, the learning evolution mechanism module, and the collaborative decision-making analysis module. Among them, the computational experiments can provide a customized test environment for the analysis of collaborative decision-making processes and find out the appropriate intervention strategy. Finally, the validity of the CEDA model is verified through the case of academic ecosystem involution. The results show that computational experiments can provide new ideas and paths for collaborative decision-making processes analysis. © ICST institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Ecosystems

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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Robust control of Feeding Speed for Coal Mine Tunnel Drilling Machines 25

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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Toward parallel intelligence: An interdisciplinary solution for complex systems

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The Innovation 2023年第6期4卷 152-164页

作者： Yong Zhao Zhengqiu Zhu Bin Chen Sihang Qiu Jincai Huang Xin Lu Weiyi Yang Chuan Ai Kuihua Huang Cheng He Yucheng Jin Zhong Liu Fei-Yue Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Hunan Institute of Advanced Technology Changsha 410073China Shanghai Institute of Infectious Disease and Biosecurity Shanghai 200032China Institute of Epidemiology Helmholtz Zentrum Minchen-German Research Center for Environmental Health(GmbH)NeuherbergGermany Department of Computer Science Hong Kong Baptist UniversityHong KongChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and *** meet these demands,the parallel systems method rooted in the artificial systems,computational experiments,and parallel execution(ACP)approach has been *** method cultivates a cycle termed parallel intelligence,which iteratively creates data,acquires knowledge,and refines the actual *** the past two decades,the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines,offering vers atile interdisciplinary solutions for complex systems across diverse *** review explores the origins and fundamental concepts of the parallel systems method,showcasing its accomplishments as a diverse array of parallel technologies and applica-tions while also prognosticating potential *** posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.

关键词： execution artificial offering

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Robust control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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