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第40届中国控制会议

作者： Duqiao Zhao Ding Liu Linxiong Liu Xia Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xian University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

In this paper, a distributed MPC algorithm is proposed for linear discrete systems with bounded communication noise and random communication failure. Based on the characteristics of time-varying directed graphs, the convergence of the algorithm is analyzed in the case of communication noise and random communication failure. This algorithm uses the distributed projection dual subgradient algorithm to solve the dual problem and replaces the double stochastic condition of the traditional algorithm with row stochastic condition. The exponential stability of the system is guaranteed. Finally, an example is given to illustrate the performance of the algorithm.

关键词： Distributed MPC Bounded Communication Noise Random Communication Faults Distributed Projection Dual Subgradient Row Stochastic

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Cooperative trajectory planning algorithm of USV-UAV with hull dynamic constraints

arXiv

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arXiv 2022年

作者： Huang, Tao Chen, Zhe Gao, Wang Xue, Zhenfeng Liu, Yong Institute of Cyber-Systems and Control Zhejiang University No.38 Zheda Road Hangzhou310027 China Research Center for Intelligent Perception and Control Huzhou Institute of Zhejiang University No.819 Xisaishan Road Huzhou313098 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100191 China

Efficient trajectory generation in complex dynamic environments remains an open problem in the unmanned surface vehicle (USV). The perception of the USV is usually interfered with by the swing of the hull and the ambient weather, making it challenging to plan the optimal USV trajectories. In this paper, a cooperative trajectory planning algorithm for the coupled USV-UAV system is proposed to ensure that USV can execute a safe and smooth path in the process of autonomous advance in multi-obstacle maps. Specifically, the unmanned aerial vehicle (UAV) plays the role of a flight sensor, providing real-time global map and obstacle information with a lightweight semantic segmentation network and 3D projection transformation. And then, an initial obstacle avoidance trajectory is generated by a graph-based search method. Concerning the unique under-actuated kinematic characteristics of the USV, a numerical optimization method based on hull dynamic constraints is introduced to make the trajectory easier to be tracked for motion control. Finally, a motion control method based on NMPC with the lowest energy consumption constraint during execution is proposed. Experimental results verify the effectiveness of the whole system, and the generated trajectory is locally optimal for USV with considerable tracking accuracy. © 2022, CC BY.

关键词： Numerical methods

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Non-Fourier Heat Conduction based on Self-Adaptive Weight Physics-Informed Neural Networks

Non-Fourier Heat Conduction based on Self-Adaptive Weight Ph...

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第40届中国控制会议

作者： Shuyan Shi Ding Liu Zhongdan Zhao National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shananxi Key Laboratory of Complex System Control and Intelligent Information Processing

This paper establishes the non-Fourier heat conduction model to describe the heat transfer process of mono-crystalline silicon under the condition of unstable thermal field and thermal shock in the Czochralski method.A novel differential equations solver called Physics-Informed Neural Networks（PINN） algorithm was *** with finite element method（FEM）,this method has some advantages like no grid requirement and easily *** order to deal with the unbalance of constraint condition and speed up the convergence,we propose a novel method called Self-Adaptive Weight Physics-Informed Neural Networks（SWPINN）.The comparison of the experimental results of SWPINN and COMSOL verifies the effectiveness of *** modifying the parameter of non-Fourier heat conduction model,this paper obtains the temperature distribution under different heat relaxation ***,comparison between SWPINN and PINN shows that the proposed method has faster convergence speed and higher accuracy.

关键词： Non-Fourier Heat Conduction Physics-Informed Neural Networks Partial Differential Equation Monocrystalline Silicon Czochralski Method

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Impulsive Formation control of Nonlinear Leader-Following Multi-agent systems with Input Saturation*

Impulsive Formation Control of Nonlinear Leader-Following Mu...

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Industrial Cyber-Physical systems (ICPS)

作者： Ni Zhang Xiaowei Jiang Xianhe Zhang Le You School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

Leader-following formation analysis problem for a second-order nonlinear multi-agent system(MAS) with input saturation is investigated in this paper. And the impulsive formation control algorithm is introduced in the designed protocol which only works at the impulse times. Owing to the real-world limited communication channels, input saturation is considered in the impulsive controller. Furthermore, based on Lyapunov stability theories, Kronecker properties, eigenvalue and so on, some sufficient conditions that guarantee the leader-following consensus of MAS are obtained. Lastly, several simulations are worked out to verify the correctness and effectiveness of the theoretical results.

关键词： Sufficient conditions Protocols Simulation Communication channels Cyber-physical systems control systems Formation control

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Development of a neural network model for forecasting energy consumption in energy management systems

Development of a neural network model for forecasting energy...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Valeriya Tynchenko Ilia Panfilov Ksenia Degtyareva Natalia Kandaurova Tatyana Dolgova Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow Russia Software Research and Training Laboratory Siberaim Federal Iniversity Krasnoyarsk Russia Information-Control Systems Department Reshetnev Siberian State University of Science and Technology Department of Systems Analysis and Operations Research Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Center for Continuing Education Bauman Moscow State Technical University Moscow Russia Department of Information Economic System Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

This paper explores the use of neural networks to predict energy consumption based on data on the production and use of various fuels, including oil, gas and coal. The aim of the study is to develop a model that can take into account the complex relationships between key parameters such as production volumes, production costs, CO₂ emissions, energy efficiency, inventory levels and transportation costs. The relevance of the study is due to the need to improve the accuracy of forecasting for effective planning and management of resources in the energy industry, especially in conditions of unstable market and environmental factors. In the course of the work, a multi-layered fully connected neural network model was developed, which was trained and tested on the prepared data. The evaluation of the model using the coefficient of determination and the average absolute error demonstrated its high accuracy and suitability for practical application. Additionally, an analysis of the importance of the signs was carried out, which showed that the most significant factors are the import/export of energy and the share of alternative sources. Visualization of the results confirmed that the model is able to make accurate predictions, minimizing errors. The results obtained confirm that the use of neural network models to predict energy consumption is a promising area that can significantly improve decision-making processes in the energy sector and increase resource efficiency.

关键词： Industries Energy consumption Analytical models Accuracy Costs Neural networks Production Predictive models Data models Forecasting

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Informational infrastructure of the common digital space of scientific knowledge

Informational infrastructure of the common digital space of ...

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2020 International Conference "Common Digital Space of Scientific Knowledge: Problems and Solutions", CDSSK 2020

作者： Ataeva, Olga Kalenov, Nikolay Serebriakov, Vladimir Sotnikov, Alexander Computing Center FRS "Computer Sciences and Control" of Russian Academy of Sciences Vavilova str. 40b Moscow119333 Russia Joint Supercomputer Center of Russian Academy of Sciences – Branch of Federal State Institution "Scientific Research Institute for System Analysis" of Russian Academy of Sciences Leninskiy pr. 32a Moscow119334 Russia

The space of scientific knowledge is understood as a system of knowledge from various fields of science tested by the scientific community. The Common Digital Space of Scientific Knowledge (CDSSK) is a digital environment into which information resources and objects that have been tested by the scientific community and that reflect scientific knowledge from a different fields of science are integrated. The common digital space of scientific knowledge consists of a set of thematic subspaces related to various areas of science, built according to common principles. The first step towards the implementation of the CDSSK is the development of its ontology, i.e. a multi-level system of concepts describing resources and objects of subject areas, concepts, terms and connections between them, characterized by an open hierarchical and dynamic structuring, oriented both for storing existing knowledge and for extracting new ones. Since the CDSSK is a fundamentally new information environment, there are a number of significant problems on the way to its implementation. The paper deals with the problems and tasks of forming such a space and developing tools for implementation and support the CDSSK. © 2021 Copyright for this paper by its authors

关键词： Ontology

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The 2022 report of synergetic roadmap on carbon neutrality and clean air for China:Accelerating transition in key sectors

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Environmental Science and Ecotechnology 2024年第3期19卷 4-18页

作者： Yu Lei Zhicong Yin Xi Lu Qiang Zhang Jicheng Gong Bofeng Cai Cilan Cai Qimin Chai Huopo Chen Renjie Chen Shi Chen Wenhui Chen Jing Cheng Xiyuan Chi Hancheng Dai Xiangzhao Feng Guannan Geng Jianlin Hu Shan Hu Cunrui Huang Tiantian Li Wei Li Xiaomei Li Jun Liu Xin Liu Zhu Liu Jinghui Ma Yue Qin Dan Tong Xuhui Wang Xuying Wang Rui Wu Qingyang Xiao Yang Xie Xiaolong Xu Tao Xue Haipeng Yu Da Zhang Ning Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Xin Zhang Zengkai Zhang Bo Zheng Yixuan Zheng Jian Zhou Tong Zhu Jinnan Wang Kebin He Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100041China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100041China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China School of Public Health Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of HealthFudan UniversityShanghai200032China School of Economics and Management Beijing University of Chemical TechnologyBeijing100029China Department of Earth System Science University of CaliforniaIrvineCA92697USA National Meteorological Center China Meteorological AdministrationBeijing100081China College of Environmental Sciences and Engineering Peking UniversityBeijing100871China Policy Research Center for Environment and Economy Ministry of Ecology and Environment of the People's Republic of ChinaBeijing100029China Jiangsu Key Laboratory of Atmospheric Environment Monitoring

China is now confronting the intertwined challenges of air pollution and climate *** the high synergies between air pollution abatement and climate change mitigation,the Chinese government is actively promoting synergetic control of these two *** Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key *** Synergetic Roadmap 2022 report is the first annual update,featuring 20 indicators across five aspects:synergetic governance system and practices,progress in structural transition,air pollution and associated weather-climate interactions,sources,sinks,and mitigation pathway of atmospheric composition,and health impacts and benefits of coordinated *** to the comprehensive review presented in the 2021 report,the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant *** milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time,a decline in the production of crude steel and cement after years of growth,and the surging penetration of electric ***,in 2022,China issued the first national policy that synergizes abatements of pollution and carbon emissions,marking a new era for China's pollution-carbon *** changes highlight China's efforts to reshape its energy,economic,and transportation structures to meet the demand for synergetic control and sustainable ***,the country has witnessed a slowdown in carbon emission growth,improved air quality,and increased health benefits in recent years.

关键词： Synergetic roadmap Carbon neutrality Clean air

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Parameter estimation of time fractional heat conduction equation for monocrystalline silicon

Parameter estimation of time fractional heat conduction equa...

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Chinese Automation Congress (CAC)

作者： Shuyan Shi Ding Liu Zhongdan Zhao Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shananxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (纸本)9781665426480

In this paper, a time-fractional heat conduction model is established to describe the heat transfer process of monocrystalline silicon in the Czochralski method. The numerical solution of the fractional-order model is obtained by using implicit difference scheme. In addition, an improved grey wolf algorithm is proposed to estimate the parameters of the fractional heat conduction model using the experimental temperature data. The numerical experiment results show that the time-fractional heat conduction model has a higher explanatory ability, compared with the classical heat conduction model. The Improved Grey Wolf algorithm proposed in this paper is effective in solving the parameter estimation problem of the time-fractional heat conduction equation.

关键词： Heating systems Temperature distribution Parameter estimation Inverse problems Simulation Mathematical models Silicon

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The 2023 report of the synergetic roadmap on carbon neutrality and clean air for China: Carbon reduction, pollution mitigation, greening, and growth

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Environmental Science and Ecotechnology 2025年第1期23卷 1-18页

作者： Jicheng Gong Zhicong Yin Yu Lei Xi Lu Qiang Zhang Cilan Cai Qimin Chai Huopo Chen Renjie Chen Wenhui Chen Jing Cheng Xiyuan Chi Hancheng Dai Zhanfeng Dong Guannan Geng Jianlin Hu Shan Hu Cunrui Huang Tiantian Li Wei Li Xiaomei Li Yongsheng Lin Jun Liu Jinghui Ma Yue Qin Weiqi Tang Dan Tong Jiaxing Wang Lijuan Wang Qian Wang Xuhui Wang Xuying Wang Libo Wu Rui Wu Qingyang Xiao Yang Xie Xiaolong Xu Tao Xue Haipeng Yu Da Zhang Li Zhang Ning Zhang Shaohui Zhang Shaojun Zhang Xian Zhang Zengkai Zhang Hongyan Zhao Bo Zheng Yixuan Zheng Tong Zhu Huijun Wang Jinnan Wang Kebin He State Key Joint Laboratory for Environment Simulation and Pollution Control College of Environmental Sciences and Engineering and Center for Environment and HealthPeking UniversityBeijing100871China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing210044China Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing100041China Center for Carbon Neutrality Chinese Academy of Environmental PlanningBeijing100041China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing100084China Ministry of Education Key Laboratory for Earth System Modelling Department of Earth System ScienceTsinghua UniversityBeijing100084China National Center for Climate Change Strategy and International CooperationBeijing100035China Nansen-Zhu International Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China School of Public Health Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of HealthFudan UniversityShanghai200032China School of Economics and Management Beijing University of Chemical TechnologyBeijing100029China Department of Earth System Science University of CaliforniaIrvineIrvineCA92697USA National Meteorological Center China Meteorological AdministrationBeijing100081China College of Environmental Sciences and Engineering Peking UniversityBeijing100871China Institute of Eco-Environmental Management and Policy Chinese Academy of Environmental PlanningBeijing100041China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Contr

The response to climate change and air pollution control demonstrates strong synergy across scientific mechanisms,targets,strategies,and governance *** report,based on a monitoring indicator system for coordinated governance of air pollution and climate change,employs an interdisciplinary approach combining natural and social *** establishes 20 indicators across five key areas:air pollution and climate change,governance systems and practices,structural transformation and technologies,atmospheric components and emission reduction pathways,and health impacts and *** report tries to provide actionable insights into the interconnectedness of air pollution and climate *** highlights key policy gaps,presents updated indicators,and offers a refined monitoring framework to track progress toward China's dual goals of reducing emissions and improving air *** to previous editions,this year's report has updated four key indicators:meteorological impacts on air quality,climate change and its effects,governance policies,and low-carbon building energy *** aim is to further refine the monitoring framework,track progress,and establish a comprehensive theory for collaborative governance while identifying challenges and proposing solutions for China's pathway to carbon neutrality and clean *** report comprises six *** executive summary chapter is followed by analyzing air pollution and climate change *** systems and practices are discussed in the third chapter,focusing on policy implementation and local *** fourth chapter addresses structural transformations and emission reduction technologies,including energy and industrial shifts,transportation,low-carbon buildings,carbon capture and storage,and power *** fifth chapter outlines atmospheric component dynamics and emission pathways,presenting insights into emission drivers and future *** sixth chapter assesses he

关键词： Synergetic roadmap Carbon neutrality Clean air

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Development of Smart Irrigation system Based on Climate-Smart Agricultural Practices

Development of Smart Irrigation System Based on Climate-Smar...

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Conference on Technologies for Sustainability (Sustech)

作者： Oleksandr Kuchanskyi Alexandr Neftissov Andrii Biloshchytskyi Yurii Andrashko Volodymyr Vatskel Department of Computational and Data Science Astana IT University Astana Kazakhstan Department of Information Control Systems and Technologies Uzhhorod National University Uzhhorod Ukraine Research and Innovation Center "Industry 4.0" Astana IT University Astana Kazakhstan University Administration Astana IT University Astana Kazakhstan Department of Information Technology Kyiv National University of Construction and Architecture Kyiv Ukraine Department of System Analysis and Optimization Theory Uzhhorod National University Uzhhorod Ukraine

ISBN: (数字)9798331504311

ISBN: (纸本)9798331504328

The paper presents a smart irrigation system that combines hardware and software elements and allows the implementation of climate-smart agriculture ideas in agricultural companies’ activities. The system was implemented in a Ukrainian company specializing in growing potatoes in 2021-2024. According to the results, on average, we got a significant increase in potato yield and reduced water consumption by more than 50%. The possibilities of transferring smart irrigation technology based on a smart irrigation system in the activities of agricultural companies in Kazakhstan were analyzed. The assessment and forecasting of potato yield growth in Kazakhstan in the coming years was also carried out, provided that the described technology is used, considering the peculiarities of the sharp continental climate. The results confirm that implementing the described system and other climate-smart agricultural practices increases the profitability of agricultural enterprises, promotes food security in the context of global population growth, and promotes environmental sustainability by saving water resources. This is extremely important in the context of climate change.

关键词： Irrigation Climate change Wireless sensor networks Profitability Green products Ecosystems Food security Companies Water resources Meteorology

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