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International Joint Conference on Neural Networks (IJCNN)

作者： Zishu Gao Guodong Yang En Li Zize Liang State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Producing a 3D voxel from a single view by deep learning-based methods has garnered increasing attention. Several state-of-the-art works introduce the recurrent neural network(RNN) to fuse features and generate full volumetric occupancy. However, the inputs are unable to be fully exploited to improve the reconstruction due to long-term memory loss. And most of the works have considered using 3D supervision for the whole optimization to recover the full volume, but lack detailed silhouette supervision to refine the reconstruction process. To address these issues, an end-to-end object reconstruction network with scaling volume-view supervision is proposed. We introduce an auto-encoder 3D volume predicting network that takes a single arbitrary image as input and outputs a voxel occupancy grid. And a scaling volume-view supervision module, which uses up-sampling to zoom errors and increase penalties, is leveraged to improve both the global and local optimization. Extensive experimental analysis on ShapeNet dataset shows that our network has superior performance when the scaling volumeview supervision is involved and the deep residual module boosts the reconstruction performance and speeds up the optimization effectively.

关键词： Three-dimensional displays Image reconstruction Optimization Two dimensional displays Feature extraction Convolution Decoding

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Consensus control of Multi-Agent systems With Two-Way Switching Directed Topology ⁎

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IFAC-PapersOnLine 2020年第5期53卷 669-674页

作者： Xin Wang Qinglai Wei Ruizhuo Song The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

In this paper, a novel control protocol method is developed to solve distributed consensus control problems for multi-agent systems with switching directed topologies. Because of the external disturbance, the information cannot transmit completely so that the proposition of two-way topology is necessary. Besides, the external disturbance is considered naturally and we give a control protocol and parameters of noise intensity function in this paper. Furthermore, an example is given to support the proposed theorem. Finally, the simulation results prove the correctness of the theory.

关键词： Distributed consensus control multi–agent systems two–way topology fixed switching directed topologies

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Sliding Mode control for Flexible-link Manipulators Based on Adaptive Neural Networks

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International Journal of Automation and computing 2018年第2期15卷 239-248页

作者： Hong-Jun Yang Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

This paper mainly focuses on designing a sliding mode boundary controller for a single flexible-link manipulator based on adaptive radial basis function （RBF） neural network. The flexible manipulator in this paper is considered to be an Euler-Bernoulli beam. We first obtain a partial differential equation （PDE） model of single-link flexible manipulator by using Hamiltons approach. To improve the control robustness, the system uncertainties including modeling uncertainties and external disturbances are compensated by an adaptive neural approximator. Then, a sliding mode control method is designed to drive the joint to a desired position and rapidly suppress vibration on the beam. The stability of the closed-loop system is validated by using Lyapunov＇s method based on infinite dimensional model, avoiding problems such as control spillovers caused by traditional finite dimensional truncated models. This novel controller only requires measuring the boundary information, which facilitates implementation in engineering practice. Favorable performance of the closed-loop system is demonstrated by numerical simulations.

关键词： Sliding mode control adaptive control neural network flexible manipulator partial differential equation （PDE）.

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Feature Selection and Learning-Based Model for Uav Path Planning on Rough Terrains

SSRN

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SSRN 2022年

作者： Ali, Hub Xiong, Gang Husnain, Haider Muhammad Tamir, Tariku Sinshaw Dong, Xisong Shen, Zhen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Qingdao Academy of Intelligent Industries Qingdao266109 China Chengdu610054 China

Path planning and obstacle avoidance in 3D terrain have been identified as a monumental challenge for a UAV in a variety of autonomous missions, such as disaster management and search and rescue operations. In large terrain areas, it’s a key problem for traditional approaches to search within the point-cloud maps to find a global path for a UAV considering the flight safety, maneuverability, weather constraints, and fuel cost. Hence, this paper proposes a trajectory planning technique for global and local path planning of a fixed-wing UAV above 3D terrain under static and dynamic constraints. For global path generation, a novel Feature Selection and Learning-based Model (FSLM) has been introduced to select the features of a point-cloud map and transform them into the feature set. The feature set is utilized by an improved A* planner with an extensive search area to deliver an optimal global path. The global path is assumed as the UAV's reference waypoints. The motion of the UAV on reference waypoints is simplified with two coordinates (R, d), where R is the cumulative distance covered by the UAV along the reference waypoints and d is its offset distance from the reference line segment in time t. For any local collision, offset trajectories are generated along with reference waypoints to avoid collision. Cost functions have been added so that the best global and local path can be chosen, taking into account altitude, weather, and fuel constraints. The simulation results show the performance of this approach in various complex terrains by considering weather and dynamic constraints, and the results are also compared to other 3D UAV path planning techniques. © 2022, The Authors. All rights reserved.

关键词： Motion planning

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Learning Greenhouse Climate control Policy from Monitored Data

Learning Greenhouse Climate Control Policy from Monitored Da...

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Chinese Automation Congress (CAC)

作者： Xiaoxuan Zhao Haoyu Wang Xiujuan Wang Udom Lewlomphaisarl Dong Li Jing Hua Mengzhen Kang The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technologies Beijing China National Electronics and Computer Technology Center Pathum Thani Thailand Institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Hangzhou China Qingdao AgriTech Co. Ltd. Qingdao China

The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhouses by building a long short-term memory (LSTM) model. The result is verified according to the real monitored data of a solar greenhouse, which shows that the model can learn the control strategy of a ventilator in the solar greenhouse. Through monitored data and models, the knowledge of greenhouse ventilation control can be learned, and automatic control can be achieved in a greenhouse with a similar configuration.

关键词： Ventilators Green buildings Buildings Production Ventilation Data models Data mining

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A KDC-enhanced closest point method for thermal analysis on curved geometries using LS-GFDM

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Applied Mathematics Letters 2025年 171卷

作者： Tang, Zhuochao Gu, Jiming Chen, Bin Fu, Zhuojia School of Management Science and Engineering Anhui University of Technology Maanshan243002 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Maanshan243002 China Center for Numerical Simulation Software in Engineering and Sciences College of Mechanics and Engineering Science Hohai University Nanjing211100 China

This paper presents a Krylov-deferred correction (KDC)-enhanced closest point method (CPM) integrated with the least-squares generalized finite difference method (LS-GFDM) for thermal analysis on curved geometries. To overcome the inherent limitations of conventional single-step/multi-step temporal schemes in long-time simulations, we systematically unify three advanced components: (i) CPM's embedding strategy that transforms surface PDEs into extended problems over Cartesian grids, (ii) LS-GFDM's spatial discretization employing dual point sets to enhance applicability beyond conventional GFDM, and (iii) KDC's predictor–corrector framework that iteratively refines temporal solutions to achieve high-order accuracy. Building upon our previous work (Tang et al. 2025) where LS-GFDM was integrated with CPM using explicit Euler temporal schemes, this study constitutes a critical advancement by replacing low-order temporal discretization with the KDC methodology. Numerical experiments demonstrate that our KDC-CPM-LSGFDM framework achieves superior numerical performance. © 2025 Elsevier Ltd

关键词： Least squares approximations

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Grouping Methods for Facilitating Emergency Evacuations

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IFAC-PapersOnLine 2020年第5期53卷 845-850页

作者： Linyao Yang Ke Tan Xin Liu Xiao Wang Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Shenzhen China

It is widely believed that the motion of crowds can be described by the “social force” model, and small group behaviors have great impacts on evacuation efficiency as a common phenomenon in pedestrian evacuations. Some previous works have modeled group behaviors in social force models by depicting group members’ interaction forces. However, the impacts of different grouping schemes have not been considered and evaluated. This paper proposes four different grouping methods to explore the evacuation dynamics of different group structured pedestrians. Results show that group evacuations based on the spatial partitioning outperform those clustering-based schemes with the larger group number. More importantly, simulations indicate that the number of groups also highly affects the evacuation efficiency, and the larger the number of groups, the more efficient the evacuation.

关键词： Evacuation Simulation Social force Clustering methods Agent based modeling

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Parallel Building Process management System

Parallel Building Process Management System

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2021 China Automation Congress, CAC 2021

作者： Liu, Sheng Shen, Zhen Dong, Xisong Hu, Bin Xiong, Gang Chen, Xiaoyu State Key Laboratory for Management and Control of Complex Institute of Automation Chinese Academy of Sciences Beijing China Beijing engineering Research Center of intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426473

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved. © 2021 IEEE

关键词： Engines

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Blockchain-based Consensus Study on Distributed control systems

Blockchain-based Consensus Study on Distributed Control Syst...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Jing Zhu Hongchang Deng Xiang Li Yong Yuan Feiyue Wang College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Institute of Systems Engineering Macau University of Science and Technology Macau China School of Mathematics Renmin University of China Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In this paper, two blockchain-based consensus mechanisms are proposed for distributed control systems, those are the proof-of-work-based (PoW-based) and proof-of-stake-based (PoS-based) consensus mechanisms. The basic idea and process of these blockchain-based consensus mechanisms are introduced, giving rise to the dynamic, impartial and efficient consensus compared with the consensus protocol achieved by traditional control theories.

关键词： Digital twin Conferences Decentralized control Process control control theory Consensus protocol Computational efficiency

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The Architectural Unit Setting up and Architectural Characteristics of Néré, <i>Parkia biglobosa</i>, Jack, R. Br. (Fabaceae)

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American Journal of Plant Sciences 2022年第1期13卷 109-136页

作者： Beda Innocent Adji Doffou Sélastique Akaffou Véronique Letort Mengzhen Kang Xiujuan Wang Marc Jaeger Philippe De Reffye Kouadio Henri Kouassi Yao Patrice Houphouet Jerôme Duminil Yves Caraglio Sylvie Sabatier Université Jean Lorougnon Guédé UFR Agroforesterie Daloa C&#244 te d’Ivoire CIRAD UMR-botAnique et Modélisation de l’Architecture des Plantes et des végétations (AMAP) Montpellier France MICS CentraleSupélec-Université Paris-Saclay Gif-sur-Yvette France Key Laboratory of Management and Control for Complex Systems (CASIA-LMCCS) Institute of Automation Chinese Academy of Sciences Beijing China IRD UMR-DIADE Montpellier France

Parkia biglobosa is a much-loved and over-exploited African savannah species for its socio-economic importance. Knowing and taking into account its architectural unit, which is the basis for diagnosing phenology, prod... 详细信息

Parkia biglobosa is a much-loved and over-exploited African savannah species for its socio-economic importance. Knowing and taking into account its architectural unit, which is the basis for diagnosing phenology, productivity and tree health, could provide a new perspective on its sustainable management. The aim of this study is to establish the architectural development in Parkia biglobosa by retrospective analysis. To achieve this objective, 390 individuals of all sizes ranging from seedlings to senescent trees were observed and analysed under various soil and climatic conditions in Côte d’Ivoire. The results showed that Parkia biglobosa is a light plant but shading tolerant. It is a mixed vegetative axis plant, the stem is orthotropic* in its proximal part and plagiotropic* (collapsing) in its distal part in young stage. The tree then transitions to an adult and old stage into a tree with a plagiotropic* axis in the proximal and distal parts, the trunk is built up by superimposing collapsed relay axes that gradually straighten, branching is sympodial*, growth is defined and sexuality is terminal and lateral. The ontogeny takes place in three phases: initiation of development and establishment of the crown (young), then flowering and establishment of the architectural unity (adult) and finally the death of secondary axes in the crown, duplication of the architecture by a series of partial and total reiterations (old). The level of organisation is 5: the phytomere, the module or growth unit, the axis, the architectural unit and the reiterated complex. Retrospective analysis of the modules showed that the dimensions of the growth units are indicators of morphological variation and species adaptation to a changing climate (P < 0.05). However, the equations generated by the morphological and habitat dimension linkage models are not significant (R² and

关键词： Parkia biglobosa Architectural Development Architectural Unit Côte d’Ivoire

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