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Chinese control Conference

作者： Xiangyang Dai Wei Xue Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan

Remote sensing hyperspectral imaging can obtain rich spectral information of terrestrial objects, which allows the indistinguishable matter in the traditional wideband remote sensing to be distinguished in hyperspectral remote sensing. Hyperspectral image has the characteristics of "combining image with spectrum". Making full use of spectral information and spatial information in hyperspectral image is the premise of obtaining accurate classification results. At present, most of hyperspectral data feature extraction algorithms mainly utilize local spatial information in the same channel and spectral information in the same spatial location of different channels. However, these methods require a large amount of prior knowledge, it is difficult to fully grasp the hyperspectral data of all spatial and spectral information, and the model generalization ability is poor. With the development of deep learning, convolutional neural network shows superior performance in all kinds of visual tasks, especially in the two-dimensional image classification, and could get a high classification accuracy. In this paper, an image classification method based on three-dimensional convolution neural network is proposed based on the structural properties of hyperspectral data. In the proposed method, first the stereo image blocks of hyperspectral data are intercepted, then multi-layer convolution and pooling operation of extracted blocks by convolutional neural network are implemented to obtain the essential information of hyperspectral data, finally the classification of hyperspectral data is completed. The experimental results show the proposed method could provide better feature expression and classification accuracy for hyperspectral image.

关键词： Hyperspectral imaging Image classification Convolution Feature extraction Support vector machines

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Disturbance observer based time-varying sliding mode control for uncertain mechanical system

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Journal of systems Engineering and Electronics 2012年第1期23卷 108-118页

作者： Binglong Cong Xiangdong Liu Zhen Chen School of Automation Beijing Institute of Technology Beijing 100081 P. R. China Key Laboratory for Intelligent Control ＆ Decision on Complex Systems Beijing Institute of Technology Beijing 100081 P. R. China

It is now well known that the time-varying sliding mode control （TVSMC） is characterized by its global robustness against matched model uncertainties and disturbances. The accurate tracking problem of the mechanical system in the presence of the parametric uncertainty and external disturbance is addressed in the TVSMC framework. Firstly, an exponential TVSMC algorithm is designed and the main features are analyzed. Especially, the control parameter is obtained by solving an optimal problem. Subsequently, the global chattering problem in TVSMC is considered. To reduce the static error resulting from the continuous TVSMC algorithm, a disturbance observer based time-varying sliding mode control （DOTVSMC） algorithm is presented. The detailed design principle and the stability of the closed-loop system under the composite controller are provided. Simulation results verify the effectiveness of the proposed algorithm.

关键词： mechanical system time-varying sliding mode control （TVSMC） global sliding phase global chattering disturbance observer.

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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Decentralized Filtering a Multi-Agent System with Local Parametric Couplings Based On Kalman Filter

Decentralized Filtering a Multi-Agent System with Local Para...

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第25届中国控制与决策会议

作者： Yini Lv Hongbin Ma Mengyin Fu Chenguang Yang Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institution of Technology School of Computing and Mathematics Plymouth University

ISBN: (纸本)9781467355339

In this paper, decentralized filtering of multiagent systems with coupling uncertainties is proposed and investigated. The considered multi-agent system is composed of many agents, each of which evolves with a discrete-time stochastic linear time-varying dynamics, and every agent can be locally influenced by its neighbor agents. Therefore the states evolution of each agent is not only related with its previous states but also related with its neighbors' previous states in the linear dynamic system. Communication limitations existing in the considered multi-agent system restrict that each agent can only observe its own measurements (outputs) and its neighbor agents' outputs while the states are invisible to any agent. Because of communication limitations and information constraints, without knowing the coupling gains of the local interactions, it is not easy for each agent to estimate its states by traditional kalman filter or other state observers, which were extensively discussed in the literature. In this preliminary study, for the considered coupled linear discrete-time multiagent system with uncertain linear local couplings, based on the key idea of state augmentation and the certainty-equivalence principle borrowed from the area of adaptive control, we propose an efficient decentralized kalman filtering scheme, for each agent, to simultaneously estimate the unknown states and coupling parameters, and extensive simulations are conducted, which have clearly verified the effectiveness of the proposed decentralized filtering scheme.

关键词： multi-agent system, kalman filter, parametric couplings, parameter estimation, states estimation, decentralized filtering

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A Collision-Free Person-Following Approach Based on Path Planning 17

A Collision-Free Person-Following Approach Based on Path Pla...

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17th IEEE International Conference on Mechatronics and automation, ICMA 2020

作者： Pang, Lei Cao, Zhiqiang Yu, Junzhi Zhang, Weimin Chen, Xuechao Institute of Automation State Key Laboratory of Management and Control for Complex Systems China Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems China

ISBN: (纸本)9781728164151

Person following is a crucial capability for mobile robots in tasks of human assistance and cooperation. In this paper, a person-following approach based on path planning is proposed for mobile robots, which takes person following and obstacle avoidance into account in a unified framework. The proposed approach is comprised of a sensing module and a planning module. The sensing module with a camera and a 3D LiDAR is employed to locate the target person and perceive obstacles. For the planning module, the combination of global planner and local planner effectively outputs collision-free paths and control commands for a mobile robot to keep following the target person. Experiments were conducted to evaluate the performance of the proposed approach. © 2020 IEEE.

关键词： Mobile robots

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Tracking and Mapping Strategy for Indoor UAV Based on Entropy Theory:An ORB-SLAM3 Extension 41

Tracking and Mapping Strategy for Indoor UAV Based on Entrop...

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第41届中国控制会议

作者： Jian Xu Haoyu Qi Min Xu Yunge Zang Zhen Li Xi Zhang Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For indoor application,which is an entirely GPS-denied environment,visual simultaneous localization and mapping(SLAM) facilitates the real autonomy of unmanned aerial vehicle(UAV) but raises the challenging requirement on accurate localization with low computational *** address this difficulty,a stereo-camera based SLAM system is proposed by applying Entropy theory to *** an extension to ORB-SLAM3,the additional entropy decision module and map processor are specifically *** decision module can improve computing efficiency by deciding whether keyframes or extra optimization should be ***,the map processor is targeted at loading and maintaining the prior map whenever *** results in indoor laboratory environment show that the developed system can achieve the superior localization accuracy in more efficient computation manner with smaller size of mapping compared with ***,the map can be effectively expanded and corrected even when prior information is invalid,greatly increasing the robustness of SLAM system.

关键词： UAV stereo-camera ORB-SLAM3 entropy theory prior map

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Cyber-physical-social System in intelligent Transportation

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IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 320-333页

作者： Gang Xiong Fenghua Zhu Xiwei Liu Xisong Dong Wuling Huang Songhang Chen Kai Zhao the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science the Cloud Computing Center Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center for Intelligent Systems and Technology Institute of AutomationChinese Academy of Science

A cyber-physical system (CPS) is composed of a physical system and its corresponding cyber systems that are tightly fused at all scales and levels. CPS is helpful to improve the controllability, efficiency and reliability of a physical system, such as vehicle collision avoidance and zero-net energy buildings systems. It has become a hot R&D and practical area from US to EU and other countries. In fact, most of physical systems and their cyber systems are designed, built and used by human beings in the social and natural environments. So, social systems must be of the same importance as their CPSs. The indivisible cyber, physical and social parts constitute the cyber-physical-social system (CPSS), a typical complex system and it's a challengeable problem to control and manage it under traditional theories and methods. An artificial systems, computational experiments and parallel execution (ACP) methodology is introduced based on which data-driven models are applied to social system. Artificial systems, i.e., cyber systems, are applied for the equivalent description of physical-social system (PSS). Computational experiments are applied for control plan validation. And parallel execution finally realizes the stepwise control and management of CPSS. Finally, a CPSS-based intelligent transportation system (ITS) is discussed as a case study, and its architecture, three parts, and application are described in detail. © 2014 Chinese Association of automation.

关键词： Amphibious vehicles complex networks Embedded systems intelligent systems Transportation

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Event-Trigger Extended Kalman Filter Design for Distributed Generation Network with Limited Communication 36

Event-Trigger Extended Kalman Filter Design for Distributed ...

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第36届中国控制会议

作者： Xing Xin Luyu Li Sen Li Zhen Li Jian Li Zhen Chen Xiangdong Liu Beijing Institute of Electronic System Engineering School of Automation & Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538629185

For distributed generation(DG) network, it is important to estimate the real-time states. The information-centric networking(ICN) is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended kalman filter(ET-EKF) is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units(PMUs).

关键词： Event-trigger extended Kalman filter(ET-EKF) real-time estimation distributed generation network smart grids phasor measurement unit(PMU)

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Semantic Segmentation of Indoor Point Clouds with the Channel Attention Mechanism

Semantic Segmentation of Indoor Point Clouds with the Channe...

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2022 Chinese automation Congress, CAC 2022

作者： Liu, Wei Lu, Yisheng Zhang, Tao Chen, Jun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geoexploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

In recent years, the semantic segmentation of 3D point cloud has received increasing attention the field of computer vision, because 3D point cloud can better reflect our 3D space. Because of the unstructured and disordered characteristics of 3D point cloud data, semantic segmentation of point cloud is still a difficult task. Our network automatically learns the importance of feature channels by adding a channel attention module, which enables the network to obtain better training results. After the channel attention module is fused, the important channels in the features are enhanced, and the unimportant channels are suppressed, making the network training more efficient. In this paper, we propose an indoor point cloud semantic segmentation method combined with channel attention mechanism. The experimental results show that our method achieves better results than other methods. © 2022 IEEE.

关键词： Semantic Segmentation

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Application of machine learning method in optical molecular imaging: a review

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Science China(Information Sciences) 2020年第1期63卷 5-20页

作者： Yu AN Hui MENG Yuan GAO Tong TONG Chong ZHANG Kun WANG Jie TIAN CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular ImagingThe State Key Laboratory of Management and Control for Complex SystemsInstitute of Automation Chinese Academy of Sciences Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of MedicineBeihang University University of Chinese Academy of Sciences

Optical molecular imaging(OMI) is an imaging technology that uses an optical signal, such as near-infrared light, to detect biological tissue in organisms. Because of its specific and sensitive imaging performance, it is applied in both preclinical research and clinical surgery. However, it requires heavy data analysis and a complex mathematical model of tomographic imaging. In recent years, machine learning(ML)-based artificial intelligence has been used in different fields because of its ability to perform powerful data processing. Its analytical capability for processing complex and large data provides a feasible scheme for the requirement of OMI. In this paper, we review ML-based methods applied in different OMI modalities.

关键词： optical molecular imaging machine learning artificial intelligence

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