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检索条件"机构=State Key Laboratory of Intelligent Control and Management of Complex Systems"

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Distributed Full Order Sliding Mode control for Finite-time Attitude Synchronization and Tracking of Spacecraft

Distributed Full Order Sliding Mode Control for Finite-time ...

引用

第37届中国控制会议

作者： Nsubuga Latifu Zhuoyue Song Chao Duan Zhen Li Housheng Su Qinghe Wu Xiangdong Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Key Laboratory of Drive and Control of Servo Motion System Ministry of Industry and Information Technology School of Automation Huazhong University of Science and Technology

This paper investigates a distributed finite-time attitude synchronization and tracking problem of multiple spacecraft when a time varying reference signal is available to only a subset of group *** Rodrigues parameters are used for attitude representation.A two layer sliding mode surface with fast non-singular terminal sliding mode surface（FNTSMS） as the inner layer and terminal sliding mode surface（TSMS） as the outer layer is used to create a full order sliding mode *** proposed distributed attitude coordination control law guarantees attitude synchronization and tracking as long as their exists atleast one spacecraft that has a direct access to the virtual leader’s time varying ***-time stability of the closed loop system is guaranteed by Lyapunov-based stability *** results are presented to validate the performance of the proposed control strategy.

关键词： Attitude synchronization Attitude tracking Finite-time Full-order sliding mode（FOSM） Distributed control

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Artificial Intelligence Course Design: iSTREAM-based Visual Cognitive Smart Vehicles

Artificial Intelligence Course Design: iSTREAM-based Visual ...

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IEEE Symposium on intelligent Vehicle

作者： Xiaoyan Gong Yilin Wu Zifan Ye Xiwei Liu State Key Laboratory of Management and Control for Complex Systems Intelligent Education Institute of Qingdao Academy of Intelligent Industries Qingdao China Beijing NO. 13 School Beijing China NO.2 high school of Beijing Normal University Beijing China

ISBN: (纸本)9781538644539

New intelligent era calls for new learners and thus urgently needs a series of artificial intelligence. As a good educational platform for teaching artificial intelligence, smart cars have aroused concern and practices of all parties. However, at present, most courses and training pay more attention to basic knowledge and technology of smart cars, seldom to training based on artificial intelligence curriculum system and comprehensive competency integrating science, technology, art and management. Therefore, based on concept of iSTREAM (intelligence for Science, Technology, Robotics, Engineering, Art, and management) and Raspberry intelligent vehicle teaching platform, this paper introduced a smart car-themed artificial intelligence courses including basic courses, specialized courses, specialized technical courses and elective courses. This course can guide learners to develop smart cars based on visual cognition, in-depth learning, VR and 3D printing integrated artistic creativity. It combines disciplines such as science, technology, art, games and management to upgrade a single knowledge and technology course into a comprehensive competency course that integrates knowledge, skills, emotion and management. Practice in Beijing NO.13 and NO.101 High School shows that this course allows students to experience scientific research process, learn artificial intelligence related knowledge and skills, understand scientific way of thinking and scientific research methods, stimulate learners' responsibility and scientific passion, and cultivate leadership skills through self-learning and partly project management.

关键词： Automobiles Artificial intelligence Art Hardware Software Project management intelligent vehicles

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Development of a Tetris Playing Robot controlled by KNR

Development of a Tetris Playing Robot Controlled by KNR

引用

IEEE International Conference on Mechatronics and Automation

作者： Ming Wang Yanlu Zhang Huifang Dong Xu Li Junzhi Yu Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system.

关键词： Mobile robots Cameras Robot sensing systems Image color analysis Servomotors Robot kinematics

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Trajectory tracking of under-actuated reentry vehicle based on time-varying SMC with RBF disturbance observer 5

Trajectory tracking of under-actuated reentry vehicle based ...

引用

5th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Ji, Haibo Guo, Fuhui Liu, Xiangdong School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

In this paper, an effective guidance scheme and a control scheme are proposed to realize trajectory tracking of hypersonic reentry vehicle(HRV) subject to aileron stuck in some position. The overload is adopted as virtual control instead of lift and lateral force, then guidance order can be obtained by torque coefficient function. In attitude subsystem, attack of angle and sideslip angle are controlled to track guidance order. Time-varying sliding mode control method is adopted to design guidance law and attitude controller. Besides, a RBF observer is designed to estimate the unknown external disturbance to soften the chattering caused by TVSMC. Simulations verify the proposed schemes.

关键词： Sliding mode control

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A Vision and Neural Network Based Air-Ground Coordinated control System

A Vision and Neural Network Based Air-Ground Coordinated Con...

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2017 IEEE International Conference on Unmanned systems (ICUS)

作者： Muyun Jiang Jiahui Shi Hongbin Ma You Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538631089;9781538631072

This paper presents an air-ground coordinated system made up of an Unmanned Aerial Vehicle(UAV) and an Unmanned Ground Vehicle(UGV).The movement of UGV is totally controlled by UAV and multiple sensors are adopted in the system to ensure the stability.A novel neutral network algorithm is introduced to identify the location and orientation of *** component is introduced and tested in detail and the coordinated system performs a satisfying result.

关键词： Air-ground system Neutral Network

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Design of AI + Curriculum for Primary and Secondary Schools in Qingdao

Design of AI + Curriculum for Primary and Secondary Schools ...

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2018 Chinese Automation Congress, CAC 2018

作者： Han, Xiao Hu, Fang Xiong, Gang Liu, Xiwei Gong, Xiaoyan Niu, Xiaojie Shi, Wanruo Wang, Xinzhu Qingdao Institute of Education Sciences Qingdao China Qingdao No.2 Middle School of Shandong Province Qingdao China Cloud Computing Center Chinese Academy of Sciences Dongguan China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China Faculty of Education Beijing Normal University Institute of Educational Technology Beijing China

ISBN: (纸本)9781728113128

We are entering a new AI era, and the development of AI technology and popularization of AI education has become the national strategy of China. The primary and secondary school students are the builder of future society, and have strong curiosity and passion to learn new things;therefore, we should make a good preparation of AI education for them and cultivate their basic AI literacy and computational thinking to adapt to the future. In this paper, from the viewpoint of thinking mode and literacy and skill training, a curriculum including basic, project, and practical types is designed. Integrating with the iSTREAM educational system proposed by Chinese Academy of Sciences, exploratory works were shown with some case studies. The applications show that AI education is helpful to enrich the study of primary and secondary school students and to prompt comprehensive quality. © 2018 IEEE.

关键词： Curricula

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An image processing method for green apple lesion detection in natural environment based on GA-BPNN and SVM

An image processing method for green apple lesion detection ...

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IEEE International Conference on Mechatronics and Automation

作者： Yunong Tian En Li Lei Yang Zize Liang The University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

The technologies of information processing, especially the image processing, are important technical means to realize intelligent management and control of modern orchard. In order to realize the intelligentization of orchard production, the orchard image database, especially the lesion image database needs to be set up. Because of the uneven illumination and the complex background under the natural light condition, traditional image segmentation methods cannot solve the adaptive threshold issue during the lesion image processing of green apples. This paper proposes an image processing method based on a BP neural network updated by genetic algorithm (GA-BPNN) and support vector machine (SVM) to realize lesion image processing of green apples in orchard. With this method, apple images can be processed in batch and the lesion image database can be consummated automatically. Furthermore, the recognition of the diseased apple is realized. The experimental results show that the proposed method can obtain green apple segmentation and lesion detection with good efficiency and robustness in complex natural orchard environment.

关键词： Lesions Image segmentation Diseases Training Green products Support vector machines

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Catching Dynamic Heterogeneous User Data for Identity Linkage Learning

Catching Dynamic Heterogeneous User Data for Identity Linkag...

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International Joint Conference on Neural Networks

作者： Fan Lei Qiudan Li Song Sun Lei Wang Daniel Dajun Zeng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

Benefitting from the development of social platforms, more and more users tend to register multiple accounts on different social networks. Linking user identities across multiple online social networks based on user behavior patterns is considerable for network supervision and information tracking. However, a user's online behavior in a social network is dynamic. The user profile may be changed due to some specific reasons such as user migration or job changes. Thus, catching the dynamics of evolutionary user data and collecting the latest user features are important and challenging issues in the area of user identity linkage. Inspired by deep learning models such as word2vec and DeepWalk, this paper proposes an integrated framework to catch the dynamic user data by supplementing vacant features and updating outdated features in data sources. The framework firstly represents all textual and structural user data into low-dimensional latent spaces by utilizing word2vec and DeepWalk, then, integrates different user features and predicts vacant data fields based on late fusion approach and cosine similarity computation. We then explore and evaluate the application of our proposed method in a user identity mapping task. The results proved that our framework can successfully catch the dynamic user data and enhance the performance of identity linkage models by supplementing and updating data sources advance with the times.

关键词： Couplings Data models Twitter Data mining Machine learning Task analysis

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Recognize User Intents in Online Interactions from Massive Social Media Data 2

Recognize User Intents in Online Interactions from Massive S...

引用

2017 IEEE 2nd International Conference on Big Data Analysis（ICBDA 2017）

作者： Chenxi Cui Wenji Mao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences

ISBN: (纸本)9781509036202

Online interactions,especially user generated contents on social events,reveal a variety of communicative purposes ranging from expressing feelings to proposing *** intents in users' online interactive behavior from massive social media data can effectively identify users' motives and intents behind communication and provide important information to aid monitoring,analysis and decision making for a variety of ***,user intents recognition from online communication is inherently challenging due to the ambiguity in semantic processing and diversity of syntax ***,the massive online data are usually unlabeled,which greatly hinders the usage of typical machine learning based methods that can automate the recognition *** this paper,we tackle this problem by proposing a Speech Act Theory guided classification scheme,which regards online communication as performative actions of users and classifies user utterances according to their pragmatic *** the basis of this,we construct a dictionary of performative words,expand it using external knowledge sources and refine it by word embedding and similarity *** then use this dictionary to automatically label the online textual data with *** a large amount of the labeled data,we train feature based classifiers to identify user intents in their online *** experimental study using a microblog dataset on social events from Sina Weibo shows the effectiveness of our proposed method.

关键词： user intent recognition speech act theory online communication social media big data

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Learning Insulators Segmentation from Synthetic Samples

Learning Insulators Segmentation from Synthetic Samples

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International Joint Conference on Neural Networks

作者： Wenkai Chang Guodong Yang Zhengxing Wu Zize Liang University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Neural networks always require extensive training samples. However, in some special applications, i.e., insulators in high power grid, it is very hard and costly to collect variety-rich samples. In this study, a synthetic method is proposed to generate segmentation training samples for the insulators. Instead of relying on full-fledged Computer Graphic, this study focuses on the training features of neural networks. Based on this synthetic approach, many kinds of insulators samples including positive, empty and fake ones can be constructed, and their quantities are particularly balanced by an equalization strategy. In order to validate these produced samples, three end-to-end segmentation networks are employed to adapt to the generators in an adversarial training framework. Meanwhile, an improved training strategy is utilized to speed up the convergence. Finally, extensive experiments are executed to further analyze the proposed synthetic method and demonstrate its effectiveness for insulators segmentation.

关键词： Insulators Training Image segmentation Feature extraction Inspection Generators Neural networks

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