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第三十四届中国控制会议

作者： ZHANG Ya TIAN Yu-Ping CAI Jun School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education 73658 Army

ISBN: (纸本)9781467374439

This paper studies the distributed filtering problem of sensor networks, where a set of heterogeneous sensing nodes is required to estimate the state of a linear discrete-time dynamic system in a collaborative manner. Due to limited sensing range and communication constraints, just part of sensors can get observations of the process and a consensus based sub-optimal filtering algorithm is designed. The convergence properties of the estimation error covariance is further studied, and a necessary and sufficient convergence condition is provided based on LMIs. This condition shows that the convergence of the algorithm requires the target node in the extended topology of network is globally reachable and each sensing node is observable to the process. Simulation examples are given to illustrate the results.

关键词： Distributed filter,Sensor networks,Consensus,Convergence analysis,LMIs

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Stability Analysis of Event-triggered Networked control systems with Time-Varying Delay 34

Stability Analysis of Event-triggered Networked Control Syst...

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第三十四届中国控制会议

作者： WANG Zhao SUN Jian CHEN Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467374439

Networked control systems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communications while still keeping a satisfactory performance of the system, by transmitting the state measurements only when an event-triggered condition is met. However,some network-induced problems would happen inevitably, such as communication delay. The delay can degrade the control performance significantly and can even lead to instability. In this paper, we study an NCS considering both ETC and time-varying delay, which is rare in the literature. We formulate the system as a discretized piecewise linear system with exponential uncertainty. Then the model is embedded in a polytopic approximation with better structure suitable for stability *** conditions are derived in terms of linear matrix inequalities(LMIs). Finally, the developed method is illustrated by a numerical example.

关键词： Networked control system,event-triggered control,time-varying delay,piecewise linear system,polytopic approximation,stability

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Performance Evaluation of the Deep Learning Approach for Traffic Flow Prediction at Different Times

Performance Evaluation of the Deep Learning Approach for Tra...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Yanjie Duan Yisheng Lv Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences

Traffic flow prediction is very important in the deployment of intelligent transportation system. Based on our previous research on deep learning approach for traffic data prediction, we further evaluates the performance of the SAE model for traffic flow prediction at daytime and *** 250 experimental tasks training a SAE model and evaluating its performance at daytime and nighttime with 3different criteria, we obtain the best combination of hyper parameters for each criterion at different times on weekday and non-weekday, respectively. Experimental results show that the MAE and RMSE at daytime are larger than that at nighttime,while the MRE at daytime are smaller than that at *** different criteria, the hyper parameters of the SAE model should vary accordingly. The results in this paper indicate that in real applications, traffic flow prediction using the deep learning approach can be a combination of multiple SAE models with different parameters suitable for different periods, which is of significance in future research.

关键词： SAE MAE Performance Evaluation of the Deep Learning Approach for Traffic Flow Prediction at Different Times

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A Simple and Effective Method For the Use of Chemical Accident Cases

A Simple and Effective Method For the Use of Chemical Accide...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Sifeng.Jing Xiwei.Liu Chuanzhong.Xu Institute of Smart Education Systems Qingdao Academy of Intelligent Industries The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Refinery No.2 Petro China Fushun Petrochemical Company

past chemical industry accident cases include volume valuable information like precursor, equipment involved, relevant causes and experiences of emergence response. In-depth analysis and fully utilization of these information play an important decision-making role in controlling risk and enhancing safety performance in chemical industry. In this work, a survey of use of accident data is conducted around the world and the result shows that the detailed use of these information play an important role in preventing accidents. However, in china there much more needs to be done in the application of accident data. According to the needs of safety management of chemical plants, a simple and effective method of the use of chemical accident cases is proposed based on collecting and analyzing of a large number of chemical accident cases. And finally, a utilization system of chemical industry accident cases is implemented through Microsoft access 2010. The result shows that the system can realize the effective management and use of past chemical accident information.

关键词： chemical accident cases use of information database fuzzy query chemical safety performance

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Kinematics and dynamics modelling of all terrain articulated tracked vehicles

Kinematics and dynamics modelling of all terrain articulated...

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World Congress on Intelligent control and Automation (WCICA)

作者： Hao Lin Wei Lin En Li Zize Liang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Zhenhai Refining & Chemical Company Dep. V Sinopec Ningbo China

ISBN: (纸本)9781467384155

This paper presents an extended kinematics and dynamics of the articulated tracked vehicles (ATV) used in many applications. The velocity of the front and the rear vehicle are firstly analysed and the kinematics of ATV is built, according to which the steer radius and the track velocity can be obtained. Then we analyse the force and moment acting on the ATV running on the firm ground and the soft ground, respectively. And a unified dynamics is established in a matrix form. To show the motion performance of the ATV, simulations are performed and the results are further presented.

关键词： Vehicles Force Vehicle dynamics Kinematics Dynamics Mathematical model Tracking

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An overview of recent progress in high-order nonholonomic chained system control and distributed coordination

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Journal of control and Decision 2015年第1期2卷 64-85页

作者： Jie Huang Jie Chen Hao Fang Lihua Dou School of Automation Beijing Institute of TechnologyBeijingChina State Key Laboratory of Intelligent Control and Decision of Complex Systems BeijingChina Fujian Institute of Education FuzhouChina

This paper reviews some main results and progress concerning with nonholonomic system control,especially focusing on the networked chained system *** controllability of nonholonomic system,the control method of nonholonomic system,the chained form transformation,the basic graph theory for multi-agent systems are recalled,*** important definitions,lemmas,theorems and dynamics are *** the consensus and formation control problems for networked nonholonomic chained systems are ***,some open questions are proposed.

关键词： distributed coordination multi-agent system nonholonomic system chained system high-order

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Image Clustering Based on Deep Sparse Representations

Image Clustering Based on Deep Sparse Representations

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IEEE Symposium Series on Computational Intelligence

作者： Le Lv Dongbin Zhao Qingqiong Deng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781509042418

Currently, the supervised trained deep neural networks (DNNs) have been successfully applied in several image classification tasks. However, how to extract powerful data representations and discover semantic concepts from unlabeled data is a more practical issue. Unsupervised feature learning methods aim at extracting abstract representations from unlabeled data. Large amount of research works illustrate that these representations can be directly used in the supervised tasks. However, due to the high dimensionality of these representations, it is difficult to discover the categorical concepts among them in an unsupervised way. In this paper, we propose combining the winner-take-all autoencoder with the bipartite graph partitioning algorithm to cluster unlabeled image data. The winner-take-all autoencoder can learn the additive sparse representations. By the experiments, we present the properties of the sparse representations. The bipartite graph partitioning can take full advantage of them and generate semantic clusters. We discover that the confident instances in each cluster are well discriminated. Based on the initial clustering result, we further train a support vector machine (SVM) to refine the clusters. Our method can discover the categorical concepts rapidly and the experiment shows that the clustering performance of our method is good.

关键词： supervised trained deep

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P-94:Distinguished Student Poster: Three Dimensional Lenticular Display Rendering Based on Light Field Acquisition

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SID Symposium Digest of Technical Papers 2017年第1期48卷

作者： Renjing Pei Zheng Geng Kui Ma Zhang Mei Wang Rong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences East Zhongguanchun Road No. 95 Haidian District Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 101408 China

Crosstalk is a critical defect affecting quality in 3D displays. Existing methods require tedious computations or device-specific optical measurements and results are often sub-optimal for 3D productions. We propose a method based on light field acquisition and optimization for crosstalk reduction. Algorithms were developed and experimental results showed superior performance.

关键词： lenticular 3D display crosstalk optimization light field light field capture

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A Geometric Extension Design for Second-Order Nonlinear Agents Formation Surrounding a Sphere

A Geometric Extension Design for Second-Order Nonlinear Agen...

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第28届中国控制与决策会议

作者： Yang-Yang Chen Kai-Xuan Wang Ya Zhang Cheng-Lin Liu Qin Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University Chien-Shiung Wu College Southeast University Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan University College of information engineering Yangzhou University

ISBN: (纸本)9781467397155

This article deals with the problem of driving a family of second-order nonlinear agents to land on a sphere and formation tracking a set of given orbits on the sphere.A novel geometric extension called the concentric compression method is proposed to give a solution to spheral landing and then combines with the control of spherical meridian and parallel to achieve formation motion along given orbits on the *** asymptotic stability of system is proved by Lyapunov-based method when the communication topology is *** effectiveness of the analytical result is verified by a numerical simulation.

关键词： Formation tracking Sphere landing Geometric Extension Second-Order Nonlinear Agents

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Decentralized adaptive neural network sliding mode control for reconfigurable manipulators with data-based modeling

Decentralized adaptive neural network sliding mode control f...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yuanchun Li Guibin Ding Bo Zhao Bo Dong Guangjun Liu Department of Control Engineering Changchun University of Technology Changchun Jilin Province China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Department of Aerospace Engineering Ryerson University Toronto Ontario Canada

ISBN: (纸本)9781509006212

In this paper, a decentralized adaptive neural network sliding mode control scheme is proposed for trajectory tracking control problem of reconfigurable manipulators based on data-based modeling. This method can be implemented to reconfigurable manipulators with different configurations and degrees of freedom without modifying any control parameters. Different from the previous works, the proposed control strategy is applied to mechanism model and data-based model of reconfigurable manipulators, respectively. The data-based model which is more comprehensive and precise is trained by the BP neural network with sampled input-output data. The gradient descent method is used to attain higher identification precision. Then the asymptotical stability of the system is proved using the Lyapunov theorem. Simulations are presented to not only illustrate the effectiveness of the proposed decentralized control scheme, but make a detailed comparison for control performance of the two modeling methods.

关键词： Neural networks Manipulator dynamics Adaptation models Adaptive systems Mathematical model Decentralized control

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