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Collaborative Optimization of Cyber Physical Social systems for Urban Transportation Based on Knowledge Automation

IFAC-PapersOnLine 2020年第5期53卷 572-577页

作者： Gang Xiong Xiaoyu Chen Nan Shuo Yisheng Lv Fenghua Zhu Tianci Qu Peijun Ye State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China Graduate School of System Design Tokyo Metropolitan University Tokyo 191-0065 Japan

The integration of signals from physical, social and cyber spaces, known as Cyber-Physical-Social systems (CPSS), is a new research paradigm for urban transportation, where the traffic control and management (C&M) is collaborative optimized among the three sub-systems. Though some technologies and optimization methods have been studied since its proposition, there is a lack of a systemic architecture as well as an overall implementation about how to efficiently exploit the social signals. For this reason, this paper proposes a general framework of CPSS for urban transportation and presents a feasible solution for traffic optimization based on knowledge automation. The specific implementation includes basic modeling of CPSS, knowledge evolution and reasoning, and collaborative optimization of C&P strategies. As a remarkable highlight, the influence of both individual activities and social learning is concerned during knowledge evolution and reasoning part. A case study from the application in the city of Dongguan is also given to validate our proposed framework and methods, showing that they can efficiently improve the average speed of the actual transportation.

关键词： CPSS knowledge automation urban transportation Collaborative Optimization

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Surface Defect Classification of Steels Based on Ensemble of Extreme Learning Machines

Surface Defect Classification of Steels Based on Ensemble of...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Yanan Liu Ying Jin Hongbin Ma Beijing Institute of Technology Beijing P. R. China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China

In recent years, iron and steel industry of China has developed rapidly, and steel surface defects recognition has attracted wide attention in the field of industrial inspection. Aiming at the problems of poor precision and low speed of traditional surface defect detection methods, we propose to use a fully learnable ensemble of Extreme Learning Machines (ELMs), which is ELM-IN-ELM, for defect classification. The Local Binary Pattern is adopted as the basic feature extraction method. The ELM-IN-ELM determines the final classification decision by automatically learning the output of M independent ELM sub-models. To further illustrate the superiority of the ELM-IN-ELM algorithm for classification, the Northeastern University (NEU) surface defect database is used to evaluate its classification effect. The experimental results demonstrate that this method works remarkably well for surface defects classification. Compared with other methods, the proposed method can identify the types of defects more accurately, which is of practical significance to steel surface defect detection.

关键词： Steel Neural networks Training Inspection Surface treatment Feature extraction Binary codes

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Load Curve Modeling Based on Behavior Analysis of Distributed Power Customers

Load Curve Modeling Based on Behavior Analysis of Distribute...

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2019 4th Asia Conference on Power and Electrical Engineering (ACPEE 2019)

作者： Xinyang HAN Yu ZHANG Yuqiao JIAO Yue ZHANG Yanjing QU Min DING State Grid Energy Research Institute School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Shanghai Municipal Electric Power Company

As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load,this paper proposes a load curve modeling method for renewable power customers based on the behavior ***,customers' active behavior is represented by the quantity of active customer *** on the analysis of customer behaviors,a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo ***,with the inputs as the quantity of active customer households and time of photovoltaic power generation,an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical *** combing the average usage time of electrical appliances,load characteristics are analyzed based on usage state of electrical appliance of distributed power ***,the simulation results verify the effectiveness of the proposed method.

关键词： Carlo Monte Markov Load Curve Modeling Based on Behavior Analysis of Distributed Power Customers

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Blockchain-based Social Manufacturing for Customization Production

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IFAC-PapersOnLine 2020年第5期53卷 53-58页

作者： Xiuqin Shang Xi Chen Lulu Niu Gang Xiong Zhen Shen Xisong Dong Zhengchao Shen Chao Liu Bangwen Xi the Research Center of Precision Sensing and Control the state key laboratory for management and control of complex systems & Beijing engineering research center of intelligent systems and technology institute of automation Chinese Academy of Sciences Beijing 100190 China Beijing University of Posts and Telecommunications Beijing 100876 China Alstom Beizhong Power (Beijing) Co. Ltd. Beijing 100040 China the System Integration Electronics (Hangzhou)Co. LTD No. 58 No. 11 Road Foxconn Qiantang Tech-Industrial Area HETZ Hangzhou 310018 China

This paper proposes the social manufacturing based on Blockchain, which realizes precise and efficient customization through smart contract and distributed accounting. It is a new manufacturing mode of service-oriented, distributed and collaborative customization. This paper proposes the definition of SM based on Blockchain. In the process of using to Blockchain, it can form a strong trust relationship, so that multiple nodes / roles in SM can save the complete copy of the whole database, rather than a centralized permission / role. Secondly, the Blockchain-based SM system is developed for customized manufacturing. Finally, its application case and the optimization results are given. In SM, it is the key that how to transform customized manufacturing actions into socialized actions of manufacturing resources through internet communities and interconnect Socialized Manufacturing Resources (SMRs) in upstream and downstream. In this paper, the smart contract relationship is established based on Blockchain between SMRs to build credit mechanism in SM, Which can ensure the effective circulation and association of SMRs.

关键词： Social Manufacturing Blockchain Optimization SM Resources

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On Event-triggered Adaptive Robust control 36

On Event-triggered Adaptive Robust Control

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第36届中国控制会议

作者： Yuan Huang Junzheng Wang Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781538629185

In this work,an event-triggered adaptive robust controller（ET-ARC） design is considered for a continuous-time nonlinear system combined with structural uncertainties and parameter *** the event-trigger scheme,the controller only can obtain the sampled date of the output measurement at some certain instants determined by the designed triggering condition and therefore the performance of the ET-ARC depends on the triggering condition ***,in this work,for the adaptive robust control scheme,an event-triggered transmission strategy is proposed,which relies on the output measurement of the nonlinear ***,based on this strategy,the design idea of the adaptive robust controller is presented such that the tracking performance is ***,based on a more general assumption,we provide a possible formation of control signal which satisfies the requirement proposed.

关键词： Adaptive robust control event-triggered transmission parameter estimation

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A New Fast and Robust Template Matching with Randomness 29

A New Fast and Robust Template Matching with Randomness

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第29届中国控制与决策会议

作者： Chang Liu Yongqiang Bai Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509046584

Template matching is one of the most important techniques in computer vision,where the algorithm should find the location of template image in scene *** commonly used method of template matching is Normalized Cross Correlation which has a high matching accuracy while consuming a large amount of computational *** this paper,a novel,fast and robust template matching approach is *** new algorithm randomly visits the pixels and locates local maxima by gradually moving to the regions with larger NCC *** further improve the speed and accuracy of the algorithm,several additional rules are *** analysis and experimental results show that the proposed algorithm maintain a high matching accuracy while providing a significant speedup.

关键词： Template Matching Normalized Cross Correlation Brightness-contrast Invariance

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Artificial Neural Network Based Maximum Power Point Tracking for PV system

Artificial Neural Network Based Maximum Power Point Tracking...

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第三十八届中国控制会议

作者： Al-wesabi Ibrahim Min Ding Xiaoling Jin Xianzhong Dai Mohammad Abu Sarhan Muhammed Badeaa Shafik Hao Zhou School of Automation China University of Geoscience Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute School of electrical engineering and automation Wuhan university

Nowadays PV systems is suffering from two main problems: high production cost and low efficiency especially under variable weather conditions. Therefore, to reduce such associated problems, PV systems are being connected with various optimization controllers such as maximum power point tracking. In this paper, an artificial neural network maximum power point method has been designed to be linked between a PV system and DC-DC buck converter, and each part of the system is fully explained. The whole system was modeled under MATLAB/Simulink environment, simulation results demonstrated the efficiency of the proposed method. The proposed method has been examined to track the maximum power point under different weather conditions which shows a rapid and accurate tracking of the maximum power point(MPP) of PV system. The whole system which consists of PV arrays, Buck converter, ANN tracker, and load has been modeled using MATLAB/Simulink environment. This Simulink model has been examined using different levels of temperature and irradiation and the output results of both P-V and I-V characteristics, output power, and the system efficiency clearly demonstrate the validation of the modeled system. This demonstration has been done by comparing between the result of experimental platform and the results of simulated model which approves that ANN is highly recommended to be used in the field of maximum power point tracking of PV system.

关键词： Artificial neural network(ANN) Photovoltaic(PV) Maximum power point tracking(MPPT) Buck converter

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Loose Coupling Visual-lidar Odometry by combining VISO2 and LOAM 36

Loose Coupling Visual-lidar Odometry by combining VISO2 and ...

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第36届中国控制会议

作者： Min Yan Junzheng Wang Jing Li Chi Zhang Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

ISBN: (纸本)9781538629185

Odometry is a very popular research direction in recent decades and plays a very critical role in the autonomous navigation ***02,as a relatively robust and mature visual odometry algorithm,becomes unreliable when distinct visual features are insufficiently or when the texture of the environment is *** if not in such a challenging environment,the drift is still a big problem for the practical ***,a lidar odometry algorithm,has been leading the way for the performance on KITTI data *** fact,it also has limitations in shape features not prominent environment,like a highway with few buildings *** that the current mobile unmanned platforms（e.g.,unmanned vehicles） are almost equipped with both lidar and cameras,this paper proposes a loose coupling visual-lidar odometry by combining VIS02 and LOAM to achieve the advantages of both camera and lidar and reduce the number of restricted *** algorithm proposed in this paper is tested on the raw data set of *** average translation error is about 1.37% on 10 sequences,and the accuracy is improved with respect to LOAM with the same *** the help of VIS02,the algorithm also performs well in shape features not prominent environment（e.g.,highway）,and from the experiment results,we confirmed the efficient strategy to combine VIS02 and LOAM to adapt to challenging environment and to keep the accuracy of the algorithm.

关键词： Ego-motion Estimation Visual Odometry Lidar Odometry SLAM

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Observer-based Finite Time Dissipative control for Nonlinear Discrete Time-varying system with Time-varying Delay

Observer-based Finite Time Dissipative Control for Nonlinear...

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American control Conference

作者： Menghua Chen Jian Sun Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9781538654293;9781538654286

This paper addresses an observer-based finite time dissipative control problem for nonlinear discrete time-varying systems with time-varying delay. The nonlinear perturbation is subject to the Lipchitz condition. On the basis of a newly augment time-varying Lyapunov-like functional, delay-dependent conditions are obtained using the discrete Wirtinger-type inequality. The conditions ensure that the closed-loop system is finite time bounded (FTB) as well as the dissipative performance is satisfied. Then the observer-based time-varying control problem is achieved by solving a class of recursive linear matrix inequalities (RLMIs). Two examples illustrate the feasibility and superiority of the proposed method.

关键词： Time-varying systems Delays Linear matrix inequalities Symmetric matrices Closed loop systems Observers Asymptotic stability"

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Obstacle Information Detection Based on Fusion of 3D LADAR and Camera 36

Obstacle Information Detection Based on Fusion of 3D LADAR a...

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第36届中国控制会议

作者： Jing Li Liuzhi Yu Junzheng Wang Min Yan Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781538629185

Obstacle information detection is a prerequisite for safety and stability driving of unmanned platforms in the unknown *** detection of the obstacle using the 3D laser radar(3D LADAR) and camera is proposed in this ***,joint calibration between 3D LADAR and camera based on the planar feature method is ***,laser point cloud is clustered to identify the number of obstacles,and then detected image is divided into the corresponding small regions according to the number of ***,we use the image processing technology to detect the obstacle *** experiments in the real world are implemented to show that the proposed approach can effectively detect the size of the obstacles.

关键词： Obstacle detection Joint calibration Monocular camera 3D LADAR Information fusion

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