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A hierarchical urban network control with integration of demand balance and traffic signal coordination

IFAC-PapersOnLine 2016年第3期49卷 31-36页

作者： Zhou, Zhao Lin, Shu Xi, Yugeng Li, Dewei Zhang, Jun Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control Information Processing Ministry of Education of China Shanghai200240 China School of Computer and Control Engineering University of Chinese Academy of Science Beijing100049 China Joint Institute of UM-SJTU Shanghai Jiao Tong University Shanghai200240 China

This paper concerns the integration of demand balance control and traffic flow coordination control in a hierarchical framework for complex urban traffic networks. At the first level, a complex traffic network is first partitioned into several subnetworks. The traffic dynamics in each subnetwork is modeled by utilizing the concept of Macroscopic Fundamental Diagram (MFD), which relates the network-wide space-mean flow and the number of vehicles at the aggregated level. This model aims at designing a demand balance model predictive controller (MPC), which can improve the internal flow inside the subnetwork by regulating the input flows from outside. At the second level, based on a more detailed traffic flow model, the signal timings of all intersections for each subnetwork are determined by a flow coordination MPC controller, which aims at distributing the number of vehicles in each subnetwork as homogeneously as possible. The effectiveness of the proposed approach is investigated via simulation under different scenarios on a hypothetical urban traffic network, and the performance is compared with other control strategies. © 2016

关键词： Street traffic control

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A Comparing Study on Assessment Mechanism for Renewable Energy Bidding Deviation in Spot Trading 5

A Comparing Study on Assessment Mechanism for Renewable Ener...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Wang, Hao Zhang, Li Guo, Yixin Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China North China Electric Power University School of Electrical and Electronic Engineering Baoding China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Participating in market trading is an essential step to promote the sustainable development of renewable energy. To properly deal with the uncertainty of renewable energy, it is important to establish a reasonable bidding deviation assessment mechanism in the electricity market. Based on the analysis of existing research and practice, the bidding deviation assessment mechanism are summarized into two categories, that is, the outcome assessment mechanism (OAM) and the performance assessment mechanism (PAM). Models of the mechanism are built to analyze the principles of the two types of mechanism, and the impact of aggregation effect of renewable energy on the assessment is discussed. Simulation results show that the outcome assessment mechanism will lead to over-assessment, but is conducive to motivating renewable energy stations (RSs) to actively reduce bidding deviation;while the performance assessment mechanism can ensure the cost-recovering of balancing dispatch, but make RSs unable to improve market behavior except to passively accept penalties at settlement. To promote the development of renewable energy, both assessment mechanisms have room for further improvement. © 2022 IEEE.

关键词： Power markets

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Design of an Industrial Wireless Sensor Network Security Defense Scheme Based on the Uniqueness of Clock Slope 4

Design of an Industrial Wireless Sensor Network Security Def...

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4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Shao, Shuai Dong, Lei Wang, Zhongfeng Cui, Shijie Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Southeast University Key Laboratory of Mems of the Ministry of Education School of Electronic & Engineering Nanjing China

ISBN: (纸本)9798350363586

This paper proposes a security defense scheme for industrial wireless sensor networks that utilizes the uniqueness and stability of clock slope characteristics to address the security defense challenges faced by industrial wireless sensor networks (IWSNs) under the constraints of low power consumption and low cost. By combining key elements of time synchronization technology, this scheme fully leverages the physical characteristics of the clock slope without the need to introduce additional protocols or algorithm designs, ensuring compatibility with existing time synchronization technology and providing an effective method for node identity recognition in large-scale IWSN environments. © 2024 IEEE.

关键词： Mechanical clocks

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Artificial Intelligence-based Fault Detection and Diagnosis: Towards Application in a Chemical Process

Artificial Intelligence-based Fault Detection and Diagnosis:...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Liu, Yiqi Li, Zhi Chen, Hongtian The School of Automation Science & Engineering Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangzhou510640 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9798350337754

As the chemical processes become more and more complicated, it is crucial but also difficult to detect and diagnose faults in the system than ever. With the development of machine learning algorithms and cloud computing, to monitor chemical processes completely with the help of big data become true. However, most machine learning methods suffer from unexplainable problem. By employing Explainable Artificial Intelligence(XAI) techniques, this paper applies two kinds of unsupervised machine learning methods, One-Class Support Vector Machine and Depth-based Isolation Forest Feature Importance, to detect and diagnosis faults in a chemical process. By combining two different fault explanation methodologies, accuracy and reliability of the fault diagnosis results can be achieved by the validation in a simulated continuous stirred tank reactor. © 2023 IEEE.

关键词： Support vector machines

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A Brief Research and Lookback of the Development of Iris Recognition

A Brief Research and Lookback of the Development of Iris Rec...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Li, Xiaoshuang Hu, Shenhua Lv, Chengkan Qin, Haojun Zhu, Fenghua Wang, Feiyue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing China School of Electrical Engineering and Aotumation Wuhan University Wuhan China

ISBN: (纸本)9781728128535

Personal identification has been used more and more widely in information society. Iris recognition, as one of numerous identification methods, has already been applied in many situations, because the iris patterns have stable, unique and non-invasive features. We analyze the general process of iris recognition in this paper, including image preprocessing, feature extraction, classification and recognition. We also study the progress in iris recognition brought by deep learning method. It is our belief that traditional approaches play a very significant role in iris recognition field, while deep learning methods will make a great difference to iris recognition. © 2019 IEEE.

关键词： Deep learning

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Safety-Critical Line-of-Sight Path Following Guidance of an Under-Actuated Maritime Autonomous Surface Ship Based on Robust Optimization 42

Safety-Critical Line-of-Sight Path Following Guidance of an ...

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42nd Chinese control Conference, CCC 2023

作者： Li, Jianzhong Peng, Zhouhua Liu, Lu Wang, Dan Wang, Anqing Gu, Nan School of Marine Electrical Engineering Dalian Maritime University Dalian116026 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China

ISBN: (纸本)9789887581543

This paper is concerned with the path following guidance problem at kinematic level for a maritime autonomous surface ship (MASS) sailing in a constrained water with static and dynamic obstacles. A safety-critical line-of-sight (LOS) path following method is proposed based on control barrier functions. Specifically, an LOS guidance law is firstly designed to achieve the straight-line path following task. Next, collision avoidance with channel boundaries and static/dynamic obstacles are encoded in the control barrier functions, where robust optimization is used to ensure the constraint satisfaction in the presence of external disturbances. Then, safety-critical guidance signals are obtained by solving two quadratic programming problems. By using the proposed method, the MASS is capable of accomplishing the path following task with guaranteed input-to-state safety. Simulation results are given to substantiate the efficacy of the proposed path following guidance law for the MASS sailing in constrained water region subject to external disturbance. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Quadratic programming

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Improving Data Utility Through Game Theory in Personalized Differential Privacy

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Journal of Computer Science & Technology 2019年第2期34卷 272-286页

作者： Lei Cui Youyang Qu Mohammad Reza Nosouhi Shui Yu Jian-Wei Niu Gang Xie College of Information and Computer Taiyuan University of Technology Taiyuan 030024 China School of Information Technology Deakin University Melbourne VIC 3125 Australia School of Software University of Technology Sydney Sydney NSW 2007 Australia School of Computer Science and Engineering Beihang University Beijing 100191 China Shanxi Key Laboratory of Advanced Control and Intelligent Information System Taiyuan University of Science and Technology Taiyuan 030024 China

Due to dramatically increasing information published in social networks,privacy issues have given rise to public *** the presence of differential privacy provides privacy protection with theoretical foundations,the trade-off between privacy and data utility still demands further ***,most existing studies do not consider the quantitative impact of the adversary when measuring data *** this paper,we firstly propose a personalized differential privacy method based on social ***,we analyze the maximum data utility when users and adversaries are blind to the strategy sets of each *** formalize all the payoff functions in the differential privacy sense,which is followed by the establishment of a static Bayesian *** trade-off is calculated by deriving the Bayesian Nash equilibrium with a modified reinforcement learning *** proposed method achieves fast convergence by reducing the cardinality from n to *** addition,the in-place trade-off can maximize the user's data utility if the action sets of the user and the adversary are public while the strategy sets are *** extensive experiments on the real-world dataset prove the proposed model is effective and feasible.

关键词： personalized privacy protection game theory trade-off reinforcement learning

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Disturbance Observation and control of Operational Unmanned Aerial Vehicles

Disturbance Observation and Control of Operational Unmanned ...

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2023 IEEE International Conference on Unmanned Systems, ICUS 2023

作者： Yao, Guanyu Yang, Liying Chang, Yanchun He, Yuqing School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350316308

UAVs are used widely in all works and life, and their operation forms and application scenarios are more complex than ever before. In order to deal with various disturbances faced by operational UAVs in application scenarios and achieve stable control, a disturbance observation and compensation structure combining linear extended state observer and sliding mode controller is proposed to achieve stable control of operational UAVs. Firstly, the typical operational UAV is taken as the research object, and the kinematics and dynamics models are established. Then, a linear extended state observer is designed to estimate the environment and body disturbances, and the sliding mode control method is combined to control the system. Finally, the effectiveness of the designed control method is verified through simulation. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Multi-view local learning

Multi-view local learning

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23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08

作者： Zhang, Dan Wang, Fei Zhang, Changshui Li, Tao State Key Laboratory on Intelligent Technology and Systems Department of Automation Tsinghua University Beijing 100084 China School of Computer Science Florida International University Miami FL 33199 United States

ISBN: (纸本)9781577353683

The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. However, the local learning methods developed so far are all devised for single-view problems. In fact, in many real-world applications, examples are represented by multiple sets of features. In this paper, we extend the idea of local learning to multi-view problem, design a multi-view local model for each example, and propose a Multi-View Local Learning Regular-ization (MVLL-Reg) matrix. Both its linear and kernel version are given. Experiments are conducted to demonstrate the superiority of the proposed method over several state-of-the-art ones. Copyright © 2008, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Artificial intelligence

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Vehicle object detection based on rgb-camera and radar sensor fusion

Vehicle object detection based on rgb-camera and radar senso...

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2019 International Joint Conference on Information, Media, and Engineering, IJCIME 2019

作者： Li, ZhongTong Yan, Ming Jiang, Wei Xu, Pin School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781728155869

Object detection has always played a major role in the field of computer vision. With the development of faster region-based convolutional neural network (faster-RCNN), single shot multi-box detector (SSD), You Only Look Once (Yolo) and other deep learning networks, 2D object detection has been developed well developed. However, in some key areas, such as driverless vehicles and artificial intelligence robots, cannot meet the requirements of tasks just by detecting two dimensional (2D) objects. So we need to get the three dimensional (3D) position of the object. In 3D object detection, it is difficult to obtain object position information only by red-green-blue (RGB) image. There are some methods to get the 3D position of the target through the point cloud data set. Therefore, this paper proposes a deep learning network, which can combine both color image information and point cloud geometry information, while using MobileNet V3 as the backbone network greatly enhances the operation speed. The region proposal networks (RPN) layer in faster-RCNN is migrated to the network. After testing, the method proposed by us improves obviously in speed and recognition accuracy compared with the previous methods. © 2019 IEEE.

关键词： Object detection

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