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第29届中国控制与决策会议

作者： Xingyu Lv Bangjun Lei Shumin Fei Office of Educational Administration Guizhou Institute of Technology School of Electrical and Information Engineering Guizhou Institute of Technology Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

ISBN: (纸本)9781509046584

A nonhnear L disturbance attenuation control（DAC） of unified power flow controller（UPFC） is investigated in power system by using Hamiltonian function ***,the dissipative Hamiltonian structure of the UPFC system is established by means of variable ***,based on the obtained dissipative Hamiltonian structure,a nonhnear L DAC is put *** results on the two-area four-machine power system demonstrate the effectiveness and robustness of the nonhnear L DAC in comparison with that of direct feedback linearization control（DFLC） and add-On self-tuning（ST） control and PI *** research results show that the nonhnear L DAC has better performance than the other controls.

关键词： UPFC uncertain nonlinear dynamical system Hamiltonian function method nonlinear L2 DAC

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Semi-Global Stabilization via Homogeneous Output Feedback for a Class of Nonlinear Time-Delay systems

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Journal of systems Science & Complexity 2016年第6期29卷 1538-1552页

作者： WANG Pan CHAI Lin FEI Shumin Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University

The semi-global stabilization problem for a class of nonlinear systems with state time-delay is addressed in this paper. By using Lyapunov-Krasovskii functional method and homogeneous dom- ination approach, a homogeneous observer and an output feedback controller with a scaling gain are designed. Then the sealing gain is adjusted such that the closed-loop system is semi-global asymptoti- cally stable. A numerical example is presented to illustrate the effectiveness of the obtained results in this paper.

关键词： Homogeneous domination approach Lyapunov-Krasovskii functional nonlinear time-delay systems output feedback semi-global.

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A LiDAR Odometry for Outdoor Mobile Robots Using NDT Based Scan Matching in GPS-denied environments

A LiDAR Odometry for Outdoor Mobile Robots Using NDT Based S...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Bo Zhou Zhongqiang Tang Kun Qian Fang Fang Xudong Ma Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University

ISBN: (纸本)9781538604915

The three-dimensional localization problem of outdoor mobile robots is a primary issue for autonomous navigation applications, since the accuracy of positioning will affect the incoming mapping and path planning tasks heavily. In this paper, using INS, encoder and laser LiDAR as the main means for pose perception, a laser LiDAR aided odometry approach based on the normal distributions transform(NDT) scan matching approach is proposed to improve the precision of pose estimates for a mobile robot in GPS denied outdoor environments. The 3D kinematic model of the mobile robot is developed so that the IMU and the encoder data can be fused firstly to obtain the initial localization result with dead reckoning technologies. On that basis, the three-dimensional NDT scan matching method is introduced to compute the pose transformation matrix in real-time using the adjacent two depth frames from LiDAR data, which can get fine pose estimates by calibrate the accumulation errors periodically. Experiments results show the correctness and validity of the presented method.

关键词： Out mobile robots LiDAR odometry NDT matching Auxiliary positioning Outdoor mobile robot Nondestructive Testing Mobile robots Lidar positioning accuracy odometry scanning transformation matrix

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Mask-aware networks for crowd counting

arXiv

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arXiv 2018年

作者： Jiang, Shengqin Lu, Xiaobo Lei, Yinjie Liu, Lingqiao School of Computer Science University of Adelaide AdelaideSA5005 Australia Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China School of Automatic Southeast University Nanjing210096 China Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China College of Electronics and Information Engineering Sichuan University Chengdu610064 China School of Computer Science University of Adelaide AdelaideSA5005 Australia

Crowd counting problem aims to count the number of objects within an image or a frame in the videos and is usually solved by estimating the density map generated from the object location annotations. The values in the density map, by nature, take two possible states: zero indicating no object around, a non-zero value indicating the existence of objects and the value denoting the local object density. In contrast to traditional methods which do not differentiate the density prediction of these two states, we propose to use a dedicated network branch to predict the object/non-object mask and then combine its prediction with the input image to produce the density map. Our rationale is that the mask prediction could be better modeled as a binary segmentation problem and the difficulty of estimating the density could be reduced if the mask is known. A key to the proposed scheme is the strategy of incorporating the mask prediction into the density map estimator. To this end, we study five possible solutions, and via analysis and experimental validation we identify the most effective one. Through extensive experiments on five public datasets, we demonstrate the superior performance of the proposed approach over the baselines and show that our network could achieve the state-of-the-art performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Identity Recognition Based on Face Image

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Journal of Physics: Conference Series 2019年第3期1302卷

作者： Chen Qin Xiaobo Lu Pengguo Zhang Huibin Xie Wenbin Zeng School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China Zhejiang Uniview Technologies Co. Ltd Zhejiang 310018 China

This article is aimed at designing a human identity recognition algorithm based on face image, which will be used in indoor environment. As the working environment is set as indoor environment, the camera will not be affected much by illumination variation. The key is how to detect human face and handle the variation of facial pose. This article divides the whole recognition process into 4 parts: image pre-processing, face detection, face alignment, feature extraction and comparison. Face detection and feature extraction are the core functions and both realized by deep learning. The process of the whole algorithm can be described as following: images after pre-processing are fed to face detection network to get the locations of face and face landmarks. Then face alignment will be conducted. Finally, deep features of face will be extracted and compared. The unique features of this algorithm are its good performance of handling the variation of facial pose and its clear framework which allows the whole method can be easily adjusted and upgraded.

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A Deep Learning Approach for Vehicle and Driver Detection on Highway

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Journal of Physics: Conference Series 2019年第4期1187卷

作者： Peihua Lv Yang Zhang Xiaobo Lu Di Zhou School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China Zhejiang Uniview Technologies Co. Ltd Zhejiang 310018 China

The technology of the detection for vehicle and driver is a popular spot in these ten years. In particular, the driver detection is still a troubled question in the study of public security. In our paper, an algorithm based on YOLOv3 and support vector machine (SVM) is proposed for realizing the detection of vehicles on highway, as well as the detection and binary classification of people in the vehicles, so as to achieve the purpose of distinguishing drivers and passengers and form a one-to-one correspondence between vehicles and drivers. The effectiveness of the algorithm is verified under various complicated highway conditions. Compared with other advanced vehicle and driver detection technologies, the model has a good performance and is robust to road blocking, different attitudes and extreme lighting.

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Design and Implementation of General Source Simulation System Architecture

Design and Implementation of General Source Simulation Syste...

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2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS2017)

作者： Wei Chu Songyi Liu Key Laboratory of Information Systems Engineering Department of China Satellite Launch Measurement and Control System

Equipment development and daily training of C2 system need simulation intelligence which are provided by simulation system. This paper put forward a whole system architecture and integration framework which can improve the develop efficiency of source simulation system on the basis of the using demand analysis of simulation system. This may satisfy the demand of system flexibility and rapid deployment.

关键词： simulation system system architecture integration framework

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Multi-dimensional Taylor Network Optimal control of Aircraft Flight

Multi-dimensional Taylor Network Optimal Control of Aircraft...

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Chun-Peng Hu Hong-Sen Yan Yu Zhou School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

This paper will introduce the design of the multidimensional Taylor network(MTN) optimal control in the flight control of aircraft. The MTN optimal control, which combines the classical architecture o

ISBN: (纸本)9781467389808

关键词： Aircraft control Multi-dimensional Taylor network (MTN) controller Attitude control Simulation Aircraft control attitude control Air Travel network optimization simulating Classical architecture Taylor flight control(aircraft) Feedback control systems Optimal control Stability analysis

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Moving Vehicle Detection with Shadow Elimination Based on Improved ViBe Algorithm

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Journal of Physics: Conference Series 2019年第2期1302卷

作者： Xue Xia Xiaobo Lu Yichao Cao Shudong Xia Changqing Fu School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China Beijing PKU Trans Info Technology Co. Ltd Beijing 100193 China

Moving vehicle detection based on video processing has been widely used in intelligent transportation system recently. However there are also many problems, such as dynamic background, ghost region, and shadow of moving objects. This paper proposes an improved ViBe object detection algorithm. First, an accurate background image is obtained by using the multi-frame averaging method, and then the background model is initialized by this accurate background image, thus effectively reducing the generation of ghost region. Whenever there is no moving object for a fixed number of consecutive frames in the video, this frame is updated to the background image. Conservative update strategy and foreground point counting method are adopted to update the background and reduce the impact of dynamic background on the foreground detection. Next, the foreground image detected by improved ViBe algorithm is input into the shadow elimination method proposed in this paper. Shadows in foreground pixels are detected in RGB color space, and then the pixels determined as shadows are eliminated. Finally, accurate moving vehicles are obtained. Our algorithm can effectively eliminate the shadows of moving vehicles, quickly adapt to background changes and illumination mutation, and get accurate moving objects, which is helpful for vehicle contour extraction and subsequent image processing.

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Applicability analysis of bidding strategy in electricity market 3

Applicability analysis of bidding strategy in electricity ma...

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3rd International Conference on Mechanical, Electronic and Information Technology engineering, ICMITE 2017

作者： Zhou, Suyan Chen, Fei Qiao, Yahui Zhang, Wenzhe Zhang, Kaifeng Yuan, Kun Dai, Xuemei Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing210096 China Shanxi Electric Power Company Xi'an710082 China Hohai University Nanjing210098 China Chongqing Electric Power Company Chongqing404100 China

With the development of the electricity market, competition has been introduced in the generation side. It is the overall development trend of the electricity market reformulation to optimize the allocation of different resources through bidding. Therefore, it is significant to research the bidding strategies of the generation companies and the large consumers. This paper reviews the existing research methods of bidding strategy. According to the different market mechanisms, the market participators will choose different bidding strategies based on their own cases. We analyze the applicability of bidding strategies under the different conditions, and give suggestions on how to select bidding strategy for the different market participators under different conditions. © The Authors, published by EDP Sciences, 2017.

关键词： Power markets

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