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第29届中国控制与决策会议

作者： Ding Wang Chaoxu Mu Derong Liu The 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 School of Electrical and Information Engineering Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509046584

A neural-network-based adaptive critic control method is established for continuous-time input-affine uncertain nonlinear systems to achieve disturbance *** present problem can be formulated as a two-player zero-sum differential game and the adaptive critic mechanism is employed to solve the minimax optimization problem.A neural network identifier is developed to reconstruct the unknown dynamical *** optimal control law and the worst-case disturbance law are designed by introducing and training a critic neural *** effectiveness of the present self-learning control method is also illustrated by a simulation experiment.

关键词： Adaptive critic control Adaptive dynamic programming Approximate dynamic programming Disturbance rejection Learning systems Neural networks Nonlinear control

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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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Local dominant orientation feature histograms (LDOFH) for face recognition

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Applied Informatics 2017年第1期4卷 1-10页

作者： Cui, Xinfang Zhou, Peng Yang, Wankou School of Automation Southeast University Nanjing China Key Lab of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

This paper presents a simple and robust feature descriptor method, namely local dominant orientation feature histogram (LDOFH). In this method, the discriminant histogram contains dominant orientation, and the corresponding relative energy value is obtained by calculating the direction and the amplitude of the gradient of each pixel over a local patch. The LM-NNDA (Yang et al. in Pattern Recognit 44:1387–1402, 2011) method based on the principal component analysis (PCA) method is finally employed to reduce the redundancy information and get the low-dimensional and discriminative features. We apply this descriptor on AR, IMM face image databases. Experimental results demonstrate the effectiveness of the proposed LDOFH method.

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Modeling the throughput of IEEE 802.15.4 based wireless networks under interference

Modeling the throughput of IEEE 802.15.4 based wireless netw...

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Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Bing Han Xianghui Cao Hongbao Shi School of Automation and the Key Lab of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing Jiangsu China

ISBN: (纸本)9781538629024

The IEEE 802.15.4 standard is the basis of many protocol suites such as ZigBee, WirelessHART and MiWi popular in Internet of Things systems, wireless sensor networks, and industrial wireless networks. In practice, due to its working bands are free to access, IEEE 802.15.4 based networks often suffer from interference which will deteriorate the network performance. In this paper, we model the interference as an on-off process and propose a new analytical model for IEEE 802.15.4 based networks which quantitatively characterizes how such interference affects the network throughput. We also conduct extensive simulations which demonstrate the accuracy of the model.

关键词： Interference IEEE 802.15 Standard Throughput Analytical models Data models Protocols Wireless networks

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Event-based Cubature Kalman Filter for Smart Grid Subject to Communication Constraint

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IFAC-PapersOnLine 2017年第1期50卷 49-54页

作者： Li S. Li Z. Li J. Wang Q. Song Z. Chen Z. Sheng Y. Liu X. Liu Y. School of Automation and Key Laboratory for Intelligent Control Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China Department of control science and engineering Harbin Institute of Technology Harbin 150001 China

Accurate real-time estimation plays an important role in smart grids. Although various filtering algorithms, such as unscented Kalman filter (UKF), have been proposed for phasor measurement unit (PMU), they occupy huge communication bandwidth without specific concern, which puts heavy burden on the communication network especially when wireless communications are applied. In order to relief this burden, the event-based cubature Kalman filter (EBCKF) is proposed based on event-based schemes in this paper. The event-based strategy guarantees that only the observations containing innovational information are transmitted, and cubature Kalman filter (CKF), which is based on the spherical cubature integration, provides more accurate estimation than UKF. Besides, the design-oriented communication rate is provided corresponding to the event-based strategy design. The proposed filter can effectively reduce the communication rate while ensuring the accuracy of filtering. Finally, the standard IEEE 39-bus system is utilized to verify the feasibility and performance of the proposed method. © 2017

关键词： communication rate dynamic state estimation Event-based cubature Kalman filter (EBCKF) IEEE 39-bus phasor measurement unit (PMU)

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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 042061-042061页

作者： Lv, Peihua Zhang, Yang Lu, Xiaobo Zhou, Di 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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PID2018 benchmark challenge: Model-based feedforward compensator with a conditional integrator ??

arXiv

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arXiv 2018年

作者： Yuan, Jie Ates, Abdullah Dehghan, Sina Zhao, Yang Fei, Shumin Chen, YangQuan School of Automation Southeast University Nanjing210096 China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey Mechatronics Embedded Systems and Automation Lab University of California MercedCA95340 United States School of Science and Engineering Shandong University Jinan250061 China Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing210096 China

Since proportional-integral-derivative (PID) controllers absolutely dominate the control engineering, numbers of different control structures and theories have been developed to enhance the effciency of PID controllers. Thus, it is essential and inspiring to operate different PID control strategies to the PID2018 Benchmark Challenge. In this paper, a novel control strategy is designed for this refrigeration system, where a feedforward compensator and a conditional integrator are utilized to compensate the disturbances and remove the steady-state error in the benchmark problem, respectively. The simulation results given in the benchmark problem show the straightforward effectiveness of the proposed control structure compared with the existing control methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Disturbance rejection

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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 022080-022080页

作者： Xue Xia Lu, Xiaobo Cao, Yichao Xia, Shudong Fu, Changqing 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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