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作者： Chen, Wenjie Liu, Jin Gan, Ming-Gang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

Algorithm based on NMI feature matching and Position Prediction for automatic target tracking are develop for realize an DSP based real-time target tracking system. The target is firstly detected with a improved frame-difference method, and then the target area is segmented based on threshold segmentation and region growth. The NMI feature is used for matching. Finally a combining forecast algorithm is used in the tracking system. This tracking system is implemented with a DSP controller and software is accomplished on DSP/BIOS operation system. It is proved that it can be meet the needs of real-time stably tracking and overcome the disturbance brought by attitude variances and short time occlusion.

关键词： Target tracking

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Denoising of fiber optic gyroscope signal by unsupervised adaptive filtering

Denoising of fiber optic gyroscope signal by unsupervised ad...

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作者： Ma, Tao Chen, Jie Chen, Wenjie Zhang, Bo School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

Angle random walk (ARW) is the noise component at the output of a fiber optic gyroscope (FOG) and it affects the FOG short-term accuracy. Using only the noise property described by random walk coefficient, we developed an unsupervised adaptive filter (UAF) for suppressing the noise. Theoretical analysis illuminates that UAF performs as good as the best FIR filter in the sense of means square. Experimental results both in stationary and non-stationary cases show that UAF is more effective than wavelet denoising and that based on fast fourier transform.

关键词： Adaptive filters

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Application of an improved independent component analysis to artifacts removal from EEG

Application of an improved independent component analysis to...

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作者： Peng, Zhihong Luo, Junping School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

EEG data can be easily influenced by other components in the process of recording, which would thus interfere the analysis. Independent Component Analysis (ICA) is a valid method for blind source separation. It can estimate original signals' independent components from observed signals even the original signals and mixing model are unknown. Considering the shortcomings of the application of two ICA algorithms, FastICA and extended Infomax, to EEG artifacts removal, we propose a novel InfastICA algorithm by combing FastICA and extended Infomax. By appling to removal of the EOG artifacts from EEG, test results show that this new algorithm has no special requests to the matrix W's default values and study steps, and has a fast convergence speed, with simple operation and practical application.

关键词： Independent component analysis

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An image mosaicing approach for video sequences based on space-time manifolds

An image mosaicing approach for video sequences based on spa...

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作者： Zou, Li-Hui Chen, Jie Zhang, Juan Dou, Li-Hua School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

In order to utilize the repetitive information among the video sequence more reasonably, this paper proposes an image mosaicing approach based on space-time manifolds for the video sequence taking the properties of high-overlapped ratio between neighbor frames and multiple frames into account. Firstly, we iterate Lucas-Kanade optical flow under Gaussian pyramid strategy to compute the motion parameters between neighbor frames with higher accuracy and align the sequence, in the meantime, eliminate the brightness difference among the neighbors combining with the result of motion computation, and then stitch together the whole sequence whose brightness is already uniform into a high resolution image using the space-time manifolds mosaicing technique. It was verified by the experiment that the proposed approach was very effective to video sequences and the mosaicing result was nice.

关键词： Optical flows

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Detection of stealthy false data injection attacks against networked control systems via active data modification

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Information Sciences 2021年 546卷 192-205页

作者： Zhong-Hua Pang Lan-Zhi Fan Jian Sun Kun Liu Guo-Ping Liu Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology Beijing 100144 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 China Department of Artificial Intelligence and Automation Wuhan University Wuhan 430072 China

This paper investigates the design and detection problems of stealthy false data injection (FDI) attacks against networked control systems from the different perspectives of an attacker and a defender, respectively. First, a Kalman filter-based output tracking control system is presented, where stealthy FDI attacks are designed for its feedback and forward channels so as to destroy the system performance while bypassing a traditional residual-based detector. Second, to successfully detect such two-channel stealthy attacks, an active data modification scheme is proposed, by which the measurement and control data are amended before transmitting them through communication networks. Theoretical analysis is then carried out for both ideal and practical cases to evaluate the effectiveness of the detection scheme. An interesting finding is that the attacks designed based on a false model obtained from those modified data can remain stealthy. Finally, simulation results are provided to validate the proposed attack design and detection schemes.

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Neural network structure design based on N-gauss activation function1

arXiv

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arXiv 2021年

作者： Lu, Xiangri Ma, Hongbin Zhang, Jingcheng State Key Laboratory of Intelligent Decision and Control for Complex Systems Beijing Institute ofTechnology Beijing China Institute of Pattern Recognition and Intelligent Systems School of Automation Beijing Institute ofTechnology China Institute of Navigation Guidance and Control School of Automation Beijing Institute of

Recent work has shown that the activation function of the convolutional neural network can meet the Lipschitz condition, then the corresponding convolutional neural network structure can be constructed according to the scale of the data set, and the data set can be trained more deeply, more accurately and more effectively. In this article, we have accepted the experimental results and introduced the core block N − Gauss, N − Gauss, and Swish (Conv1, Conv2, FC1) neural network structure design to train MNIST, CIFAR10, and CIFAR100 respectively. Experiments show that N − Gauss gives full play to the main role of nonlinear modeling of activation functions, so that deep convolutional neural networks have hierarchical nonlinear mapping learning capabilities. At the same time, the training ability of N − Gauss on simple one-dimensional channel small data sets is equivalent to the performance of ReLU and Swish. Copyright © 2021, The Authors. All rights reserved.

关键词： Gaussian distribution

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A novel GIS platform for UGV application in the unknown environment

A novel GIS platform for UGV application in the unknown envi...

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International Conference on Geoinformatics

作者： Qiangrong Yang Meiling Wang Mei-po Kwan Yi Yang Key Laboratory of Intelligent Control and Decision of Complex System Beijing China School of Automation Beijing institute of Technology Beijing China Department of Geography and Geographic Information Science University of Illinois at Urbana Champaign Champaign IL USA

ISBN: (纸本)9781467376648

Recently, the UGV (Unmanned Ground Vehicle) receives more and more attention from the public with the application in deep space exploration, national defense, and riot relief. Moreover, how to describe the driving environment of UGV with the sensor data objectively and share these data with other UGV efficiently becomes the focus of the research of the UGV. To solve the above problems, a novel GIS platform for UGV application in the unknown environment is proposed in this paper based on the features of UGV. First, the GIS database is redesigned and the properties such as road width, lane number, lane info, and if_traffic are proposed. The data structure of the database is redesigned to fit the need of UGV to describe the environment simply and explicitly. Then a two-line road model is proposed to model the feature of the road network clearly. This model can meet the driving need of UGV and represent the traffic rules of the urban environment. Moreover, the turning path in the intersection is designed to be an arc instead of a right angle path considering the dynamic features of UGV. Finally a cost map for navigating the UGV locally is generated with the road model and the environment information from the sensors. The GIS platform designed in this paper proves to be able to offer guidance and help to UGV for driving through the unknown environment wisely and quickly without human intervention. And it shows promising application of sharing data with other UGV efficiently by using cost map instead of the original sensor data.

关键词： Navigation Vehicles Robots

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On the nonexistence of event-based triggers that preserve Gaussian state in presence of package-drop

On the nonexistence of event-based triggers that preserve Ga...

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American control Conference

作者： Enoch Kung Junfeng Wu Dawei Shi Ling Shi Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Automatic Control The Royal Institute of Technology (KTH) State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781509045839

state estimation is a core objective in cyber-physical systems. In the state estimation problem over linear systems, the Kalman filter is the standard solution. The filter is the format on which the solutions to subsequent estimation problems are based. Among these problems are the estimation problem in the presence of packet drops and estimation problem involving event-based triggers. We study in this paper both phenomena simultaneously. In an attempt to find the Kalman-like filter, which proves the Gaussianity of the state and offers a set of update equations, our paper shows that no such filter exists. More precisely, one cannot find an event-based trigger such that under possible packet drops, the state variable remains a Gaussian variable. This conclusion can be reasonably extended to a more general setting.

关键词： state estimation Packet drops Event-based triggers state estimation Event-based Filters state variable TRIGGERS Gauss

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Design of a multi-functional supervising terminal

Design of a multi-functional supervising terminal

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作者： Du, Le Chen, Jie Deng, Fang Beijing Institute of Technology Chinese Academy of Sciences Beijing 100080 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

In order to watch the status of a system, a multi-functional terminal is necessary. This paper discusses the function of the terminal, the theory or principle which the design based on, the design of the hardware and the software. For the hardware, we use MCU C8051F as the controller. The peripheral circuit design includes the power module, serial port module etc. For the software, we use the idea of multi-layers design including the driver layer and application layer.

关键词： Application programs

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Bayesian optimization assisted meal bolus decision based on gaussian processes learning and risk-sensitive control

arXiv

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arXiv 2021年

作者： Cai, Deheng Liu, Wei Ji, Linong Shi, Dawei State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Department of Endocrine and Metabolism Peking University People’s Hospital Beijing China

Effective postprandial glucose control is important to glucose management for subjects with diabetes mellitus. In this work, a data-driven meal bolus decision method is proposed without the need of subject-specific glucose management parameters. The postprandial glucose dynamics is learnt using Gaussian process regression. Considering the asymmetric risks of hyper- and hypoglycemia and the uncertainties in the predicted glucose trajectories, an asymmetric risk-sensitive cost function is designed. Bayesian optimization is utilized to solve the optimization problem, since the gradient of the cost function is unavailable. The proposed approach is evaluated using the 10-adult cohort of the FDA-accepted UVA/Padova T1DM simulator and compared with the standard insulin bolus calculator. For the case of announced meals, the proposed method achieves satisfactory and similar performance in terms of mean glucose and percentage time in [70, 180] mg/dL without increasing the risk of hypoglycemia. Similar results are observed for the case without the meal information (assuming that the patient follows a consistent diet) and the case of basal rate mismatches. In addition, advisory-mode analysis is performed based on clinical data, which indicates that the method can determine safe and reasonable meal boluses in real clinical settings. The results verify the effectiveness and robustness of the proposed method and indicate the feasibility of achieving improved postprandial glucose regulation through a data-driven optimal control method. © 2021, CC BY.

关键词： Gaussian distribution

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