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第三十四届中国控制会议

作者： Wang Mao-zhang BAI Yong-qiang Department of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781467374439

With the battlefield environment becomes more complicated nowadays, it's difficult to achieve high precision target tracking only using single platform of target tracking system. Especially for maneuvering targets, the application of interactive multiple model(IMM) algorithm based on a variety model becomes necessary and feasible. At the same time, the best linear unbiased estimate(BLUE) filter is much more appropriate and useful than Kalman filter when it comes to deal with nonlinear system. Most of the time, we are blind to the correlation degree of our target during the merge process of tracking. We can track our target with multi-platform with introduction of Cross-Correlation(CI) fusion algorithm which is based on distributed data and proves its effectiveness by simulation.

关键词： Multi-platform,Maneuvering target tracking,BLUE filter,AIMM,CI fusion

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MEMS-based Human Activity Recognition Using Smartphone 35

MEMS-based Human Activity Recognition Using Smartphone

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第35届中国控制会议

作者： TIAN Ya CHEN Wenjie Department of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781509009107

Data mining is one hot orientation in today’s research *** activity recognition is meaningful in our daily living and is a significant aspect in data *** previously research is almost based on tri-axial *** paper presents a novel method to collect data from both accelerometer and gyroscope using *** daily activities including Walking,Running,Upstairs,Downstairs,Standing,Sitting and Cycling,a total of seven categories are *** raw data from MEMS are recorded by smartphone according to different daily *** improve the accuracy of classification for daily activities,this paper combines time-series features with wavelet coefficients to extract *** recognize these activities,the support vector machine is used to finish this ***,we compare the accuracy with other machine learning methods,such as k-nearest neighbor algorithm and neural network or decision *** result indicates that our method can achieve nearly 96%classification accuracy for the seven kinds of daily activities.

关键词： classification activity recognition wavelet transform support vector machine feature extraction

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A Novel Fast Haze Removal Technique for Single Image Using Image Pyramid 34

A Novel Fast Haze Removal Technique for Single Image Using I...

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第三十四届中国控制会议

作者： ZHAO Dong BAI Yong-qiang Department of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781467374439

Fast single image dehazing has been a challenging problem in many fields, such as computer vision and real-time applications. Recently, many dehazing algorithms have been proposed based on the dark channel prior(DCP). However, these algorithms aim to improve the refinement of the raw transmission map, while ignore the computational complexity of DCP ***, this paper proposes a new technique for fast single image haze removal, which achieves a good tradeoff between the dehazing performance and the computational complexity. We first decompose the observed haze image into a coarse image and a detail image using Gaussian-Laplacian pyramid. Then, the coarse image is dehazed by Dark Channel Prior and Guided filter(GDCP). For the size of the coarse image is 1/4 of the original image, the computational complexity is reduced ***, the recomposed image is blurred, since the detail image is still haze. So, we employ an unsharp filter to sharpen the blurred recomposed image. Experimental results show that the proposed dehazing technique effectively removes haze, and significantly reduces the computational complexity by 69.59% on average, compared with traditional GDCP algorithm.

关键词： single image dehazing,image restoration,dark channel prior,image pyramid,unsharp masking

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Experimental Model Identification of Liquid-Circular Angular Accelerometer using Subspace Method 35

Experimental Model Identification of Liquid-Circular Angular...

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第35届中国控制会议

作者： WANG Meiling LI Xiang CHENG Siyuan FU Mengyin XIAO Meifeng Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Nanjing University of Science and Technology

ISBN: (纸本)9781509009107

In this paper, the model of a novel liquid-circular angular accelerometer is studied. Due to the absence of theoretical model of liquid-circular angular accelerometer, a subspace identification method(SIM) based on Akaike Information Criterion(AIC) is chosen for model identification of angular accelerometer. The proposed identification method is tested on a liquid-circular angular accelerometer prototype. The experimental results indicate that SIM could obtain a more accurate model than least square method, with a degree of fitting above 90%. In addition, SIM possesses good repeatability and stability. The experimental model identified by SIM in this paper can be applied in engineering practice.

关键词： system Identification Angular Accelerometer Subspace Method

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The SDRE based Second Order Integral Sliding Mode control for Attitude of Reentry Vehicle

The SDRE based Second Order Integral Sliding Mode Control fo...

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第三十二届中国控制会议

作者： GENG Jie SHENG Yongzhi LIU Xiangdong WANG Liang School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781479900305

In this paper,a state dependent Riccati equation-based second order integral sliding mode control(SSOISMC) algorithrn is proposed for the reentry vehicle with a strong conpling,nonlinearity and ***,the state dependent Riccati equation(SDRE) controller is developed to approach the attitude controller for the nonlinear reentry vehicle without uncertainties. Then the second order integral sliding mode control theory is proposed to combine sliding mode with SDRE,and it is applied to reentry vehicle with parameter variations or external *** achievement of the second order sliding phase is *** the proposed control law,the optimal performance index is achieved and the uncertainties are rejected,furthermore, the chattering is ***,simulation is made through the assumption that aerodynamic parameters and atmospheric density are *** validity and robustness of the proposed strategies are verified by simulation results.

关键词： Flight vehicle control state dependent Riccati equation(SDRE) Second order integral sliding mode

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Analysis and Testing of Delay in HLA-based Distributed Simulation system

Analysis and Testing of Delay in HLA-based Distributed Simul...

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第25届中国控制与决策会议

作者： Chen Chen Lu Chao School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

ISBN: (纸本)9781467355339

Time is a significant concept in distributed *** the increment of simulation system scale, working efficiency of simulation system will go down very sharply due to the restrictions of time management tactics and time sequence coupling. Therefore, it is necessary to study the characteristics of delay in simulation system to improve its working effeciency. Aiming at HLA-based distributed simulation system, causes of simulation delay is analysed and principles of delay testing is explained. A method which employs synchronization point setting and an effective wall clock time querying approach is put forward. Statistics and analysis of message interaction delay is executed on the software platform of pRTI 1.3 version. The measurement of delay lays an important data foundation for time management algorithms.

关键词： Distributed Simulation system, Delay Testing, High Level Architecture, Synchronization Point.

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Learning to Win in Evolutionary Two-person Boolean Game with Fixed Strategy Updating Rule

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IFAC-PapersOnLine 2015年第28期48卷 520-525页

作者： WANG, Dong Hongbin, M.A. Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Canada

This paper introduces an algorithm to learn the strategy updating rule for a two- person Boolean game using the records of the history strategies and game results. The two-person game in this paper is introduced as a zero-sum game along with a Boolean strategy set, and the strategies are governed by fixed Boolean functions whose arguments are the history strategies and game results with additive binary noise, which can be modeled as a stochastic Boolean dynamic system. However, for this easy-to-play game, there is no effective convenient methods to win more often. To achieve this goal, a learning algorithm based on Boolean regression and maximum-likelihood estimation is put forward to learn the strategy updating rule and the noise property using the records of the history strategies and game results. In addition, extensive simulations via actual examples have illustrated the effectiveness of the proposed learning algorithm. © 2015

关键词： Learning algorithms Identification (control systems) Maximum likelihood estimation Parameter estimation Stochastic systems Boolean dynamics Boolean games Extensive simulations Fixed strategy Learning Noise properties Strategy updating Two person game

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Generalization of integral inequalities and (c_1,c_1) stability of neutral differential equations with time-varying delays

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Journal of systems Engineering and Electronics 2017年第2期28卷 347-360页

作者： Shuli Guo Lina Han Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Mathematics Institute Oxford University Department of Cardiovascular Internal Medicine Nanlou Branch of Chinese PLA General Hospital

A uniform stability analysis is developed for a type of neutral delays differential equations which depend on more general nonlinear integral inequalities. Many original investigations and results are obtained. Firstly, generations of two integral nonlinear inequalities are presented, which are very effective in dealing with the complicated integro-differential inequalities whose variable exponents are greater than zero. Compared with existed integral inequalities, those proposed here can be applied to more complicated differential equations, such as time-varying delay neutral differential equations. Secondly, the notions of (ω, Ω) uniform stable and (ω, Ω) uniform asymptotically stable, especially (c1, c1) uniform stable and (c1, c1) uniform asymptotically stable, are presented. Sufficient conditions on about (c1, c1) uniform stable and (c1, c1) uniform asymptotically stable of time-varying delay neutral differential equations are established by the proposed integral inequalities. Finally, a complex numerical example is presented to illustrate the main results effectively. The above work allows to provide further applications on the proposed stability analysis and control system design for different nonlinear systems. © 2017 Beijing Institute of Aerospace Information.

关键词： control system stability Differential equations Nonlinear equations Time delay Time varying control systems

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Fault Tolerant control for a Class of Nonlinear system based on Active Disturbance Rejection control and RBF Neural Networks 36

Fault Tolerant Control for a Class of Nonlinear System based...

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第36届中国控制会议

作者： Lushan Zhou Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781538629185

In this paper,a fault tolerant control method based on active disturbance rejection control(ADRC) and radial basis function neural network(RBFNN) is proposed for a class of multi-input-multi-output nonlinear system with actuator faults,components faults and sensor *** proposed method does not rely on the plant *** regarding the faults and plant uncertainties as the disturbance,through the observation of extended state observer and the compensation of feedback control signal,this method achieves the fault tolerance control of the plant with component fault and actuator *** sensor faults,in this work,radial basis function neural network is applied to estimate the real output of the *** this output estimation is utilized by active disturbance rejection control to achieve the fault tolerance of ***,the effectiveness of the proposed method is validated by the simulation results of the three-tank system.

关键词： Fault tolerant control active disturbance rejection control radial basis function neural network

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Dehazing Network Based on U-Net Structure and Residual Block 41

Dehazing Network Based on U-Net Structure and Residual Block

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第41届中国控制会议

作者： Wenbo Zhang Haoze Li Han Sun Yongqiang Bai School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of deep learning technology,the dehazing method based on convolutional neural network has also developed ***,it still faces some problems such as incomplete dehazing and difficulty in detail *** at the problems,we propose a dehazing network based on U-Net structure and residual *** the down sampling process,we introduce the residual block of attention mechanism,which effectively improves the feature extraction and expression ability of the *** the middle part of the network,the smooth dilation convolution residual block is used to expand the receptive field of the network and improve the restoration effect of small *** the same time,we introduce a feature fusion mechanism based on attention mechanism,which can reduce the loss of information and weight the down-sampling features into intermediate *** the process of up sampling,the method of adding elements instead of feature stitching is used to reduce the number of parameters and realize the function of jump ***,dense convolution residual blocks are added to the jump connection between input and output to further improve the *** experimental results show that the PSNR of this method can reach 32.893,which is better than the existing methods.

关键词： Image Dehazing Residual Network Attention mechanism

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