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2016 IEEE International Conference on automation Science and Engineering, CASE 2016

作者： Fan, Qiu Yi, Yang Hao, Li Mengyin, Fu Shunting, Wang School of Automation State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509024094

A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status for each pixel of images. First, we extract and match sparse image features to estimate ego-motion between two consecutive stereo images, the result of feature points grouping is used to segment moving object in U-disparity map. Second, a Fully Convolutional Neural Network is employed for semantic segmentation. Moreover, semantic cues are utilized to remove pixels have no potential to be moved in motion mask. Finally, we use a fully connected CRF to integrate motion into semantic segmentation. To validate the effectiveness of the proposed algorithm, we present experimental results with KITTI stereo images that contain moving objects. © 2016 IEEE.

关键词： Semantics

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Robust sampled-data control for Itô stochastic Markovian jump systems with state delay

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International Journal of Robust and Nonlinear control 2018年第15期28卷

作者： Guoliang Chen Jian Sun Jianwei Xia School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China School of Mathematics Science Liaocheng University Liaocheng China

In this paper, the problem of robust sampled-data control for Itô stochastic Markovian jump systems (Itô SMJSs) with state delay is investigated. Using parameters-dependent Lyapunov functionals and some stochastic equations, we give stochastic sufficient stability criteria for polytopic uncertain Itô SMJSs. As a corollary, stochastic sufficient stability criteria are given for nominal Itô SMJSs. For this two cases of Itô SMJSs, based on the obtained stochastic stability criteria, their time-independent sampled-data controllers are designed, respectively. Then, for designing a time-dependent sampled-data controller for Itô SMJSs, a parameters-dependent time-scheduled Lyapunov functional is developed. New stochastic sufficient stability criteria are obtained for polytopic uncertain Itô SMJSs and nominal Itô SMJSs. Furthermore, their time-dependent sampled-data controllers are designed, respectively. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： Itô stochastic Markovian jump systems parameters-dependent time-scheduled Lyapunov functional robust sampled-data control stability

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End-to-End Driving Activities and Secondary Tasks Recognition Using Deep Convolutional Neural Network and Transfer Learning

End-to-End Driving Activities and Secondary Tasks Recognitio...

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2018 IEEE intelligent Vehicles Symposium, IV 2018

作者： Xing, Yang Tang, Jianlin Liu, Hong Lv, Chen Cao, Dongpu Velenis, Efstathios Wang, Fei-Yue Advanced Vehicle Engineering Centre Cranfield University BedfordMK43 0AL United Kingdom Vehicle Intelligence Pioneers Ltd Qingdao China Jiangsu XCMG Construction Machinery Research Institute Ltd. No. 26 Tuolanshan Road Economic Development Zone Xuzhou Jiangsu221004 China School of Mechanical and Mechatronics Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538644522

Drivers' decision and their corresponding behaviors are important aspects that can affect the driving safety, and it is necessary to understand the driver behaviors in real-time. In this study, an end-to-end driving-related tasks recognition system is proposed. Specifically, seven common driving activities are identified, which are normal driving, right mirror checking, rear mirror checking, left mirror checking, using in-vehicle video device, texting, and answering mobile phone. Among these, the first four activities are regarded as normal driving tasks, while the rest three are divided into distraction group. The images are collected using a consumer range camera, namely, Kinect. In total, five drivers are involved in the naturalistic data collection. Before training the identification model, the raw images are first segmented using a Gaussian mixture model (GMM) to extract the driver region from the background. Then, a pre-trained deep convolutional neural network (CNN) model is trained to classify the behaviors, which directly takes the processed RGB images as the input and outputs the identified label. In this work, the AIexNet is selected as the pre-trained CNN model. Then, to reduce the training cost, the transfer learning mechanism is applied to the CNN model. An average of 79\% detection accuracy is achieved for the seven driving tasks. The proposed integration model can be used as a low-cost driver distraction and dangerous tasks recognition modeL. © 2018 IEEE.

关键词： Neural network models

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Event-based H∞filtering for networked singular systems 35

Event-based H∞filtering for networked singular systems

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35th Chinese control Conference, CCC 2016

作者： Song, Weixu Sun, Jian Chen, Jie School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789881563910

In this paper, the problem of H∞filtering for networked singular systems with an event-triggered scheme is investigated. With a modified event generator, remote sensor evaluates the periodically sampled data and only transmits those violate a certain event-triggered condition, and thus reduces the communication burden. The filtering error system is converted into a time-delay system model which can be studied using the Lyapunov stability theory. Based on this model, sufficient criteria are derived to guarantee the filtering error system regular, impulse free and stable with a prescribed H∞performance. The design method of the filter is also considered. Finally, an example is exploited to illustrate the effectiveness of the proposed method. © 2016 TCCT.

关键词： Event-triggered communication H∞ filtering Network-induced delay Singular system

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Performance monitoring and parameter optimization of fuzzy controller in combustion process of coke Oven

Performance monitoring and parameter optimization of fuzzy c...

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Asian control Conference

作者： Qi Lei Di Zhu Xu-Zhi Lai Min Wu School of Information Science and Engineering University of Central South University Changsha China School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781509015740;9781509015733

The controller parameters can not perform well in the combustion process of coke oven, caused by the fluctuating calories of fuel gas, the changes of coking time and many other exogenous disturbances. In this paper, an optimal method based on performance monitoring by using the trend extraction method, is raised to adjust the parameters of the controllers in the combustion process of coke oven. Firstly, because of the mixture of different kinds of error, the trend extraction method is used to separate trend component from original signal. Secondly, the monitoring indices are designed to examine whether the monitored controller parameters are suitable in the current situation. Then, the performance monitoring result is utilized to choose the decision vector of optimization and determine whether optimization is needed. Finally, simulation results demonstrate that our method performs well in the optimization for combustion process of coke oven in spite of massive changes in the calories of fuel gas.

关键词： Monitoring Combustion Market research Optimization Process control Ovens Heating systems

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SPID control for synchronization of complex PIDE networks with time delays 43

SPID control for synchronization of complex PIDE networks wi...

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43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

作者： Yang, Chengdong Zhang, Ancai Zhang, Xinghui Liu, Zhaodong Pang, Guochen Qiu, Jianlong Wen, Yumei Shanshui, Shandong Cao, Jinde School of Automation Southeast University Nanjing210096 China School of Information Science and Technology Linyi University Linyi276005 China Key Laboratory of Complex Systems and Intelligent Computing Universities of Shandong Linyi University Linyi276005 China School of Automation and Electrical Engineering Linyi University Linyi276005 China Cement Group Jinan250307 China School of Mathematics Southeast University Nanjing210096 China

ISBN: (纸本)9781538611272

This paper deals with the problem of complex spatio-temporal networks, which is modeled by coupled partial integro-differential equations (PIDEs). A spatial proportional-integral-derivative (SPID) state-feedback controller is studied. With Laypunov direct method, a sufficient condition on synchronization of the complex PIDE network is investigated in terms of linear matrix inequality (LMIs). Finally, a numerical example shows the effectiveness of the proposed results. © 2017 IEEE.

关键词： Linear matrix inequalities

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Evaluation of Lower-Limb Rehabilitation Based on Muscle Fatigue

Evaluation of Lower-Limb Rehabilitation Based on Muscle Fati...

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IEEE International Symposium on Industrial Electronics

作者： Juan Zhao Jinhua She Dianhong Wang Edwardo F. Fukushima Min Wu Hiroshi Hashimoto School of Engineering Tokyo University of Technology Hachioji Tokyo Japan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Master Program of Innovation for Design & Engineering Advanced Institute of Industrial Technology Tokyo Japan

The purpose of this study was to investigate the features of muscle fatigue extracted from surface electromyography (sEMG) signals of lower limbs, and then to present an evaluation method of lower-limb rehabilitation to provide physical basis for the training effect of rehabilitation. Four healthy young university students were invited to perform a pedaling exercise for 40 days. The sEMG signals of four lower-limb muscles are recorded and processed using a Butterworth filter and a Daubechies 10 wavelet. Then, the change of the ratios of the spectrums of Types I and II muscle fibers to the total number of the spectrum along the exercise are examined. The time of the first intersection of the ratios for Types I and II for each muscle is used as a performance index. The increase in the time at the beginning and the end of the training period indicates the improvement of motor function, and thus it verifies the effectiveness of the rehabilitation.

关键词： SEMG Muscle fatigue Rehabilitation evaluation Unequal length segmentation

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Smoothed State Estimation via Efficient Solution of Linear Equations

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IFAC-PapersOnLine 2017年第1期50卷 1613-1618页

作者： Geng L.-H. Ninness B. Wills A. Schön T. L.-H. Geng is with the Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin 300222 China Faculty of Engineering and Built Environment The University of Newcastle Callaghan NSW 2308 Australia Department of Information Technology Division of Systems and Control Uppsala University Uppsala 751 05 Sweden

This paper addresses the problem of computing fixed interval smoothed state estimates of a linear time varying Gaussian stochastic system. There already exist many algorithms that perform this computation, but all of them impose certain restrictions on system matrices in order for them to be applicable. This paper develops a new forwards–backwards pass algorithm that is applicable under the mildest restrictions possible - namely that the smoothed state distribtions exists in forms that can be characterised by means and covariances, for which this paper also develops a new necessary and sufficient condition. © 2017

关键词： Bayesian methods Estimation Filtering filtering smoothing Stochastic system identification

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Two-layer Fuzzy Kernel Regression for Human Emotional Intention Understanding

Two-layer Fuzzy Kernel Regression for Human Emotional Intent...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Luefeng Chen Mengtian Zhou Min Wu Jinhua She Kaoru Hirota School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China School of Engineering Tokyo University of Technology Tokyo Japan Tokyo Institute of Technology Beijing Institute of Technology Yokohama Japan

A two-layer fuzzy kernel regression (TLFKR) model is proposed for understanding human emotional intention in human-robot interaction, where TLFKR model consists of two layers, including fuzzy c-means (FCM) with kernel ridge regression (Kernel 1) for information analysis layer, fuzzy support vector regressions (FSVR) (Kernel 2) for intention understanding layer. TLFKR model represents the weight impact for each emotional information and aims to improve smooth human-robot interaction by endowing robot with human emotional intention understanding capability. Experimental Results show that the proposal obtains an intention understanding accuracy of 65.67%/68.33%/80.67% with the clusters number c=2/3/6 (according to different genders/ages/nationalities), which are 7.34%/7.18%/8.67% and 18.67%/21.33%/33.67% higher than that of TLFSVR and SVR, respectively. Additionally, preliminary application experiments are performed in the developing emotional social robot system, where two mobile robots and volunteers experience a scenario of "drinking at a bar", and social robots are able to express basic emotions and understand human order intention.

关键词： Kernel Robots Training Support vector machines Proposals Information analysis Bars

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Function projective synchronization of nonlinear complex spatio-temporal networks with time-varying delays via boundary control

Function projective synchronization of nonlinear complex spa...

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2017 Chinese automation Congress, CAC 2017

作者： Yang, Chengdong Zhang, Ancai Li, Zhenxing Chen, Xiangyong Chen, Xiao Qiu, Jianlong Wen, Yumei School of Automation Southeast University Nanjing210096 China School of Information Science and Technology Linyi University Linyi276005 China Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi276005 China School of Automation and Electrical Engineering Linyi University Linyi276005 China Shandong Shanshui Cement Group Jinan250307 China School of Mathematics Southeast University Nanjing210096 China

ISBN: (纸本)9781538635247

This paper studies boundary control for function projective synchronization of a complex sptio-temporal network with time-varying delays and nonlinear terms satisfying the Lipschitz condition. A boundary controller based on distributed measures is studied for function projective synchronization. Using Lyapunov's direct method, the problem of existence of the controller is formulated as the feasibility problem of linear matrix inequalities (LMIs). Finally, an example shows the effectiveness of the proposed method. © 2017 IEEE.

关键词： Linear matrix inequalities

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