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An Initiative Service Method with Regard to Degree of Sleepiness for Drinking Service Robot

An Initiative Service Method with Regard to Degree of Sleepi...

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第37届中国控制会议

作者： Zhen-Tao Liu Si-Han Li Wei-Hua Cao Man Hao Lin-Bo Xian School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

To ensure the efficiency of people’s work while working long hours,an initiative service method with regard to degree of sleepiness for drinking service robot is *** can recognize the degree of sleepiness and provide initiative service to increase the efficiency of people’s *** of sleepiness is defined as three levels by observer rating,which is supposed to be associated with human actions,environmental factors,and individual *** addition,a model of degree of sleepiness based on Finite State Machines（FSM） is *** relationship between human demands and degree of sleepiness is established through demand analysis model by which the initiative service with regard to degree of sleepiness for drinking service robot is *** on real initiative drinking service are performed in a multimodal emotional communication based on human-robot interaction（MEC-HRI） system,from which the experimental results show that the time of initiative service is 8 minutes earlier than that without initiative *** prospect,the proposal could be applied to other kinds of services such as health care,safety driving assistance,and other safety work assistance.

关键词： Service Robot Sleepiness Initiative Service Finite State Machines Human-Robot Interaction

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A Safety Assessment Method Based on Online Sequential Extreme Learning Machine（OS-ELM） in Deep Drilling Process

A Safety Assessment Method Based on Online Sequential Extrem...

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第37届中国控制会议

作者： Yupeng Li Weihua Cao Chao Gan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Accurate and timely assessment of drilling system is key for achieving safety and efficiency in deep drilling. In this paper, an online assessment model is proposed by applying online sequential extreme learning machine（OS-ELM）. The model has been tested through the actual drilling data for drilling system safety assessment and accidents early warning. By analyzing the mechanism characteristics of accidents, well logging parameters are chosen as the input and accident types are chosen as the output. Owing to the OS-ELM is capable of updating network parameters based on new arriving data without retraining historical data, the model can be updated online for specific formation accidents information to make it more adaptable to a particular environment. The numerical test results show that, comparing with other widely used assessment techniques like support vector machines（SVM） and back propagation（BP）, the proposed model has a higher accuracy and shorter recognition time.

关键词： safety assessment extreme learning machine deep drilling online learning

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Quick and Effective Position control for Planar n-link Underactuated Manipulators Based on Optimization Algorithm

Quick and Effective Position Control for Planar n-link Under...

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第37届中国控制会议

作者： Pan Zhang Xuzhi Lai Yawu Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper,a simple one-stage control strategy is developed based on optimization algorithm to quickly realize the position control of a planar n-link（n ≥ 3） underactuated manipulator with a passive first *** continuous control of a planar three-link underactuated manipulator with a passive first joint can be realized,and so can the planar n-link（n ≥ 3） ***,one problem that the number of the variables needing to be optimized will increase with the increase of the number of the links will ***,considering the planar three-link manipulator can be controlled to reach to any target position,we employ the differential evolution（DE） algorithm to optimize the angles of only two active links and the design parameters of the corresponding ***,the angles and the corresponding design parameters of other n — 3 active links are kept being *** this way,all link angles can simultaneously converge to their target *** a planar four-link underactuated manipulator with a passive first joint as an example,the simulation results verify the effectiveness and rapidity of the proposed strategy.

关键词： Planar underactuated manipulators First-order nonholonomic system Differential Evolution algorithm Position control One-stage control

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Research on Digital Hearing Aid Speech Enhancement Algorithm

Research on Digital Hearing Aid Speech Enhancement Algorithm

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第37届中国控制会议

作者： Junlei Song Yuan Meng Junming Cao Jin Fang Kaifeng Dong Fang Jin Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The microphone array speech enhancement algorithm（MASEA）, the minimum mean square error algorithm for short-time logarithmic spectrum estimation based on voice activity detection（VAD-LSA-MMSE）, and the Wiener filtering algorithm based on voice activity detection（VAD-Wiener） are currently the three most commonly used speech enhancement algorithms. Among them, the MASEA algorithm has some disadvantages such as poor noise reduction effect. VAD-LSA-MMSE algorithm has some disadvantages of relying on high SNR and introducing music noise, thereby reducing the intelligibility. The VAD-Wiener algorithm has some disadvantages such as higher SNR requirements. Aiming at the shortcomings of these three speech enhancement algorithms, based on the VAD algorithm and the MASEA algorithm, this paper proposed a new speech enhancement algorithm by combining the characteristics of Wiener filtering algorithm and LSA-MMSE algorithm. The new speech enhancement algorithm is a VAD-based microphone array speech enhancement algorithm（VAD-MASEA）. VAD-MASEA is better than the other three algorithms in noise reduction, speech enhancement and voice intelligibility, and has the characteristics of adapting to a lower SNR environment. This paper used MATLAB to carry out experimental research, including the new algorithm and the three existing algorithms were simulated and compared the signal waveforms of the four algorithms. Experimental results show that the proposed VAD-MASEA algorithm overcomes the high SNR requirement and can be used in low SNR environments and obtain highly intelligible enhanced signals.

关键词： Voice enhancement Wiener filtering VAD-LSA-MMSE

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Image Jacobian Matrix Estimation based on Fuzzy Adaptive Robust Kalman Filter

Image Jacobian Matrix Estimation based on Fuzzy Adaptive Rob...

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第37届中国控制会议

作者： Zhenzhu Liu Xinmei Wang Zhenjiang Feng Zhongzhao Xie Shuai Ke School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Aiming at the problem of image Jacobian matrix estimation, this paper proposes a method to get the motion state estimation of the object feature point at the current time by using the combination of robust Kalman filter and fuzzy adaptive method from the image feature space, and the estimation of the image Jacobian matrix can be obtained. Firstly, an adaptive robust decorrelation Kalman filter algorithm with colored measurement noise is proposed by reconstructing process equation and measurement equation and combining the mathematical characteristics of the standard Kalman filter noise. Secondly, by monitoring if the ratio between theoretical residual and actual residual is near 1, the fuzzy inference system constantly adjust the weighted measurement noise covariance and recursively correct the measurement noise covariance of the adaptive Kalman filter, and thus be able to estimate the position and velocity of the object feature point at the current time in the image space more accurately, then the estimation of image Jacobian matrix can be achieved accurately under unknown dynamic environment. The feasibility and superiority of the proposed method can be verified by the simulation and experimental results.

关键词： Image Jacobian Matrix Estimation Robust Kalman Filter Fuzzy Adaptive

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Piecewise control Strategy for a Planar Four-link Underactuated Manipulator with Friction

Piecewise Control Strategy for a Planar Four-link Underactua...

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第37届中国控制会议

作者： Haoqiang Chen Xuzhi Lai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A piecewise control strategy is proposed to realize the position-posture control of a planar four-link Active-PassiveActive-Active（APAA） underactuated manipulator（UM）. Specially, the particle swarm optimization（PSO） algorithm is used to obtain the target angle of all links based on the constraints of control objects of the system. The overall control process of the system is divided into two stages: Firstly, we design a fuzzy-PI controller for the first link to realize the control target of the passive link, and the error between the current angle and the desired angle of the passive link is converged to zero by adjusting the velocity of the first link. Secondly, the position mode of the servo controller is adopted to control the active links move to their target angles, respectively. Finally, the experimental results of the real system verify the effectiveness of the proposed control strategy.

关键词： underactuated manipulator planar four-link fuzzy-PI control position-posture control

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Low Resource-Consuming Cyber-physical System Sampling Method using Bernoulli Circulant Matrix

Low Resource-Consuming Cyber-physical System Sampling Method...

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第37届中国控制会议

作者： Xing Jin Xiang Yang Dian Zhang Jingjing Zhang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Cyber-physical System(CPS) have a high requirement on real-time property, and it is difficult to improve the sampling efficiency base on traditional sampling theory. In this paper, the compression sensing(CS) theory is applied to the sampling compression process of CPS system. The CS theory was used to the sampling compression method of CPS system. The Bernoulli circulant matrix, which is easy to be realized and stored, and its construction algorithm were designed to simplify the realization of CS theory in CPS. It is concluded that for random data set, the compression ratio increases from 14.06 % to 42.18 % and the reconstruction error decreases from 27.65 to 1.28 with increasing repetition times. Note that the sampling time are around tens of microseconds and the reconstruction time are around several milliseconds, which indicates a high real-time performance for CPS. In addition, for image data set, the compression ratios are about 42.90 % which indicates a high compression ratio and huge storage resources saving. More importantly, the sampling time and reconstruction time are only several microseconds and several seconds respectively, which indicates a high real-time performance for CPS.

关键词： Cyber-physical System Compressive sensing Sampling Bernoulli circulant matrix

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Fog Removal Method of Slope Monitoring Image Based On Vision Detection

Fog Removal Method of Slope Monitoring Image Based On Vision...

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第37届中国控制会议

作者： Xianzhen Sang Yue Yang Xianhe Hou School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the slope monitoring based on image detection,the main work is to process the acquired slope *** landslide occurred mostly in the rain,fog and other complex weather *** we can process effectively and fast fog images according to the fog horizon slope vision *** would be helpful for subsequent image segmentation,object extraction,positioning,and improving the accuracy and efficiency of detection of slope *** on the visual technology in slope monitoring,we compared two kinds of defogging algorithm of slope *** is a kind of image enhancement method of non-physical model,mainly including:equalization algorithm and homomorphic filtering algorithm,McCann Retinex algorithm and multi-scale Retinex algorithm and a global *** other is the image restoration method based on physical model,including the dark channel prior bilateral filtering algorithm,and combined with the theory of dark channel prior to fog *** experimental results show that the histogram equalization method has the advantage of fast imaging quality in slope visual image processing,and is more suitable for slope monitoring.

关键词： Slope monitoring Image processing Dark Channel Prior Bilateral filtering

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Fast Automatic Localization of Epileptic Seizure Onset Zones Using complex Morlet Wavelet Transform-based Singular Value Decomposition

Fast Automatic Localization of Epileptic Seizure Onset Zones...

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第37届中国控制会议

作者： Zelin Fang Xiongbo Wan Ting Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A new method for localization of epileptic seizure onset zones（SOZs） is proposed, which uses the Shannon-entropybased complex Morlet wavelet transform to extract a satisfactory time-frequency feature of high-frequency oscillations（HFOs）.The singular value decomposition and the K-medoids clustering algorithm are employed to extract effective features from the redundant matrix of wavelet coefficients. A distinctive feature is to use the singular values to detect HFOs with the consideration that the singular values of HFOs are generally significantly higher than those of normal case. Based on the half-maximum method,the localization of SOZs are achieved by using the characteristics of HFOs. Comparisons show that our method provides a higher sensitivity and specificity than two existing methods do.

关键词： Epilepsy Seizure onset zone（SOZ） High-frequency oscillation（HFO） Singular value decomposition K-mediods clustering

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Convolutional Neural Networks for Facial Expression Recognition with Few Training Samples

Convolutional Neural Networks for Facial Expression Recognit...

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第37届中国控制会议

作者： Zhongzhao Xie Yongbo Li Xinmei Wang Wendi Cai Jing Rao Zhenzhu Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Facial expression recognition(FER) plays an important role in human-machine interaction. An assistant robot having a close interaction with human being should be able to recognize human facial expression. FER is a non-trivial problem because each individual has his own way to reveal his emotion and the facial expressions of two different persons may not be totally identical. Hence,facial expression recognition is still a challenging problem in computer vision. In this work, we propose a simple solution for facial expression recognition that uses a combination of Convolutional Neural Network and specific image pre-processing *** experiments employed to evaluate our technique were carried out using two largely used public databases(CK+, JAFFE).A study of the impact of each image pre-processing operation in the accuracy rate is presented. The proposed method: achieves competitive results when compared with other facial expression recognition methods-97.85% of accuracy in the CK+ database-it is fast to train,and it allows for real time facial expression recognition with standard computers.

关键词： Facial Expression Recognition Human-machine Interaction Convolutional Neural Network

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