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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsWuhan"

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

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

引用

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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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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Lithologic identification for imbalanced logging data based on AdaC2-SVM in drilling process

Lithologic identification for imbalanced logging data based ...

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第37届中国控制会议

作者： Xi Chen Weihua Cao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

To identify some special formation lithology with imbalanced logging data, a framework of Multi-layer lithology identification method is proposed. In this framewoke, some special lithology is divided into one class in the first layer, and each lithology is separated in the second layer. A novel algorithm of Ada Cost2-support vector machine（AdaC2-SVM） is put forward using logging data of actual well located in Karamay for training, and the support vector machine-recursive feature elimination（SVM-RFE） is adopted to select attribute, and logging data from another well nearby is used for testing. Experiment result shows the G-mean and accuracy of our method is up to 95.3% and 94.4%, which has better performance than random forest（RF）algorithm, particle swarm optimization-support vector machine（PSO-SVM） algorithm and improved PSO-SVM（IPSO-SVM）algorithm. In the future, the proposed method have a good prospect and give a valuable result for geology research.

关键词： Lithologic identification Ada C2 Support vector machine Imbalanced data Drilling process

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A novel augmented Lyapunov functional for the stability analysis of delayed neural networks

A novel augmented Lyapunov functional for the stability anal...

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第37届中国控制会议

作者： Fei Long Leichao Pang Chuan-Ke Zhang Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the stability of neural networks with a time-varying *** on the good effectiveness of the augmented Lyapunov-Krasovskii functional(LKF),some useful integral vectors are summarized and used to construct single integral terms with augmented quadratic integrand so as to develop a novel augmented LKF *** an extended reciprocally convex matrix inequality and an auxiliary function-based inequality are utilized to estimate the derivative of the *** a result,an improved stability criterion is ***,the advantage of proposed method is demonstrated by a numerical example.

关键词： Augmented Lyapunov-Krasovskii functional stability neural networks time-varying delay

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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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Dense Depth Estimation with Absolute Scale

Dense Depth Estimation with Absolute Scale

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第37届中国控制会议

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

Considering the difficulties in estimating depth from single image, in this paper, we propose a method to obtain the absolute scale depth map by combining the convolution neural network and depth filter. We compute relative transformation between consecutive frames by direct tracking features, which are extracted from RGB images and whose depthes are predicted by deep network, and then optimize relative motion by searching for a better feature alignment in epipolar line, and finally update every pixel depth of the reference frame by depth filter. We evaluate the proposed method on the open dataset comparison against the state of the art in depth estimation to evaluate our method.

关键词： Depth Estimation Pose Estimation Depth Filter

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RBF Neural Network Based-PID control for Weight on Bit During Drilling Operation

RBF Neural Network Based-PID Control for Weight on Bit Durin...

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第37届中国控制会议

作者： Sike Ma Min Wu Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Deep drilling is a costly project and efficiency is of paramount importance. The weight on bit is one of the main operating parameters that influences the drilling efficiency and it was controlled by manual before. But after people saw the giant potential of an auto-drilling system in increasing the drilling efficiency, more and more studies on the feed back control of weight on bit have emerged. This paper mainly studied weight on bit dynamic under the variational formation based on a lumped parameter model and a self-tuning PID controller for weight on bit control. The parameters of the PID controller are tuned by using gradient descent method and RBF neural network identification.

关键词： Weight on bit auto-drilling system RBF neural network PID

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Measurement System of Ferromagnetic Film Magnetic Properties Based on Magneto-optical Kerr Effect

Measurement System of Ferromagnetic Film Magnetic Properties...

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第37届中国控制会议

作者： Xueying Fu Wenqin Mo Shun Yuan Liming Xu Junlei Song Kaifeng Dong Fang Jin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A new measuring system for magnetic properties of the ferromagnetic thin film has developed based on magneto-optical Kerr effect（MOKE）. This system can realize both polar MOKE and longitudinal MOKE measurements through the optimization of optical path and electromagnet’s poles. The signal processing software on Lab VIEW has been also designed to acquire the Kerr signal and plot the hysteresis loop. The MOKE measurements have been performed to investigate the magnetic properties of ferromagnetic films such as Co Fe Si B, permalloy and Ni Fe/Ag/Ni Fe multilayer. The experimental results proved that the system has a high angular accuracy of 0.0008°.

关键词： Magneto-optical Kerr effect Kerr rotation angle Ferromagnetic film LabVIEW

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On Self-adjusting Fuzzy controller Based on Feedforward Compensation Decoupling

On Self-adjusting Fuzzy Controller Based on Feedforward Comp...

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第37届中国控制会议

作者： Zhenjiang Feng Yongbo Li Zhenzhu Liu Xinmei Wang Kaiyuan Fu Juanjuan Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Aiming at the multivariable coupling characteristics and the complexity of its control inside the concrete curing box,this paper firstly analyzes the coupling relationship between temperature and humidity in the curing box, and uses the decoupling strategy of the feedforward compensation algorithm. The simulation results show that the decoupling effect is good. Then, based on the principle of the self-adjusting function on the transient performance of the system, a self-adjusting factor fuzzy controller is designed, which combines the decoupling method and the self-adjusting function to improve the control effect of the coupling variable of temperature and humidity inside the concrete curing box.

关键词： Temperature and Humidity Coupling Feedforward Compensation Algorithm Self-adjusting Function

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Inverse Kinematic control Method of Redundant Manipulators with Joint Limits Constraints

Inverse Kinematic Control Method of Redundant Manipulators w...

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第37届中国控制会议

作者： Ting Fei Xin Chen Jiafeng Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

For the control problem of redundant manipulators with joint limits constraints, a novel method combining the simplified clamping weighted least-norm method and the typical gradient projection method is proposed in this paper. The method solves the problem that the manipulability of the redundant manipulator is poor caused by the clamping weighted least-norm method and makes the joint velocity change more smoothly. The proposed novel method is implemented on a kinematic redundant manipulator with four degree-of-freedom(DOF) which belongs to the dulcimer music-playing robot. The numerical simulation results show that the joint positions are well-bounded within the joint limits and the manipulator has a good performance for tracking a given trajectory.

关键词： Redundant manipulators Joint limits Inverse kinematic control

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