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

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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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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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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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R-H Measurement System Based on Anomalous Hall Effect Devices

R-H Measurement System Based on Anomalous Hall Effect Device...

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第37届中国控制会议

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

With the application of magnetic thin films becoming more and more widespread,people pay more and more attention to the performance *** order to obtain a magnetic film with a specific performance,it is very important to judge the quality of the magnetic film and measure the magnetic properties of the ***,with the increase of the film preparation process,the thickness of the prepared film is getting thinner and the magnetic moment signal contained therein is also *** brings a certain degree of difficulty to the traditional measurement *** example,the VSM system that obtains the hysteresis loop by measuring the magnetic moment signal has become somewhat inadequate for the measurement of ultra-thin *** order to solve this issue,a new method based on anomalous Hall effect is introduced in this *** test system of this system adopts the four-probe measuring method,a constant current is applied across the surface of the film sample,and the abnormal Hall voltage is measured at the other two *** R-H curve of the sample can be obtained through *** compared to VSM measurement,this method is simpler and stable,more accurate,which can greatly reduce the anomalous Hall-effect device R-H characteristic measurement cost.

关键词： anomalous Hall effect R-H measurement measurement system

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Electroencephalogram Emotion Recognition Based on A Stacking Classification Model

Electroencephalogram Emotion Recognition Based on A Stacking...

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第37届中国控制会议

作者： Qiao Xie Zhen-Tao Liu Xue-Wen Ding School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

To improve the accuracy of Electroencephalogram(EEG) emotion recognition,a stacking emotion classification model is proposed,in which different classification models such as XGBoost,LightGBM and Random Forest are integrated to learn the *** addition,the Renyi entropy of 32 channels' EEG signals are extracted as the feature and Linear discriminant analysis(LDA) is employed to reduce the dimension of the feature *** proposal is tested on the DEAP dataset,and the EEG emotional states are accessed in Arousal-Valence emotion space,in which HA/LA and HV/LV are classified,*** result shows that the average recognition accuracies of 77.19%for HA/LA and 79.06%for HV/LV are obtained,which demonstrates that the proposal is feasible in EEG emotion recognition.

关键词： Emotion recognition Electroencephalogram Stacking model Renyi entropy

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