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Chinese control Conference (CCC)

作者： Wei Yin Weiqi Qin Xiaowei Jiang Xiangyong Chen Ming Chi School of Automation China University of Geosciences Wuhan P. R. China Affiliated Hospital of Shandong Medical College Linyi P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Wuhan P. R. China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

Neimark-Sacker bifurcation of a delay differential equation modeling two-enterprise interaction mechanism is investigated. For the demands of computer simulation applications, the discrete-time two-enterprise interaction model is proposed by using the forward Euler scheme. By discussing the characteristic equation of linearized part, the local stability criterion of the positive fixed point is presented. Time lag is selected as the bifurcation parameter. Then it is demonstrated that variation of time lag may result in Neimark-Sacker bifurcation. Furthermore, derivations for the directions and stability of Neimark-Sacker bifurcation are also given. Finally, we simulate the main results.

关键词： Bifurcation Stability analysis Predator prey systems Delays Delay effects Biological system modeling Electronic mail

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Trajectory Planning and Tracking control for Positioning of Planar Three-link Underactuated Manipulator

Trajectory Planning and Tracking Control for Positioning of ...

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Asian control Conference

作者： Zixin Huang Xuzhi Lai Pan Zhang Min Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (纸本)9781728102634

This paper is concerned with the position control problem of the planar active-passive-active (APA) underactuated manipulator, whose dynamic constraint is mainly caused by the second-order nonholonomic constraint. First, the dynamic model of the system is established and the target angles of the three links are calculated by using differential evolution algorithm. Then, we present a trajectory planning and tracking control strategy to realize the control objective, which is to stabilize the end-point from any initial position to the target position. We plan two stage trajectories, the first of which is planned for the active links. When the the active links track the first stage trajectories, they can reach to their target angles. The second one is planned for the first active link based on the differential evolution algorithm. When the first active link tracks the second stage trajectory, it will back to its target angle eventually. Meantime, the passive link will be controlled to its target angle. Then, we design sliding mode variable structure controllers to make active links track the planned trajectories, which can make the all links reach to the their target angles. Finally, numerical simulation results illuminate the effectiveness of the proposed strategy.

关键词： Trajectory Manipulators Target tracking Position control Planning Heuristic algorithms Optimization

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Load curve modeling based on behavior analysis of distributed power customers 4

Load curve modeling based on behavior analysis of distribute...

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2019 4th Asia Conference on Power and Electrical Engineering, ACPEE 2019

作者： Han, Xinyang Zhang, Yu Jiao, Yuqiao Zhang, Yue Qu, Yanjing Ding, Min State Grid Energy Research Institute Beijing102200 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China State Grid Shanghai Municipal Electric Power Company Shanghai200122 China

As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based on the behavior analysis. Firstly, customers' active behavior is represented by the quantity of active customer households. Based on the analysis of customer behaviors, a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo method. Then, with the inputs as the quantity of active customer households and time of photovoltaic power generation, an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical appliances. By combing the average usage time of electrical appliances, load characteristics are analyzed based on usage state of electrical appliance of distributed power customers. Finally, the simulation results verify the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Fuzzy logic

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K-Means Clustering-based Kernel Canonical Correlation Analysis for Multimodal Emotion Recognition ⁎

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IFAC-PapersOnLine 2020年第2期53卷 10250-10254页

作者： Luefeng Chen Kuanlin Wang Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6R 2G7 Canada Tokyo Institute of Technology Yokohama 226-8502 Japan

Emotion is an important part of human interaction. Emotional recognition can greatly promote human-centered interaction techniques. On this basis, multimodal feature fusion can effectively improve the emotion recognition rate. However, in the multimodal feature fusion at the feature level, most of the methods do not consider the intrinsic relationship between different modes. Only the fusion of analysis and transformation of the feature matrices of different modes does not make better use of modal differences to improve the recognition rate. This problem led us to propose feature fusion method based on K-Means clustering and kernel canonical correlation analysis (KCCA). Clustering makes the classification of features not classified by mode, but by the degree of influence on emotional labels, thus positively affecting the results of KCCA. The experimental results obtained on the Savee database show that the proposed K-Means based KCCA improves overall classification performance and produces higher recognition rate than that of the state of art methods, such as the Informed Segmentation and Labeling Approach.

关键词： Emotion Recognition K-Means Clustering Kernel Canonical Correlation Analysis Feature Fusion

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Robust disturbance rejection for a fractional-order system based on equivalent-input-disturbance approach

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Science China(Information Sciences) 2018年第7期61卷 200-211页

作者： Ruijuan LIU Jinhua SHE Min WU Fenfang ZHU Zhuoyun NIE School of Applied Mathematics Xiamen University of Technology School of Automation China University of Geosciences School of Engineering Tokyo University of Technology Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Information Science and Engineering National Huaqiao University

This paper presents a disturbance rejection method that is based on the equivalent-inputdisturbance approach for uncertain fractional-order(FO) systems. An FO observer is used to reconstruct the plant states and estimate the disturbances. A disturbance estimator is incorporated in the construction of the FO control system to actively compensate for the entire disturbance. A robust stability condition for the control system and the parameters of the controller are derived using an indirect Lyapunov *** presented method effectively rejects disturbances and handles modeling uncertainties without requiring prior knowledge of the disturbance. Comparison simulations on both numerical and practical examples demonstrate the effectiveness of the proposed method.

关键词： fractional-order system disturbance rejection equivalent-input-disturbance uncertain system Lyapunov method state observer stability

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Multi-scale Protein complex Discovery based on Graph Wavelet

Multi-scale Protein Complex Discovery based on Graph Wavelet

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第三十九届中国控制会议

作者： Wang Yue Ran Xu Peng Xiao-yu Yi Ming Zhu Yuan School of Science Huazhong Agricultural University School of Mathematics and Statistics Huazhong University of Science and Technology School of Mechanical Engineering Wuhan Institute of Shipbuilding Technology School of Mathematics and Physics China University of Geosciences School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Identifying protein complexes from protein interaction networks is an important task in the post-genomic era. With the development of high-throughput sequencing technology, the acquisition of protein interaction network data is becoming more and more convenient. The current protein complex recognition algorithms cannot well balance the hierarchical and overlapping properties of protein networks. In order to overcome these limitations, this paper proposes a Graph Wavelet based Protein complex Discovery algorithm, GW-PCD. The method exploits the clustering analysis of protein interaction networks to find a modular mechanism by characterizing the distance between graph wavelet coefficients of protein pairs. Comparative experimental results show that GW-PCD enhances the performance of identifying protein complexes, which will provide valuable clues for further exploration of the unknown functions of proteins at the multiscale perspective.

关键词： Graph wavelet Protein-protein interaction network Multiresolution analysis Protein complex Community discovery

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Optimization of Overhauser magnetometer based on multi-channel frequency measurement algorithm 37

Optimization of Overhauser magnetometer based on multi-chann...

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37th Chinese control Conference, CCC 2018

作者： Wang, Guanzhong Dong, Haobin Ge, Jian Luo, Vang Liu, Huan Yuan, Zhiwen Zhu, Jun Zhang, Haiyang School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems Hubei Wuhan430074 China Science and Technology on Near-Surface Detection Laboratory Wuxi Jiangsu214035 China

ISBN: (纸本)9789881563941

Overhauser magnetometer is a weak magnetic measuring instrument based on the dynamic nuclear polarization of free radical species. It has the characteristics of high precision, high sensitivity, low power consumption and continuous measurement. It is widely used in geophysics, aeromagnetic surveying, satellite Magnetic measuring, military and various engineering fields. Aiming at the problem that the measurement accuracy of the magnetometer prototype is low and the measurement effect is poor when the angle between the probe axis and the geomagnetic field is 0°, several optimization methods are proposed and the magnetometer is optimized by adding the frequency measurement channel on the basis of the prototype. Based on the standard deviation of GSM-19 measurement data, comparing the experimental data that use the multi -channel frequency measurement algorithm, the standard deviation of prototype data decreases from 0.397 to 0.203 when the angle between probe axial and geomagnetic field is 45°, the standard deviation of the prototype data decreases from 0.631 to 0.371 when the angle between probe axial and geomagnetic field is 0°, which provides an important reference for the follow-up optimization of the magnetometer. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Magnetometers

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Convex Relaxation with Log-Determinant Divergence-L1 Regularization for 3D Shape Reconstruction

Convex Relaxation with Log-Determinant Divergence-L1 Regular...

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第三十八届中国控制会议

作者： Wei Cao Luefeng Chen Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta

Investigated is the problem of estimating the 3 D shape of an object defined by a set of 3 D landmarks with their 2 D correspondences in a single image. To solve this problem, we use a dictionary of the basic shape with LDD-L1 regularization,which is the construction of the shape space model. Based on the proposed convex optimization method, 3 D human pose reconstruction by shape space model and 3 D variable shape model was carried out on the mocap database. To improve accuracy and reduce the number of iterations, we use PSO algorithm to optimize initial value of the key parameter. The experimental results show that the improved algorithm exhibits less iterations but higher accuracy, which can be much helpful in practical applications.

关键词： LDD-L1 regularization 3D reconstruction PSO

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Dissipativity Analysis for Markovian Jump Neural Networks with Time-Varying Delay via An Extended Relaxed Integral Inequality 37

Dissipativity Analysis for Markovian Jump Neural Networks wi...

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37th Chinese control Conference, CCC 2018

作者： Wen-Juan, Lin Yong, He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences School of Automation Wuhan430074 China

ISBN: (纸本)9789881563941

This paper investigates the problem of the strictly (\mathcal{Q}, \mathcal{S}, \mathcal{R})-\gamma -dissipativity analysis for Markovian jump neural networks with a time-varying delay. By employing an appropriate Lyapunov-Krasovskii functional and using the extended relaxed integral inequality to estimate its derivative, a delay-dependent and mode-dependent condition that guarantee the considered Markovian jump neural networks strictly (\mathcal{Q}, \mathcal{S}, \mathcal{R})-\gamma -dissipative is derived. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Lyapunov functions

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Visual enhancement by spectral optimization of light sources 8

Visual enhancement by spectral optimization of light sources

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8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Jin, Xing Cheng, Xianghui Yang, Xiang Zhang, Jinjin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

The visualization of an object image is directly affected by the spectral power distribution of the illuminated light source. In addition, the quality and the clarity of an object image can be evaluated by the color entropy value. Therefore, in order to obtain higher color entropy value of the target object image, a visual enhancement method is proposed by optimizing the spectral of the illumination. The optimal light source spectrum of the target image is obtained by the maximum color entropy, and the spectral reflectance of the object is obtained by the reconstruction method of the RBF neural network. The images under the optimal illumination source were compared with those of other commercial white light sources (6774K, 5000K, 2700K, 3000K,). The result shows that the optimized light source has a better visual effect and the lines in the image are more apparent. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Light sources

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