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

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Hyperspectral Remote Sensing Image Classification Based on Convolutional Neural Network

Hyperspectral Remote Sensing Image Classification Based on C...

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第37届中国控制会议

作者： Xiangyang Dai Wei Xue School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Remote sensing hyperspectral imaging can obtain rich spectral information of terrestrial objects, which allows the indistinguishable matter in the traditional wideband remote sensing to be distinguished in hyperspectral remote *** image has the characteristics of "combining image with spectrum". Making full use of spectral information and spatial information in hyperspectral image is the premise of obtaining accurate classification results. At present, most of hyperspectral data feature extraction algorithms mainly utilize local spatial information in the same channel and spectral information in the same spatial location of different channels. However, these methods require a large amount of prior knowledge, it is difficult to fully grasp the hyperspectral data of all spatial and spectral information, and the model generalization ability is poor. With the development of deep learning, convolutional neural network shows superior performance in all kinds of visual tasks, especially in the two-dimensional image classification, and could get a high classification accuracy. In this paper, an image classification method based on three-dimensional convolution neural network is proposed based on the structural properties of hyperspectral data. In the proposed method, first the stereo image blocks of hyperspectral data are intercepted, then multi-layer convolution and pooling operation of extracted blocks by convolutional neural network are implemented to obtain the essential information of hyperspectral data, finally the classification of hyperspectral data is completed. The experimental results show the proposed method could provide better feature expression and classification accuracy for hyperspectral image.

关键词： Convolutional Neural Network Hyperspectral Image Deep Learning Classification

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H∞ control for singular systems with time-varying delay based on augmented Lyapunov-Krasovskii functional

H∞ control for singular systems with time-varying delay bas...

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第37届中国控制会议

作者： ZHI Ya-Li HE Yong School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper concers the H∞ control for singular systems with time-varying ***,an augmented LyapunovKrasovskii functional（ALKF） is constructed by adding some integral terms which are dependent on the singular matrix to the quadratic ***,to handle the derivative of the ALKF,a modified relaxed integral inequality is *** a result,a sufficient condition with a state feedback controller is derived to ensure the closed-loop system to be regular,impulse free and asymptotically stable with H∞ ***,a numerical example is given to verify the effectiveness and the superiority of the proposed method.

关键词： H∞ control Singular systems with time-varying delay Augmented Lyapunov-Krasovskii functional Relaxed integral inequality State feedback

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control strategy based on differential evolution algorithm for planar second-order nonholonomic manipulator

Control strategy based on differential evolution algorithm f...

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第37届中国控制会议

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

This paper presents a two-stage position control strategy based on the differential evolution(DE) algorithm for a planar second-order nonholonomic manipulator,which has one passive joint and this passive joint is not the first joint(planar APA manipulator for short,where m≥1,n≥0).An offline DE algorithm is used to calculate all link target angles corresponding to the target *** to these target angles,a Lyapunov function is constructed to design the controllers A for the control stage 1,which are used to control all active links to their target *** to the constraint equation of the planar APA manipulator,an oscillatory trajectory is planned for the first active link based on the online DE *** the first active link tracks the oscillatory trajectory,it will back to its target angle ***,the passive link will be jointly controlled to its target angle ***,the other Lyapunov function is constructed to design the controllers B for the control stage 2,which are used to control the first active link tracks the target trajectory and control the remaining m+n-1 active links maintain in their target *** results of a planar AAPA manipulator demonstrate the effectiveness of the proposed control strategy.

关键词： Planar second-order nonholonomic manipulator Differential evolution algorithm Lyapunov function Online intelligent trajectory planning

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Observer-Based Tracking control for Suppressing Stick-Slip Vibration of Drillstring System

Observer-Based Tracking Control for Suppressing Stick-Slip V...

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第37届中国控制会议

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

A control method is proposed to suppress stick-slip vibration of drillstring system based on tracking control with zero steady-state error and state observer in this paper. A multiple degree-of-freedom(DOF) model of drillstring dynamic is presented first, which considers high-order modal of stick-slip vibration. Then, state observer is constructed to estimate the states of drillstring system, whose states are usually difficult to measure in the top of drillstring system. Finally, combing state feedback control and internal model principle, a tracking control with zero steady-state error is proposed to ensure the speed of rotary table and bit are consistent. The proposal only need top measurement, can eliminate multiple torsional modes, and has a strong robustness. Simulations show the effective of the proposal.

关键词： Stick-slip vibration Multi-DOF model Tracking control State observer

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GMI Effect Automatic Test System Based on Network Analyzer

GMI Effect Automatic Test System Based on Network Analyzer

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第37届中国控制会议

作者： Zhi Zhao Hengchang Rao Fang JIn Jinchao Wang Lei Zhu Junlei Song Kaifeng Dong Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

The measuring instrument selects the network analyzer, combines the direct current source and the Helmholtz coil to form the GMI effect test system. PC program written in Lab VIEW, network analyzer and DC current source is controlled by the host computer. The host computer can process and plot the impedance data collected by the network analyzer, and save the data and images locally. The test system by measuring the commercial Vitrovac6025 strip material, found that the material all showed a strong GMI effect at different frequencies. By comparing the measured data of the network analyzer and the impedance analyzer measured in the same frequency band, we found that the two are consistent, which verifies the accuracy and reliability of the test system.

关键词： Giant magneto-impedance（GMI） LabVIEW Network Analyzer

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Synchronization control of star network based on quorum sensing mechanism 8

Synchronization control of star network based on quorum sens...

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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： Liu, Feng Mateus, Felix Mei, Qicheng Wu, Xianyong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China College of Electrical Engineering and New Energy China Three Gorges University Yichang443002 China

In this paper, we combined the quorum sensing mechanism of bacteria with the Repressilator oscillator to describe the rhythmicity of bacteria. It is found that the transmission of signal molecules between cells produces a star network, and the dynamical equation of the star network is given. Then, the error projection synchronization of star networks is defined and analyzed. A Lyapunov function is constructed to prove that the error system will be close to zero within a certain time under the control of the controller. Finally, a four node star network is used for simulation. The results show that the controller can achieve the desired results. © 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： Synchronization

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Peak and valley time-of-use price optimization strategy with distributed power supply 8

Peak and valley time-of-use price optimization strategy with...

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作者： Hu, Bo Zhang, Yu Han, Xin-Yang Jiao, Yu-Qiao Ding, Min 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 Energy Research Institute Co. LTD. Beijing102200 China

This paper proposes a peak-to-valley time-based electricity price optimization method based on NSGA-II with distributed power supply. First, the curve-fitting method is used to obtain the comprehensive electricity price response curve of users in the whole society. Secondly, based on the use of time-sharing electricity price, the peak-to-valley time-sharing optimization model is established. Then, based on the NSGA-II optimization method, the optimal model is solved, and the optimal electricity price is obtained at different time periods to change the peak-to-valley load and the valley load. Finally, the simulation results verify the effectiveness of the proposed method. © 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： Genetic algorithms

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Multi-robot Path Planning and Trajectory Smoothing

Multi-robot Path Planning and Trajectory Smoothing

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IEEE International Conference on automation Science and Engineering (CASE)

作者： Hub Ali Gang Xiong Huaiyu Wu Bin Hu Zhen Shen Hongxing Bai School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences China Hubei Jointown Technology Co. Ltd Artificial Intelligence Research Institute Wuhan China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

In this paper we consider a problem in task execution for multi-robot trajectory planning with collision avoidance in a shared working environment. Consider two or more robots generating trajectories towards their respective goal positions. The collision may occur if their trajectory coordinates are intersecting at a point or follow the same path segment simultaneously. The central planner is introduced to control robot motion in the collision state and to reduce the complexity of the multi-robot path planning system. The global path for every robot is generated by the $\mathrm{A}^{*}$ algorithm in a grid-based environment. The path has presented a sequence of optimal grid numbers and later transformed into Cartesian coordinates for smooth trajectory generation. The central planner takes an optimal grid sequence for every robot to analyze the collision state according to its cost value. It regenerates the trajectories to minimize the complexity cost value and replaces the previous trajectory based on minimum cost value. In the collision state, the central planner allows one robot at a time to pass along the conflict path segment and hold others in queue at a safety offset distance until the previous robot passes safely. The algorithm has been applied to robots working in a shared environment in complex maps and the simulations is performed with MATLAB to calculate the efficiency of this approach for handling collision states in a multi-robot path planning system.

关键词： Robot kinematics Trajectory Collision avoidance Task analysis Resource management

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A hybrid differential evolution and estimation of distribution algorithm for the multi-point dynamic aggregation problem 18

A hybrid differential evolution and estimation of distributi...

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2018 Genetic and Evolutionary Computation Conference, GECCO 2018

作者： Hao, Rong Zhang, Jia Xin, Bin Chen, Chen Dou, Lihua School of Automation Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781450357647

The multi-point dynamic aggregation (MPDA) is a typical task planning problem. In order to solve the MPDA problem efficiently, a hybrid differential evolution (DE) and estimation of distribution algorithm (EDA) called DE-EDA is proposed in this paper, which combines the merits of DE and EDA. The DE-EDA has been applied to multiple MPDA instances of different scales, and compared with EDA and two versions of DE in convergence speed and solution quality separately. The results demonstrate the DE-EDA can solve the MPDA problem effectively. © 2018 Copyright held by the owner/author(s).

关键词： Evolutionary algorithms

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Research and Implementation of Target Tracking Algorithm Based on Convolution Neural Network

Research and Implementation of Target Tracking Algorithm Bas...

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Chinese control Conference

作者： Li Jun Zhang Chen Wang Xing Jin School of Automation China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Video target tracking is an important research topic in computer vision, and has been widely used in video surveillance, robot, human-computer interaction and so on. The emergence of large data age and the emergence of in-depth learning methods provide a new opportunity for the study of video target tracking. This paper first analyzes the research problems of video target tracking at present, analyzes the characteristics and trends of video target tracking in the new period, introduces the emerging recursive neural network frame structure, combined with Kalman filterAnd the experimental results show that the accuracy and robustness of the target tracking based on the convolution neural network algorithm are all good.

关键词： Target tracking Convolutional neural networks Feature extraction Convolution Training Kalman filters Image color analysis

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