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Chinese control Conference

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

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： Sparse matrices Image reconstruction Cyber-physical systems Real-time systems Genetic algorithms Training Matching pursuit algorithms

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EEG emotion recognition based on ensemble learning 8

EEG emotion recognition based on ensemble learning

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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： Ding, Xue-Wen Liu, Zhen-Tao Feng, Zhi-Yong Xie, Qiao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Automotive Engineering Wuhan University of Technology Wuhan430070 China

EEG emotion recognition based on ensemble learning is proposed, in which three classification models including k-Nearest Neighbor, Decision Tree and Logistic Regression are integrated. In feature extraction, four kinds of features including Mean, Skewness, Sample Entropy and Lempel-Ziv complexity (LZC) are extracted from eight channels’ EEG signals, and Kernel Principal Component Analysis (KPCA) is employed to reduce the dimension of the feature set. The proposal is tested on the DEAP dataset in which the EEG emotional states are accessed in Arousal-Valence emotion space. The result shows that the average emotion recognition accuracies of 77.73% in Arousal dimension and 75.34% in Valence dimension are obtained, which demonstrates its feasibility. © 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： Emotion Recognition

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Study on Maximum Power Point Tracking Based on Parabolic Approximation Method for Photovoltaic Power Generation System

Study on Maximum Power Point Tracking Based on Parabolic App...

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Chinese control Conference

作者： Rengui Li Zhili Tan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Maximum power point tracking controller is essential to obtain the maximum power from a solar array in the photovoltaic systems as the PV power module varies with the temperature and solar irradiation. In the DC/DC circuit, the maximum power point tracking algorithm based on parabolic approximation method is used. On the basis of analyzing the principle of various tracking methods, the key technology of parabola approximation can be found to find the exact maximum power point.

关键词： Mathematical model Photovoltaic cells Photovoltaic systems Maximum power point trackers Approximation methods

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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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Chinese control Conference

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

This paper investigates the stability of neural networks with a time-varying delay. Based 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 candidate. Then an extended reciprocally convex matrix inequality and an auxiliary function-based inequality are utilized to estimate the derivative of the LKF. As a result, an improved stability criterion is established. Finally, the advantage of proposed method is demonstrated by a numerical example.

关键词： Linear matrix inequalities Stability criteria Symmetric matrices Biological neural networks Numerical stability Neurons

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Research of Vehicle Detection System Based on Geomagnetic Disturbance Detection

Research of Vehicle Detection System Based on Geomagnetic Di...

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Chinese control Conference

作者： Junlei Song Yi Wei Chaoyu Xu Qi Liu Kaifeng Dong Wenqin Mo Fang Jin Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

To overcome the shortcomings of high cost, maintenance difficulties in traditional vehicle detect ion methods. This paper presents a novel vehicle detection method used in the military field. The anisotropic magneto resistive (AMR) sensor is used to detect geomagnetic disturbances in real time, meanwhile, the ultrasonic distance-measuring sensor is adopted to determine the position of the target vehicle and avoid miscalculation. To reduce detection delay, a scheme containing dual AMR sensors and wireless communication module for information transferring is used on this detection system. In order to verify the effectiveness of the detection system, a mathematical model of vehicle detection based on geomagnetic disturbance detection is established. According to the test results, the influence cased by different content of ferromagnetic material and detection distance is analyzed. Finally, the related experiments on the effects of different ferromagnetic contents on the geomagnetic disturbance at different detection distances are carried out. The experimental results verify the correctness of the mathematical model proposed in this paper, and further verify the effectiveness of the detection system. This detection system possesses many prominent advantages such as low-cost, long-life, good performance of real time, convenience.

关键词： Magnetic fields Acoustics Vehicle detection Coatings Real-time systems Bridge circuits

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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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Chinese control Conference (CCC)

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

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： Vibrations Mathematical model Observers Torque Computational modeling State feedback

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Research on Handwritten Alphabet Recognition System Based on Extreme Learning Machine

Research on Handwritten Alphabet Recognition System Based on...

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Chinese control Conference

作者： Junlei Song Qi Liu Shengnan Tian Yi Wei Fang Jin Wenqin Mo Kaifeng Dong Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Aiming at the problems of slow recognition, low efficiency and degree of automation in handwritten letter recognition system at present, a handwritten letter recognition system based on extreme learning machine is designed in this paper. The system is implemented by mixed programming with MATLAB and visual studio, it can reads, normalize, binarize and extract the handwritten letter images. The real-time interactive recognition of handwritten letters can be realized on the basis of training the simple pictures by using the identification model of the extreme learning machine algorithm. The experimental results show that the handwriting recognition system based on extreme learning machine designed in this paper can recognize 98.82% of handwritten letters and greatly reduce learning and testing time. Compared with BP neural network and other recognition algorithms, its training times have been reduced by hundreds or even thousands of times. At the same time, there is no manual intervention in the entire learning and testing process, which improves the automation of handwriting recognition.

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Non-fragile finite-time dissipative piecewise control for time-varying system with time-varying delay

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IET control Theory & Applications 2019年第3期13卷 321-332页

作者： Menghua Chen Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 People's Republic of China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 People's Republic of China

This study is concerned with the problem of non-fragile finite-time dissipative (FTD) control for time-varying system with delay. The delay is time varying and belongs to a given interval. Finite-time bounded (FTB) and FTD concepts are introduced to time-varying system with delay. First, new FTB conditions are derived for time-varying system with delay by using a piecewise Lyapunov functional combined with reciprocally convex approach. Second, FTD conditions are obtained to guarantee that the time-varying system with delay is not only FTB but also satisfies a dissipative performance index. Moreover, based on the FTD conditions, the non-fragile piecewise feedback controllers are designed in terms of linear matrix inequalities (LMIs). In addition, an LMI-based iterative algorithm is given to obtain the piecewise feedback non-fragile controller gains. Finally, numerical examples demonstrate the effectiveness of the proposed method.

关键词： linear matrix inequalities delays feedback iterative methods control system synthesis Lyapunov methods time-varying systems performance index finite-time dissipative control time-varying system nonfragile piecewise feedback controllers piecewise feedback nonfragile controller gains time-varying delay nonfragile finite-time dissipative piecewise control finite-time bounded piecewise Lyapunov functional reciprocally convex approach dissipative performance index linear matrix inequalities LMI-based iterative algorithm

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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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Social Manufacturing for High-end Apparel Customization

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 489-500页

作者： Xiuqin Shang Fei-Yue Wang Gang Xiong Timo R. Nyberg Yong Yuan Sheng Liu Chao Guo Sen Bao State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Science at Aalto University Aalto FI-00076 Finland Qingdao Academy of Intelligent Industries Qingdao 266109 China IEEE

Social manufacturing(SM), a novel distributed,collaborative and intelligent manufacturing mode, is proposed and developed for high-end apparel customization. The main components of SM cloud are designed, and its research topics are summarized. Then, SM's key technologies are studied. 3D technologies for apparel customization, like 3D modeling, 3D fitting mirror and 3D customization, are developed to improve the customization precision and user experience. Information based collaborative management is realized to share, communicate,and handle the information efficiently among all groups and individuals of SM cloud. Suppliers' evaluation mechanism is designed to support the optimal decisions making. Next, SM cloud is constructed in five layers for high-end apparel *** using SM cloud based crowd-sourcing, social resources can be allocated rationally and utilized efficiently, consumer can customize the product in any processes like innovation, design,making, marketing and service, and traditional apparel enterprise can be upgraded into SM mode for keeping it competitive in the future customization markets.

关键词： Index Terms-Big data collaborative management social man-ufacturing cloud 3D apparel customization.

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