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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： Li, Danyun Wu, Xiaofang Yin, Xiang Yang, Dongming Ding, Min School of Automation China University of Geoscience Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

This study employed equivalent-input-disturbance (EID) approach to devise a control system for the rotor-side converter (RSC) of doubly fed induction generator (DFIG). It effectively suppresses the magnitude and/or frequency disturbances of the output voltage so that the power quality can meet the electric standard. The stator flux of DFIG is controlled through adjusting the exciting current to realize the indirect control of the output voltage. The inner loop of the control system consists of a state observer and a disturbance compensator. The state observer estimates the disturbances caused by the various changes including loads, wind speed and system parameters, which then be compensated by the disturbance compensator incorporating the EID into the control law. The outer loop consists of an internal model and a state-feedback controller that enables the output voltage of RSC to track the instantaneous reference stator flux. The small-gain theorem ensures the stability of the system. The effectiveness of the proposed control system has been validated by the simulation 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： Disturbance rejection

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H∞control for singular systems with time-varying delay based on augmented lyapunov-krasovskii functional 37

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

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37th Chinese control Conference, CCC 2018

作者： Ya-Li, Zhi Yong, He School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789881563941

This paper concers the H∞ control for singular systems with time-varying delay. Firstly, an augmented Lyapunov-Krasovskii functional (ALKF) is constructed by adding some integral terms which are dependent on the singular matrix to the quadratic term. Secondly, to handle the derivative of the ALKF, a modified relaxed integral inequality is introduced. As 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∞ performance. Finally, a numerical example is given to verify the effectiveness and the superiority of the proposed method. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Closed loop systems

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Finite-Time H∞ state estimation for discrete time-delayed stochastic switched genetic regulatory networks with uncertain sojourn probabilities 37

Finite-Time H∞ state estimation for discrete time-delayed s...

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37th Chinese control Conference, CCC 2018

作者： Chuanyu, Ren Xiongbo, Wan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789881563941

This paper investigates the problem of finite-time H∞ state estimation for discrete-time stochastic switched genetic regulatory networks (GRNs) with time-varying delays and exogenous disturbances. A new discrete time-delayed stochastic switched GRN model with uncertain sojourn probabilities is devised, which is more general than the switched GRNs model with completely known sojourn probabilities. The sufficient conditions which guarantee the stochastic finite-time boundedness of the estimation error dynamics with a prescribed H∞ disturbance attenuation level are derived. By solving several matrix inequalities, the state estimator parameters can be obtained. A numerical example is given to illustrate the effectiveness of our results. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： State estimation

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Tattoo recognition based on triplet GAN 37

Tattoo recognition based on triplet GAN

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37th Chinese control Conference, CCC 2018

作者： Jiawang, Cao Yuan, Zhu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789881563941

An important feature of the deep learning algorithm is that the hidden layer of the neural network is more dependent on more computing resources and a larger amount of data. In this paper, we use TripletGAN method to identify human body images with tattoos using fewer data sample labels. The model achieved better results(0.9462) than the only Triplet(0.8352) and only GAN(0.9178) in the MNIST dataset, it also achieved higher recognition accuracy (77-82%) under the premise of saving the amount of data, compared with the traditional machine learning algorithm(54-84%). We provide a new idea for tattoo image recognition applications in embedded computing units. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Image recognition

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Electroencephalogram Emotion Recognition Based on A Stacking Classification Model 37

Electroencephalogram Emotion Recognition Based on A Stacking...

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37th Chinese control Conference, CCC 2018

作者： Xie, Oiao Liu, Zhen-Tao Ding, Xue-Wen School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789881563941

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 features. In 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 set. The 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, respectively. The 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. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Emotion Recognition

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MatchMesh: Knowledge-based 3D Point Cloud Meshing Using Divide-and-conquer Deformation

MatchMesh: Knowledge-based 3D Point Cloud Meshing Using Divi...

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IEEE International Conference on Networking, Sensing and control

作者： Ying Tang Shengtao Sun Ben Wu Rowan University Glassboro USA State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Rowan University Glassboro NJ USA

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

The reconstruction of surface mesh from point cloud is compute-intensive but also very important step in the remanufacturing and personalization industries. With more 3D scanners providing lower cost and higher resolution, further detailed point clouds can be gathered without so much effort as before. In manufacturing, there are databases which contain the origin 3D design models of the products. How to utilize the design model data for swift production of related products remains a problem for remanufacturing and customization. In order to develop a knowledge-based way of handling this problem, editing or deforming an existing mesh to match the target is an effective way of easing the workload. In this paper, we introduce a divide-and -conquer process which segments the depth scan data and then find the best match in the database as its source of deformation. The segmentation is performed on 3D point level using global features extracted by 3D CNN. After that we find best match to our knowledge with the same features to acquire a fast meshing of the target object by deforming the existing parts from the match. The deformation of parts are being done sequentially. For further performance improvement, we present a deformation training method employing transfer learning on segment editing process.

关键词： Training Surface reconstruction Three-dimensional displays Databases Knowledge based systems Feature extraction Strain

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Sequence impedance modeling of droop-controlled inverter

Sequence impedance modeling of droop-controlled inverter

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8th Renewable Power Generation Conference (RPG 2019)

作者： You Hu Jiajun Wang Bin Liu Zhen Li Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The grid-connected three-phase inverter is an indispensable part of the microgrid. The droop control is widely used in parallel inverters for high reliability and flexibility. The output impedance of droop controlled inverters plays an vital role in its stability. However, the sequence impedance model of grid-connected inverter is currently based on the grid side converter with a single current loop control exdluding the low-frequency dynamics similar in doubly fed induction generators. Both the droop control and voltage loop control greatly affect the stability of inverter, specifically in the low frequency response. This paper proposes a sequence impedance model of inverter, which considers the droop control and voltage and current dual closed-loop control using the harmonic linearization method in the frequency domain. The accuracy of the model is verified through comparing the measurement impedance value in simulation with the impedance value calculated in the sequence impedance model. The influence of control method on system impedance is verified by showing the difference between the single loop controlled inverter and droop control inverter.

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Preface——Special Issue on New Directions in Nonlinear and Distributed control

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Journal of systems Science & complexity 2018年第1期31卷 1-3页

作者： LIU Tengfei XIN Bin JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China Tandon School of Engineering New York University Brooklyn NY 11201 USA

Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha... 详细信息

关键词：控制问题非线性分布式工程应用程序电子物理自然系统生产线相互作用

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Optimal Economic Operation of Microgrid Considering Lifetime Characteristics for Hybrid Energy Storage System

Optimal Economic Operation of Microgrid Considering Lifetime...

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Asian control Conference

作者： Min Ding Xiaomin Wu Danyun Li Weihua Cao Dianhong Wang Luefeng Chen Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

ISBN: (纸本)9781728102634

The PV-wind-storage microgrid plays an important role in solving power supply problems. Energy storage system is an important element to be considered when the optimal economic operation of microgrid is carried out due to the high cost and discount. To achieve reliable and economic operations of a PV-wind-storage microgrid, the lifetime characteristics of energy storage system also need to be fully investigated. In this paper, low pass filter is used to determine the power of super capacitor and battery, than established battery life quantitative model according to the equivalent cycle life curve. Considering the lifetime characteristics of energy storage system, a optimization to minimize power generation cost and to maximize the useful life of hybrid energy storage system has been achieved via the particle swarm optimization (PSO). The simulation results show the proposed method can optimize the system operations and has good optimization results.

关键词： Batteries Discharges (electric) Microgrids Capacitors Economics Optimization

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Mapping grapevine leafroll disease epidemics from UAV images

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Computers and Electronics in Agriculture 2025年 237卷

作者： Yixue Liu Jinya Su Dizhu Liu Yuyang Song Yulin Fang Baofeng Su Peng Yang College of Mechanical and Electronic Engineering Northwest A&F University 712100 Yangling China Key Laboratory of Agricultural Internet of Things Ministry of Agriculture and Rural Affairs 712100 Yangling China Shaanxi Key Laboratory of Agriculture Information Perception and Intelligent Service 712100 Yangling China Key Laboratory of Agricultural Remote Sensing (AGRIRS) Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing 100081 China School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University 210096 Nanjing China College of Enology Northwest A&F University 712100 Yangling China

Grapevine Leafroll Disease (GLD) poses a significant economic burden on the wine industry in major wine-producing regions. Conventional methods of phenotyping GLD are inefficient and delay vineyard management decisions. The emergence of affordable Unmanned Aerial Vehicles (UAV) provides unprecedented opportunities for GLD high-throughput phenotyping. However, detecting GLD-infected grapevines at the canopy level using UAV images is still a challenge due to the subtle differences between GLD canopy features and background. In this paper, we propose a GLD Detector (GLDD) for mapping GLD epidemics from UAV images. A new attention mechanism module, namely, Channel Attention with Transformers (CAT) is proposed to alleviate the difficulty of extracting high-resolution features from the elongated canopy. We redesigned YOLOv7-tiny for GLDD and conducted a series of ablation experiments to evaluate its performance. Experimental results show that GLDD outperforms YOLOv7-tiny by 3.1% and YOLOv6-tiny by 6.5%, reaching an accuracy of 88.2%. In comparison to several one-stage object detectors such as YOLOv5, YOLOX, PP-YOLOE, and YOLO-FaceV2, GLDD obtains the best detection results. Additionally, compared to convolutional-based detectors such as Faster-RCNN and transformer-based detector SwinT, GLDD performs better in speed and accuracy. Furthermore, GLD-infected grapevine distribution is also mapped by using GLDD detection results at the field scale.

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