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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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Deep-Learning-based Identification of Influential Spreaders in Online Social Networks

Deep-Learning-based Identification of Influential Spreaders ...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Feng Wang Jinhua She Yasuhiro Ohyama Min Wu School of Engineering Tokyo University of Technology Tokyo Japan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Effective influential spreaders prediction in online social networks is critical for a variety of network services such as viral marketing, online recommendation, and many more. The conventional machine learning methods mainly adopted various hand-crafted features in the prediction models. However, their effectiveness relies on the domain knowledge heavily, and thus it is difficult to generalize these models to different domains. In this paper, we propose an Influence Deep Learning (IDL) model to learn users' latent feature representation for predicting influence spread. Our IDL model is fully data-driven, and it takes sampling subnetworks as input to the deep neural networks for learning users' latent vector representation. Moreover, we design a strategy to incorporate user-specific features and network structure into the graph convolutional neural network to overcome the imbalance problem of labeled training data. The experimental results show that our model outperforms other baselines in online social networks, and our model is more practical in large-scale data sets.

关键词： Social network services Machine learning Predictive models Neural networks Integrated circuit modeling Support vector machines Training

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Periodic event-triggered output regulation for linear multi-agent systems

arXiv

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arXiv 2020年

作者： Zheng, Shiqi Shi, Peng Agarwal, Ramesh K. Lim, Chee Peng 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 Electrical and Electronic Engineering University of Adelaide AdelaideSA5005 Australia Department of Mechanical Engineering Washington University Box 1185 St Louis CampusMO63130 United States Institute for Intelligent Systems Research and Innovation Deakin University Australia

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have access to the system matrix and states of the leader. Meanwhile, the PET mechanism is considered not only in the communication between various agents, but also in the sensorto-controller and controller-to-actuator transmission channels for each agent. The above problem set-up will bring some challenges to the controller design and stability analysis. Based on a novel PET distributed observer, a PET dynamic output feedback control method is developed for each follower. Compared with the existing works, our method can naturally exclude the Zeno behavior, and the inter-event time becomes multiples of the sampling period. Furthermore, for every follower, the minimum inter-event time can be determined a prior, and computed directly without the knowledge of the leader information. An example is given to verify and illustrate the effectiveness of the new design scheme. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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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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Short-term load forecasting based on GA-BPNN-SVR optimization algorithm 8

Short-term load forecasting based on GA-BPNN-SVR optimizatio...

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作者： He, Lianghua Ge, Lai Zhang, Hao Wang, Guowei School of automation China University of Geosciences Wuhan Hubei430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China

In order to improve the accuracy of short-term power load forecasting, an algorithm that simultaneously optimizes SVR parameters and optimizes the selection of input features is proposed. Firstly, the input features are selected by BP neural network. In order to avoid the influence of the randomness of the initial weights and thresholds on the optimization, the GA algorithm is used to optimize the weights and thresholds. Secondly, using GA algorithm to optimize the parameters of support vector regression, a short-term load forecasting model based on GA-BPNN-SVR optimization algorithm is obtained. Finally, the GA-BPNN-SVR model is applied to practical short-term power load forecasting, and the forecasting effect is compared with that of GA-SVM and BPNN-SVR models. The results show that the average absolute percentage error obtained by this method is only 1.74%, which is 1.64% and 3.11% lower than the average absolute percentage error obtained with GA-SVM model and BPNN-SVR. This algorithm can be effectively used for short-term load forecasting of power systems. © 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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Fault detection of networked singularly perturbed systems under the stochastic communication protocol 8

Fault detection of networked singularly perturbed systems un...

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作者： Wan, Xiongbo Lu, Li Li, Jiankang Han, Tizhuang Li, Yongzhi School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China

In this paper, the fault detection problem has been investigated for networked singularly perturbed systems with time delays under the stochastic communication protocol (SCP). To avoid/alleviate the undesired data collisions, the SCP is introduced to schedule the data transmissions, under which the sensor nodes obtain access to the communication network according to a stochastic sequence with a known probability distribution. Our aim is to design a fault detection filter (FDF) such that, for all external disturbances and the transmitted measurements under the SCP, the error between the residual and the fault is made as small as possible. Based on the discrete Wirtinger-based inequality, a sufficient condition in terms of linear matrix inequalities (LMIs) is derived, which guarantees the existence of the desired FDF for any singular perturbation parameter belonging to a predefined interval. When these LMIs are feasible, the parameters of the desired FDF are explicitly given. A numerical example is given to illustrate 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： Time delay

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Two-DOF Speed control of Permanent Magnet Synchronous Machine with a novel Parameter Identification Method

Two-DOF Speed Control of Permanent Magnet Synchronous Machin...

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第三十九届中国控制会议

作者： Mingjin Hu Wei Hua Xudong Wu Chengdong Wu Dazhi Wang Zhentao Liu Xiaofang Yuan Wennong Zhang School of Electrical Engineering Southeast University Faculty of Robot Science and Engineering Northeastern University College of Information Science and Engineering Northeastern University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems College of Electrical and Information Engineering Hunan University

In this paper, a two-degree-of-freedom（2-DOF） speed control scheme for permanent magnet synchronous machines is developed. Both the reference-tracking and disturbance rejection performance are taken into account and only a single parameter related to expected bandwidth determines the dynamics. To improve the performance of speed control, a novel identification method for mechanical parameters is also proposed. The effectiveness of the proposed method is verified by simulations.

关键词： Speed control two-degree-of-freedom permanent magnet synchronous machine parameter identification

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A survey of computer vision-based tracking registration technology for augmented reality 8

A survey of computer vision-based tracking registration tech...

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作者： Li, Yuqing Hong, Xin Xu, Chi School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China

Augmented reality technology is a research hotspot in the field of computer vision in recent years. Tracking registration technology determines the performance of augmented reality systems. The accuracy of tracking registration directly affects the users experience. Therefore, the research of tracking registration technology is of great significance. In this paper, augmented reality and its core tracking registration technology are introduced firstly. Then, the visual tracking registration method based on marker and natural features are elaborated, and the more advanced visual SLAM-based tracking registration method in recent years is summarized. Finally, the main problems of the current research and possible development directions are analyzed. © 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： Augmented reality

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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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The influence of color temperature mismatch in star simulator on positioning accuracy and magnitude measurement by star sensor

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Journal of Physics: Conference Series 2021年第1期2132卷

作者： Zhiyong Wang Shishen Liu Hao Sun Jingjing Zhang Ruyou Li Chen Liu School of Automation China University of Geosciences Wuhan Hubei 430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai 200083 China

During the calibrating of star sensor, the calibration accuracy is greatly affected by the mismatch between the color temperature of the light and the to-be-measured star, which further affects the attitude measurement accuracy. This paper studied the near-infrared spectra of stars with different color temperatures, and analyzed the errors on star positioning and magnitude measurement of star sensor due to the color temperature mismatch. The results showed that in the central field of view, the spot centroid deviation caused by spectral mismatch is smaller than that in the edge field of *** the defocus of the imaging surface also affects the spot centroid deviation. Besides, when calibrating with 6000K color temperature light, the maximum measurement error can reach -1.9126 magnitude.

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