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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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Hierarchical Prediction Model Based on BP Neural Network for Predicting CO/CO_2 in Iron Ore Sintering Process

Hierarchical Prediction Model Based on BP Neural Network for...

引用

Chinese control Conference

作者： Ben Xu Xin Chen Yang Zhou School of Automation China University of Geosciences Wuhan China Intelligent Automation for Complex Systems Hubei key Laboratory of Advanced Control Wuhan China

The sintering process is one of the most energy-consuming processes in steelmaking, its carbon fuel consumption accounts for 8% to 10% in the steel production process. To find ways of reducing the energy consumption, it is necessary to predict the carbon efficiency. The value of CO/CO_2 in the carbon emission can reflect the utilization of carbon combustion in sintering process. In this study, the CO/CO_2 is taken to be a measure of carbon efficiency and a hierarchical model is built to predict it. Firstly, the physical and chemical reactions and the carbon flow mechanism in the sintering process are analyzed, and the process parameters that affect the CO/CO_2 are determined. Then, the gray relational analysis method is used to analyze the influence factors to determine the relationship between the parameters, and a hierarchical predictive model for CO/CO_2 is established based on the relationship between the parameters. The hierarchical predictive model is divided into two parts: the predictive models for the thermal state parameters and the predictive model for CO/CO_2. The inputs of the predictive models for the thermal state parameters are the raw material parameters and the operating parameters, and the inputs of the predictive model for CO/CO_2 are the predicted values of the predictive models for the thermal state parameters. Finally, the simulation results verify the effectiveness of the proposed modeling method. This method can provide a theoretical basis for the optimization and control of carbon efficiency in the sintering process.

关键词： Predictive models Combustion Correlation Mathematical model Carbon dioxide Chemicals Raw materials

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Modeling and Maximizing Angle Coverage in Visual Sensor Networks

Modeling and Maximizing Angle Coverage in Visual Sensor Netw...

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第37届中国控制会议

作者： Yonghua Xiong Manjie Lu Wei Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Guizhou Tobacco Science Institute

Maintaining the quality of network coverage is a major concern in visual sensor networks. In this paper, we study the angle coverage problem in visual sensor networks, considering the target is very large, and each camera node can only monitor a portion of its perimeter. The goal of the proposed work is to schedule camera nodes to achieve maximum angle coverage in different period. Firstly, we establish a novel coverage model and formally prove that the problem is NP-hard in ***, we present a scheduling scheme based on greedy algorithm, to schedule camera nodes into disjoint cover sets working in ***, we conclude that the approximate ratio of the proposed algorithm is k, theoretically, and the time complexity of the algorithm is O（n）. Finally, extensive simulations have been conducted to evaluate the performance of the proposed algorithm.

关键词： Visual sensor network angle coverage camera node scheduling greedy algorithm

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Street Object Detection Based on Faster R-CNN

Street Object Detection Based on Faster R-CNN

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第37届中国控制会议

作者： Wendi Cai Jiadie Li Zhongzhao Xie Tao Zhao Kang Lu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Library of Wuhan University of Technology

With the increased number of traffic accidents, the research and development of smart cars have been *** detection of street objects has become one of the important research topics. Generic Model detection algorithm based on Convolution Neural Network(CNN) need to design the training model, while the training and testing of the model will take a lot of time. Transfer Learning is used to fine-tune the pre-trained models, using the Image task datasets of COCO, transferring a generic deep learning model to specific one with different weights and outputs. Furthermore, the CNN structure is adjusted to improve overall performance, and the street environment is trained to the special scene. We compare the results of experiments,and the results showed that the network which is fine-tuned is effective.

关键词： Transfer Learning Faster R-CNN Inception-ResNet-v2 Object Detection

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Multi-Convolution Neural Networks-Based Deep Learning Model for Emotion Understanding

Multi-Convolution Neural Networks-Based Deep Learning Model ...

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Chinese control Conference

作者： Luefeng Chen Min Wu Wanjuan Su Kaoru Hirota Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Tokyo Institute of Technology Yokohama Japan

Multi-convolution neural networks-based deep learning model in combination with multimodal data for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using multi-convolution neural networks, where multilayer convolutions are connected in series and multiple networks are executed in parallel. Moreover, when optimizing the weights of deep neural network by traditional method, it is easy to fall into poor local optimal. To address this problem, a hybrid genetic algorithm with stochastic gradient descent is developed, which has the capacity of inherent implicit parallelism and better global optimization of genetic algorithm so that it can adaptively find the better weights of the network. And in order to speed up the convergence of the proposal, the weights optimized by stochastic gradient descent will be taken as a chromosome of genetic algorithms initial population, and it also can be used as a priori knowledge. To verify the effectiveness of the proposal, experiments on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-the-art methods. Meanwhile, the preliminary application experiments are also carried out and the results indicate that the proposal can be extended to human-robot interaction.

关键词： Feature extraction Genetic algorithms Biological cells Machine learning Sociology Statistics Neural networks

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Optimal Consensus control of Unknown Nonlinear Multi-Agent Systems Using Adaptive Dynamic Programming via MRAC

Optimal Consensus Control of Unknown Nonlinear Multi-Agent S...

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第37届中国控制会议

作者： Hao Fu Xin Chen Wei Wang Jinbin Li Yaodong Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems State Grid Hubei Electric Power Research Institute

This paper introduces an optimal consensus control scheme for nonlinear multi-agent systems with completely unknown dynamics. In general, it is difficult to solve the coupled Hamilton-Jacobi-Bellman（HJB） equations, which the optimal consensus control relies on in multi-agent systems, especially unknown nonlinear systems. For the purpose of solving the problem, we propose an optimal consensus control approach based on the model reference adaptive control（MRAC） and adaptive dynamic programming（ADP）. Using the structure of the diagonal recurrent neural network, the identifier and controller are devised to achieve MRAC for every plant of the unknown nonlinear systems, i.e. the reference model serves as a dynamic model of each individual agent. Then, according to reference models of distributed agents, an adaptive dynamic programming（ADP）is introduced to approximate the solution of the coupled HJB equations.

关键词： Multi-agent systems optimal consensus model reference adaptive control adaptive dynamic programming

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Hexagon-Shaped Screw Recognition and Positioning System Based on Binocular Vision

Hexagon-Shaped Screw Recognition and Positioning System Base...

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第37届中国控制会议

作者： Fang Wang Xin Chen Chang Tan Jinbin Li Yaodong Zhang School of Automation China University of Geoscience Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems State Grid Hubei Electric Power Research Institute

Traditional artificial live work asks for a high standard with operator’s mental state and technical level in high-voltage and strong-magnetic environment,which not only reduces the efficiency of modern production and living but also causes potential threats to the safety of ***,developing robot live work has great significance for both academic research and industrial applications.A key problem of the live work for an industrial robot is recognition and positioning of the hexagonshaped screw in substation with high *** solve this problem,this article designs a hexagon-shaped screw recognition and positioning system based on binocular vision in transformer substation.A method for stereo matching including 3 steps is proposed:edge noise of the target is reduced by median filter at the beginning;then the target can be obtained through the image segmentation method of adjusting threshold;further moments are used to express the centers of hexagons in 2 images which work as stereo matching *** depth information can be obtained due to visual geometric relationships based on stereo model and camera calibration parameters based on camera *** experiment results show that the binocular system designed in this article can accurately identify the target with good stability,and the measurement error is controlled in 4%.

关键词： Binocular stereo vision Image segmentation Stereo matching Depth information

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

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

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第37届中国控制会议

作者： Guanzhong Wang Haobin Dong Jian Ge Wang Luo Huan Liu Zhiwen Yuan Jun Zhu Haiyang Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems

Overhauser magnetometer is a weak magnetic measuring instrument based on the dynamic nuclear polarization of free radical *** has the characteristics of high precision,high sensitivity,low power consumption and continuous *** is widely used in geophysics,aeromagnetic surveying,satellite Magnetic measuring,military and various engineering *** 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 *** 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.

关键词： Overhauser magnetometer optimization standard deviation

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Stochastic stability of evolutionary prisoner's dilemma

Stochastic stability of evolutionary prisoner's dilemma

引用

2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Liang, Haili Zhou, Zhao Zhang, Fan Peng, Chen Wang, Yu-Long Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Mathematics Southeast University Nanjing China

ISBN: (纸本)9781538666173

In this paper, we study two-player evolutionary prisoner's dilemma on regular graphs and identify the stochastically stable equilibria for infinite populations. We consider four different update rules: Birth-death(BD), death-birth(DB), imitation(IM) and pairwise comparison(PC). With the same values of cost and benefit of cooperation, we show that there is a unique stochastically stable equilibrium for evolutionary prisoner's dilemma on regular graphs. If the benefit-to-cost ratio is larger than k + 2 (k is the degree of a regular graph), the networked game has a higher fraction of cooperators than that for a well-mixed population. Under certain conditions, the lower graph connectivity can lead to the emergence of more cooperators. Besides theoretical analysis, we demonstrate our results through numerical computations and simulations as well. © 2018 IEEE.

关键词： Stochastic systems

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Calculation Method of Load Distribution for Two-crane Cooperative Lift

Calculation Method of Load Distribution for Two-crane Cooper...

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第37届中国控制会议

作者： Xiaoling Shen Jianqi An Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

Cooperative lifting by two cranes is widely used in the current construction site. Since the influence of changeable load in the cooperative lifting process, it is essential to take the load distribution into consideration while planning the lifting path to ensure the safety of the whole lifting process. However, most researches did not consider the reasonable actual load distribution or just used a certain load in the lift process. This paper analyzes the relationship between crane operations and the pose of the lifted object. Then based on this relationship, this paper gives the method calculating the distribution of actual load over each crane that the planning approach is based. This paper also gives calculation methods and constraints for the skew angle of each lifting rope. The results of simulation show the effectiveness of this calculation method.

关键词： Cooperative Lifting Actual Load Calculation

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An intelligent Selection Strategy for Burden Distribution Based on Classification of Blast Furnace Condition

An intelligent Selection Strategy for Burden Distribution Ba...

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第37届中国控制会议

作者： Kexin Zhang Min Wu Jianqi An School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

Burden distribution plays an important role in the optimization of energy-consuming index of a blast furnace(BF).However, due to the low transparency of this process, operators adjust the burden distribution according to their own experiences,which makes it difficult to keep optimal production indexes for a BF. In this paper, an intelligent selection strategy of burden distribution is devised according to the energy-consuming index, where carbon-monoxide utilization rate(CMUR) is taken as the energy-consuming index. First, state variables are chosen based on the calculated Pearson correlation coefficient among each state variable. Then, the chosen state variables are divided into five clusters by k-means clustering algorithm. Finally, the values of CMUR in each condition cluster with different burden distribution are counted. According to the statistics, the burden distribution with the highest CMUR is judged to be the optimal one. Simulation results based on industrial data show that the proposed strategy selects the optimal burden distribution and provides a reasonable guide for the operators.

关键词： Burden distribution blast furnace k-means carbon-monoxide utilization rate

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