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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhang, Jialiang An, Jianqi Wu, Min Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Department of Computer Science School of Computing Tokyo Institute of Technology Yokohama226-8502 Japan

The development and distribution states of the blast furnace (BF) gas flow determine whether the reaction in the furnace can proceed normally and decide the utilization efficiency of the carbon in the furnace and the stable smooth operation of the furnace. The internal environment of BF is closed with high temperature and high pressure, which causes that the relationship between the development situation of edge gas flow of the BF and the BF operation is uncertain. In this paper, a prediction model of edge gas flow development state based on BP neural network (BPNN) is proposed, clarifying the relationship between the development state of edge gas flow and the edge burden parameters. Firstly, this paper gets the relative operation factors of effecting the development situation of edge gas flow through analyzing the process mechanism of the BF ironmaking, and proposes the development index of edge gas flow and the heat load of cooling stave to measure the development state of the edge gas flow. Secondly, the intrinsic correlation between the data is verified, and the data are analyzed by Spearman's rank correlation coefficient (SRCC) analysis. Finally, according to the analysis results, combined with the burden mechanism, the edge gas flow prediction model is established to realize the prediction of the development state of the edge gas flow. The calculation of the data collected in the metallurgy scene of the BF suggested that this prediction model of the edge gas flow development state of the BF could describe the relationship between BF operation parameters and the developing state of the edge gas flow.

关键词： Flow of gases

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An Online Modeling Method for Formation Drillability Based on OS-Nadaboost-ELM Algorithm in Deep Drilling Process

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IFAC-PapersOnLine 2017年第1期50卷 12886-12891页

作者： Gan, Chao Cao, Weihua Wu, Min Chen, Xin Hu, Yule Wen, Guojun Gao, Hui Ning, Fulong Ding, Huafeng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Adavanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Faculty of Engineering China University of Geosciences Wuhan430074 China School of Mechanical Engineering & Electronic Information China University of Geosciences Wuhan430074 China

To achieve safety, high quality, and efficiency in deep drilling, it is necessary to get formation drillability around the borehole during drilling-trajectory planning and intelligent drilling control. Since the drilling data have the characteristics of low value density and noise in the process of deep drilling, it is difficult to model formation drillability in deep drilling. In this paper, a new online modeling method for formation drillability based on online sequential nadaboost extreme learning machine (OS-Nadaboost-ELM) algorithm has been proposed. Firstly, the well logging parameters are chosen as the inputs of the model, whose output is formation drillability. Then, several ELM models are established and the outputs of these models are as weak learners. Then the weak learners are combined by Nadaboost algorithm in order to get a strong learner. Finally, the recursive least squares algorithm is used to adjust the model. The numerical test results show that, in both prediction accuracy and training efficiency aspects, the proposed method is better than other prediction methods such as multiple regression, gray method, back-propagation neural networks, Nadaboost extreme learning machine and online sequential extreme learning machine. Thus the prediction model serves as the online geological model to develop intelligent drilling systems. © 2017

关键词： E-learning

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Stability analysis of load frequency control systems with two delays in each area

Stability analysis of load frequency control systems with tw...

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Annual Conference of Industrial Electronics Society

作者： Fei Long Chuan-Ke Zhang Yong He Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In networked load frequency control (LFC) systems, time-varying delays could come from two aspects: measurements' transmission from power plant to control center and control signals from the control center to plant side, because of the use of open communication networks. Those delays can affect the dynamic performance and the stability of the system. In this paper, the two delays are considered in one-area LFC system, instead of combining these two delays into one, when the delay-dependent stability analysis is carried out by using Lyaponuvtheory and linear matrix inequality (LMI) technique. Moreover, the dynamic delay interval method is employed to derive less conservative delay-dependent stability criteria for such time-delay system compared with the existing results. Finally, the effectiveness of the proposed criteria are verified by two case studies.

关键词： Delays Stability criteria Time-varying systems Power system stability Frequency control Symmetric matrices

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Hybrid Prediction Model of Carbon Efficiency for Sintering Process

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IFAC-PapersOnLine 2017年第1期50卷 10238-10243页

作者： Hu J. Wu M. Chen X. She J. Cao W. Chen L. Ding H. School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan School of Mechanical Engineering & Electronic Information China University of Geosciences Wuhan 430074 China

Sintering process is the second most energy-consuming process in ironmarking. The main source of energy consumption is the consumption of carbon. It is significant to predict the carbon efficiency to reduce the energy consumption. In the paper, first, the comprehensive coke ratio (CCR) is defined and used as an index to measure the carbon efficiency by analyzing the sintering mechanism. The principal component analysis method is used to find the principal components affecting the CCR. Next, they are divided into different subclasses by adopting the fuzzy C-means clustering algorithm. Then, the least square-support vector machine (LS-SVM) sub-models are established based on the subclasses, and the parameters of the sub-models are obtained using an adaptive particle swarm optimization algorithm. Finally, a FCM-LSSVM model is established by weighting each LS-SVM sub-model with a fuzzy membership function. The simulations using actual production data show that the prediction accuracy of the FCM-LSSVM model is higher than that of a BP neural network model and a single LS-SVM model, and it meets the requirements of actual production. © 2017

关键词： Adaptive particle swarm optimization Comprehensive coke ratio Fuzzy C-means LS-SVM model Principal component analysis Sintering process

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A trajectory tracking control strategy based on finite element method for planar three-link underactuated manipulator

A trajectory tracking control strategy based on finite eleme...

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Annual Conference of Industrial Electronics Society

作者： Yawu Wang Xuzhi Lai Haoqiang Chen Pan Zhang Min Wu School of Automation China University of Geosciences Wuhan Hubei China Intelligent Automation for Complex Systems Hubei Key Laboratory of Advanced Control Wuhan Hubei China

This paper presents a trajectory tracking control strategy based on the finite element method for a planar three-link underactuated manipulator with a passive third joint. From the mechanical structure, the manipulator can be thought of as composed of two parts. The first part is the first link of the manipulator, which is a single link manipulator system. The second part consists of the remaining two links, which can be seen as a plananr Pendubot. First, a finite element model of the planar Pendubot is built by using COMSOL, and the coupling relationship between its active link and its passive link is analyzed. Then, two servo controllers (A and B) with the same structure are designed for two active links of the manipulator, respectively. The servo controller A is directly applied to control the angular velocity of the first link of the manipulator rotating with a constant speed, which makes the end-point of the manipulator move along the trajectory direction. Next, a fuzzy system is designed based on the coupling relationship of the planar Pendubot to calculate the target angular velocity of the second link of the manipulator according to the tracking error and its change rate. The servo controller B is applied to control the angular velocity of the second link of the manipulator, which makes the tracking error converge to zero. Finally, Simulation results demonstrate the effectiveness and the robustness of the proposed control strategy.

关键词： Manipulators Servomotors Zirconium Couplings Angular velocity Trajectory tracking Fuzzy systems

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FCM-based multiple random forest for speech emotion recognition 5

FCM-based multiple random forest for speech emotion recognit...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhou, Mengtian Chen, Luefeng Xu, Jianping Cheng, Xianghui Wu, Min Cao, Weihua She, Jinhua Hirota, Kaoru 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 Engineering Tokyo University of Technology Tokyo192-0982 Japan Tokyo Institute of Technology Yokohama226-8502 Japan

Speech emotion recognition (SER) is of great importance in the human-robot interaction, and SER have been developed rapidly in recent years. How to identify high correlation features is a main question. In this paper, multiple random forest (MRF) is proposed, which can effectively predict up to several thousand explanatory variables, and improve the recognition result. At the mean time, personalized features and non-personalized features are fused for SER that can be divided into different subclasses by adopting the fuzzy C-means (FCM) clustering algorithm, then FCM-based MRF is proposed. Finally, our model is established, and the confusion matrix is output. Moreover, we conduct a separate classification of some certain emotion, which are difficult to recognition to some extent. And results show that the proposed method of FCM-based MRF achieves good performance for SER, which the recognition accuracy is 84.17%.

关键词： Clustering algorithms

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Consensus control of Second-Order Stochastic Delayed Multi-Agent Systems with Intrinsic Dynamics and Undirected Topologies

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IFAC-PapersOnLine 2017年第1期50卷 2421-2426页

作者： Zong X. Li T. Zhang J.-F. School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan 430074 China Department of Mathematics East China Normal University Shanghai 200241 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China

In this paper, we address the consensus control of stochastic multi-agent systems with intrinsic dynamics based on measurements with time-delay and multiplicative noises under undirected graphs. By developing degenerate Lyapunov functional and stochastic stability theorem, we establish mean square and almost sure consensus conditions explicitly related to the nonlinearity of agent dynamics, control gains, noise intensities and parameters of network graphs. Especially, for the case with linear dynamics, we get necessary conditions for mean square consensus. It is shown that with respect to the weighted-average type control protocols, second-order multi-agent systems are kept mean square consentable with multiplicative measurement noises alone or intrinsic dynamics alone, but may become unconsentable due to the co-existence of multiplicative noises and intrinsic dynamics. © 2017

关键词： consensus intrinsic dynamics multiplicative noise Second-order multi-agent system time-delay

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Proposal of Initiative Service Model for Service Robot

Proposal of Initiative Service Model for Service Robot

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第十二届中国智能机器人大会

作者： Man Hao Weihua Cao Min Wu Zhentao Liu Luefeng Chen Ri Zhang School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Service robots are becoming a part of our *** realize friendly human-robot interaction,an initiative service model for service robot is proposed,which is composed of three layers,i.e.,information acquisition layer,in which communication information and environmental information are collected by sensors;decision layer,in which personal intention and emotional states are obtained by multi-modal emotion recognition and intention understanding,and users' demands are obtained by demand analysis model;initiative service execution layer,in which the task execution and emotion adaption of robot are carried *** service can sense motive of people,by which a humanized and real-time service could be *** service experiments are performed,including passive service and initiative service of *** results show that the drinking time of passive service lags behind the initiative service 30 minutes on average,and the initiative service renders drinking service 2 times more than passive service on average,besides,the water quantity provided by initiative service is more reasonable,which demonstrates the feasibility of the *** prospect,initiative service model could be applied to many occasions in our daily life,e.g.,family service,caring for the elderly,and medical rehabilitation.

关键词： service robots service pattern fuzzy production rules emotion recognition intention understanding

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Maximum power point tracking control of direct-drive permanent magnet wind turbine based on adaptive neuro-fuzzy inference system 5

Maximum power point tracking control of direct-drive permane...

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5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Ding, Min Ou, Yingxiong Hu, Bo She, Jinhua Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China State Grid Energy Research Institute Beijing102200 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

The power from wind varies depending on the environmental factors. Because of the randomness and intermittent of wind, it is difficult for the wind energy conversion system to locate and track the maximum power point (MPP) with fast speed and high accuracy under the condition of variable wind speed. In this paper, a variable-speed wind-generator maximum power point tracking (MPPT) control method based on adaptative neuro-fuzzy inference system (ANFIS) is presented. It is designed as a combination of the Sugeno fuzzy model and neural network. The ANFIS based controller predicts the optimum speed with the inputs as the speed change and power change, and controls the speed with PI controllers. The performance of the proposed controller is tested for direct-drive permanent magnet wind turbine based wind energy conversion system under fast wind speed variation in MATLAB/Simulink. The simulation results show that the designed control method has good dynamic characteristics and steady-state accuracy in wind power MPPT and improves the working efficiency.

关键词： Wind turbines

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Suppressing the pressure fluctuations caused by drill string vibration by SP-EID method

Suppressing the pressure fluctuations caused by drill string...

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Asian control Conference

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

ISBN: (纸本)9781509015740;9781509015733

During drilling process, the axial vibration of the drill string always causes the fluctuations of the bottom hole pressure, which may lead to serious accidents. At the same time the bottom hole pressure control system also has the phenomenon of parameter change and the feedback delay, so that the pressure is difficult to control. In view of this situation, we develop a method combining Smith Predictor with equivalent input disturbance(SP-EID) approach to achieve the disturbance suppression and delay compensation. First, considering the changes in the model parameters, we improve the existing hydraulic model to describe the dynamic characteristics of the bottom hole pressure, at same time the mathematical form of the disturbance is given. Then we use the Smith Predictor to compensate the delay of the feedback channel and apply EID method to suppress pressure disturbances. Finally the SP-EID method is used to adjust the mud flow on the ground to control the bottom hole pressure. The simulations are conducted to compare our method with SMC method, in order to show the superiority and effectiveness of our method.

关键词： Mathematical model Delays Matrix decomposition Vibrations State feedback Symmetric matrices

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