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23rd IEEE International Conference on automation and Computing, ICAC 2017

作者： Wan, Xiongbo Wang, Zidong Ren, Chuanyu 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 Department of Computer Science Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom

ISBN: (纸本)9780701702618

This paper investigates the problem of H∞ state estimation for discrete-time stochastic genetic regulatory networks (GRNs) with switching parameters, time-varying delays, and exogenous disturbances. A new discrete-time stochastic GRN model with switching parameters is proposed by assuming that the sojourn probability of each subsystem of the GRN under consideration is known. By using the stochastic analysis approach, sufficient conditions are derived under which the augmented estimation error system is stochastically stable and satisfies a prescribed H∞ disturbance attenuation level γ. The gain matrices of the desired state estimator can be obtained by solving a matrix inequality. A numerical example is given to illustrate the effectiveness of the designed state estimator. © 2017 Chinese automation and Computing Society in the UK - CACSUK.

关键词： State estimation

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A prediction model of edge gas flow development state based on BP neural network 5

A prediction model of edge gas flow development state based ...

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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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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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Path Planning of Messenger UAV in Air-ground Coordination

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IFAC-PapersOnLine 2017年第1期50卷 8045-8051页

作者： Yulong D. Bin X. Jie C. Hao F. Yangguang Z. Guanqiang G. Lihua D. School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China

This paper addresses a UAV path planning problem for a team of cooperating heterogeneous vehicles composed of one unmanned aerial vehicle (UAV) and multiple unmanned ground vehicles (UGVs). The UGVs are used as mobile actuators while the UAV serves as a messenger to achieve information sharing among the UGVs. The UAV needs to fly over each UGV periodically to collect the information and then transmit the information to the other UGVs. The UAV path planning problem with messenger mechanism is formulated as a Dynamic Dubins Traveling Salesman Problem with Neighborhood (DDTSPN). The goal of this problem is to find the shortest route enabling the UAV to deliver information to all requested UGVs. When solving this path planning problem, a decoupling strategy is introduced to sequentially determine the access sequence of UGVs for UAV and the access location of UAV in the communication neighborhood of each UGV. The effectiveness of the proposed approach is corroborated through computational experiments on several randomly generated instances. © 2017

关键词： Air-ground coordination DDTSPN Dubins path planning messenger mechanism

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An approach of joint-space trajectory generation 5

An approach of joint-space trajectory generation

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

作者： Chen, Xin Jiang, Chen-Xu Zhou, Li School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhanz430074 China School of Arts and Communication China University of Geosciences Wuhan430074 China

Trajectory generation is a prerequisite for robot control system and is divided into two regions, Cartesian space and joint space. This paper presents an approach to generate the trajectory in joint-space. This method uses normalization and transformation of the sine function to generate the desired trajectory, which is more smooth and continuous than the parabolic method in multiple time derivatives of the joint parameter. Compared with the third order polynomial method, this approach can depress the unacceptable infinite spikes in the jerk, which is the derivative of acceleration. Besides, the using of normalization in this approach is to make it more convenient and efficient be applied.

关键词： Trajectories

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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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