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检索条件"机构=Hubei key Laboratory of Adavanced Control and Intelligent Automation for Complex Systems"

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Speaker-independent Speech Emotion Recognition Based on Random Forest Feature Selection Algorithm 36

Speaker-independent Speech Emotion Recognition Based on Rand...

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第36届中国控制会议

作者： Wei-Hua Cao Jian-Ping Xu Zhen-Tao Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Feature selection is a crucial step in the development of a system for identifying emotions in *** to select high correlation features is an open *** paper focuses on feature selection method which aims to extract the most effective acoustic features to improve the performance of emotion *** feature selection of speakerindependent speech based on Random Forest is proposed,which can remove the redundant features that have high correlations with each *** on the speech emotion recognition based on Support Vector Machines(SVM) is performed,where the speaker-independent features selected by the proposal and Spearman correlation analysis are used for emotion recognition,*** results show that the proposal achieves 78.6%recognition rate on average,which is 2.2%higher than using Spearman.

关键词： Emotion Recognition Speech Speaker-independent Feature Selection Random Forest

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New Result for Synchronization of Chaotic Lur'e systems with Time Delay Using Sampled-data control 36

New Result for Synchronization of Chaotic Lur'e Systems with...

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第36届中国控制会议

作者： SHANGGUAN Xingchen HE Yong ZHANG Chuanke WU Min School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper investigates synchronization problem of two identical chaotic Lur'e systems with time delay using sampleddata control. Firstly, a novel piecewise Lyapunov-Krasovskii function(LKF), which considers fully useful information of the systems and their cross terms, is introduced. Secondly, a new synchronization criterion is developed in terms of linear matrix inequalities(LMIs) by discarding the positive definite constraint of the piecewise LKF. Then, maximal sampling interval and corresponding controller are obtained. At last, case study based on a typical Chua's circuit is carried out to verify the effectiveness and advantages of the proposed method.

关键词： Chaotic Lur'e system Sampled-data control Synchronization Time delay Piecewise functional

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Market-based task assignment for multi-point dynamic aggregation tasks 48

Market-based task assignment for multi-point dynamic aggrega...

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48th International Conference on Computers and Industrial Engineering, CIE 2018

作者： Du, Xin Zhang, Jia Xin, Bin Ding, Yulong Peng, Zhihong Dou, Lihua School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

Multi-agent task assignment problem exists in collaborative target tracking, collaborative rescue, regional search, etc. Most researchers regarding multi-agent task assignment only consider static tasks. However, in complex scenarios, the states of tasks (e.g., Monitoring of hazardous environments) are time-varying. This type of the task can be modeled as a multi-point dynamic aggregation (MPDA) process. This paper proposes a distributed task assignment method for the MPDA task. This method firstly adopts an auction algorithm to obtain a pre-allocation planning that can ensure every task can be completed. Then, the agents who complete the pre-allocation planning will evaluate the uncompleted tasks and assist other agents to complete these tasks, so that tasks can be completed as soon as possible. Compared with the optimal solution, simulations show that the task allocation method can obtain satisfied allocation solutions with a lower computational cost. The gap from the optimal solution is only 8% on average. Especially, for problems including more than 100 tasks, the proposed method can obtain planning solutions within one second, and the makespan of the MPDA task is more than 50% better than the best one of the 1000 random sample solutions. © 2018, Curran Associates Inc. All rights reserved.

关键词： Optimal systems

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Communication Atmosphere in Humans and Robots Interaction Based on Fuzzy Analytical Hierarchy Process 36

Communication Atmosphere in Humans and Robots Interaction Ba...

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第36届中国控制会议

作者： Ri Zhang Yong He Zhen-Tao Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Communication atmosphere in Human-Robot Interaction（HRI） is estimated by integrating emotional states of humans and robots based on the concept of Fuzzy Atmosfleld（FA）,where human emotion is estimated from bimodal communication cues（i.e.,speech and facial expression） and robot emotion is generated by emotional expression *** Analytical Hierarchy Process（FAHP） is used for dynamic weight calculation of emotional states of humans and robots in the FA model,in which a three-level hierarchy is adopted for the analysis of communication atmosphere and four acoustic cues（i.e.,volume,rate,pitch,and duration） are utilized to calculate the dynamic *** is conducted in a multi-modal emotional communication based humans-robots interaction（MEC-HRI） system,by which experimental results demonstrate the validity of proposed FA *** the communication atmosphere can help to facilitate smooth communication between humans and robots by adjusting robot behavior for emotion *** proposal is being planned for an atmosphere representation system for realizing causal communication in HRI and background music is being considered for the FA model.

关键词： Communication Atmosphere Human-Robot Interaction Fuzzy Analytical Hierarchy Process Dynamic Weight

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An improved stability criterion for singular systems with time-varying delay via a relaxed integral inequality 36

An improved stability criterion for singular systems with ti...

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第36届中国控制会议

作者： ZHI Ya-Li HE Yong WU Min School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper concerns the stability problem of singular systems with time-varying delay. According to different delaypartition intervals, an augmented Lyapunov-Krasovskii functional with delay cross terms is constructed. Based on it, using the relaxed integral inequality technique is to obtain a less conservative stability criterion. As a result, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

关键词： Stability Singular systems with time-varying delay Lyapunov-Krasovskii functional Relaxed integral inequality

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Application of neural network in modeling of activated sludge wastewater treatment process 36

Application of neural network in modeling of activated sludg...

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第36届中国控制会议

作者： Li Jun Zhang Neng Li Jing Jing Zhang Xi Yong Tian School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

This paper present a prediction model for three different objection(the airflow rate,the carbonaceous biochemical oxygen demand(CBOD) of the effluent,and the total suspend solids(TSS) of the *** model is built by the MLP neural *** accurancy of the prediction result of MLP neural network is compared with the accurancy of the result of trational stational autoregressive model(AR).The conclution is that the percentage error prediction model of the MLP neural network(PE),the fractional deviation(FB),normalized mean square error(NMSE),the mean absolute error(MAE) and mean square error(MSE) prediction model of evaluation index is better than the AR *** other words,the prediction model based on MLP neural network provides a reliable basis for reducing the energy consumption in the activated sludge process of industrial waste water treatment and further improving its effect on the treatment of industrial waste water.

关键词： Industrial waste water treatment Activated sludge process MLP neural network Data mining

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Experimental Study on Decentralized Concurrent Learning for Multi-Agent System with complex Dynamics 36

Experimental Study on Decentralized Concurrent Learning for ...

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第36届中国控制会议

作者： Ting Fei Xin Chen Min Wu Chi Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

A cooperative multi-agent system entitles some independent agents to complete complex tasks through coordination and *** the dynamics of physical agents are so complex that the environment of learning is indeed stochastic,the paper introduces the decentralized multi-agent reinforcement learning（MARL） algorithm,named as Decentralized Concurrent Learning with Cooperative Policy Exploration（DCL-CPE）,in order to solve cooperative learning within stochastic *** investigate its feasibility in practical multi-agent systems,the box-pushing test with DCL-CPE is designed with a group of two-wheel driven robots acting as learning *** to physical properties,such as nonholonomic dynamics,rolling and sliding frictions,unreliable sense,rigid body collision,etc.,the cooperative learning is a high stochastic learning *** simulation test in Webots shows that DCL-CPE is good at exploring best cooperative policy in a decentralized way,even as state transition and rewards are all stochastic.

关键词： Multi-agent system Decentralized cooperative learning Stochastic environment Webots

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Establishment and Optimization of Gas Flow Prediction Model for Annealing Furnace Based on GA-SVM 37

Establishment and Optimization of Gas Flow Prediction Model ...

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37th Chinese control Conference, CCC 2018

作者： Qu, Qilin Yuan, Yan Yali, Jin Zhang, Yongyue China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China School of Information Science and Engineering Central South University Changsha410083 China

ISBN: (纸本)9789881563941

T0616. The temperature accuracy of the steel coil is directly affected the production quality of the steel plate. In the annealing furnace temperature control system, strip temperature control is mainly decided by various furnace annealing furnace gas flow in the area, so setting up a precise model between gas flow and temperature has become an important problem of the control system of annealing furnace. In this paper, SVM is applied to the prediction model of the gas flow in the annealing furnace since it's suitable for nonlinear and high dimensional problems as a machine learning method. In view of that the choice of C, G and the model parameters of the SVM directly affect the prediction precision of the model, this paper uses GA to optimize these two parameters. Finally, we use the data of field production as training and testing samples to establish and verify the model. The experimental results showed that the established model well achieved the requirements of the accuracy of the target. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Flow of gases

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Bat Algorithm Optimizer for Drilling Trajectory Designing under Wellbore Stability Constraints

Bat Algorithm Optimizer for Drilling Trajectory Designing un...

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第37届中国控制会议

作者： Jiafeng Xu Xin Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

In the process of deep geological resources exploration, there are often some complex stratigraphic situations. A threedimension drilling trajectory is designed by using the geological environment data. The trajectory should be sure that the target position is reachable. And it can avoid the area prone to be in an accident. In order to solve this problem, this paper discusses a three-dimensional wellbore trajectory design optimization model suitable for shale gas horizontal mining. Considering the wellbore stability and dogleg severity as constraints, the minimum drilling length is taken as the objective function. Depending on the Mohr-Coulomb criterion, the range of azimuth angle and inclination angle of safety trajectory can be determined. It can be seen as a constraint on the wellbore derrick segment. As for the optimization algorithm, bat algorithm（BA） optimizer combined with a penalty function method is applied to this optimization model. Finally, the case study shows that the BA performs well in the wellbore optimization design. It obtains the trade-off result between the safe and efficient drilling demands. And, it provides a basic model idea for the real-time trajectory optimization while drilling.

关键词： Drilling Trajectory Designing Wellbore Stability Bat Algorithm

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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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第37届中国控制会议

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

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 *** 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： Deep learning emotion understanding convolution neural network facial expression body gesture

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