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第41届中国控制会议

作者： Guangjun Wang Yi Zhao Zhi Wang Yangzheng Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In order to improve the efficiency of tea picking,a scheme combining ant colony algorithm and tea picking technology is proposed to plan the picking *** this scheme,k-means clustering algorithm is used to divide the tea picking regions with irregular *** ant colony algorithm is used to carry out path planning for tea in different picking areas,and the best picking effect is selected according to the simulation *** solve the problem of long searching time of ant colony algorithm,the condition of iteration termination is changed to adaptive value,and the optimal route after the last iteration is recorded as the initial value of the next *** simulation results show that the best effect is to divide two picking *** improved ant colony algorithm reduces the operation time and the planned picking path is shorter,which can enhance the real-time tea picking and improve the efficiency of tea picking.

关键词： Tea plucking Path planning Ant colony algorithm K-means clustering

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Tea Bud Recognition Based on Machine Learning 41

Tea Bud Recognition Based on Machine Learning

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第41届中国控制会议

作者： Guangjun Wang Zhi Wang Yi Zhao Yangzheng Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Due to the low efficiency and high cost of manual tea picking,as well as the development and application of machine vision and image recognition technology,the mechanization and intelligence of tea picking will become a *** of all,this paper analyzed the advantages and disadvantages of several common target detection methods by using Matlab ***,considering cost,accuracy and real-time performance,the method of combining K-means clustering and image morphology processing is finally selected to extract tea ***,the method is reproduced on STM32 single chip ***,the effect was verified in the actual tea garden,which laid a foundation for the subsequent intelligent picking.

关键词： Machine learning K-means clustering STM32

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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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Position Attention Network for Object Tracking 41

Position Attention Network for Object Tracking

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第41届中国控制会议

作者： Mingzhong Du Longsheng Wei Shiyu Liu School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In recent years,Siamese-based trackers have achieved excellent performance,most of them usually calculate the similarity of each position on the search region to the object through the cross-correlation layer for tracking obj *** solve the problem that the above method neglects the correspondence of the local information between the object and the search region and cannot adapt to the object deformation well,we propose a Siamese network-based tracker with position attention network(SiamPA).First,we use Siamese backbone network to extract template and search region ***,we adopt the boxguided object feature selection strategy to avoid similarity calculations for background *** addition,we introduce the position attention network instead of the cross-correlation layer to learn the part-level relationship between the object and the search region ***,the classification-regression sub-network is used to decode the similarity respond map obtained by the position attention network and predict the position of the *** contribution,one is to propose a box-guided method for refining object features,and the other is to introduce a position attention network for information *** on three challenging benchmarks including GOT-10 k,UAV123 and OTB-100 demonstrate that our SiamPA achieves excellent tracking performance with a real-time speed.

关键词： Object tracking Siamese network Box-guided Position attention network

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Online adaptive Q-learning method for fully cooperative linear quadratic dynamic games

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Science China(Information Sciences) 2019年第12期62卷 164-177页

作者： Xinxing LI Zhihong PENG Lei JIAO Lele XI Junqi CAI School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

A model-based offline policy iteration(PI) algorithm and a model-free online Q-learning algorithm are proposed for solving fully cooperative linear quadratic dynamic games. The PI-based adaptive Q-learning method can learn the feedback Nash equilibrium online using the state samples generated by behavior policies, without sending inquiries to the system model. Unlike the existing Q-learning methods, this novel Q-learning algorithm executes both policy evaluation and policy improvement in an adaptive *** prove the convergence of the offline PI algorithm by proving its equivalence to Newton's method while solving the game algebraic Riccati equation(GARE). Furthermore, we prove that the proposed Q-learning method will converge to the Nash equilibrium under a small learning rate if the method satisfies certain persistence of excitation conditions, which can be easily met by suitable behavior policies. Our simulation results demonstrate the good performance of the proposed online adaptive Q-learning algorithm.

关键词： adaptive dynamic programming reinforcement learning Q-learning fully cooperative linear quadratic dynamic games policy iteration off-policy

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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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Further results on cloud control systems

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Science China(Information Sciences) 2016年第7期59卷 232-236页

作者： Yuanqing XIA Yongming QIN Di-Hua ZHAI Senchun CHAI School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

This paper is devoted to further investigating the cloud control systems(CCSs). The benefits and challenges of CCSs are provided. Both new research results of ours and some typical work made by other researchers are p... 详细信息

关键词： cloud control systems cloud computing cyber-physical systems networked control systems big data

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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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Consensus control of second-order stochastic discrete-time multi-agent systems without velocity transmission

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control Theory and Technology 2023年第4期21卷 591-601页

作者： Zi-Xuan Wang Xiaofeng Zong Ling-Jie Gai School of Automation China University of GeosciencesWuhan430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubeiChina Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhanHubeiChina

This article studies the almost-sure and the mean-square consensus control problems of second-order stochastic discrete-time multi-agent systems with multiplicative ***,a control law based on the absolute velocity and relative position information is ***,considering the existence of multiplicative noises and nonlinear terms with Lipschitz constants,the consensus control problem is solved through the use of a degenerated Lyapunov ***,for the linear second-order multi-agent systems,some explicit consensus conditions are ***,two sets of numerical simulations are performed.

关键词： Consensus control Multiplicative noises Second-order Discrete-time Multi-agent system

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