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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Green Manufacturing Based on SDN

Green Manufacturing Based on SDN

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The 4th International Conference on Environmental technology and Knowledge Transfer

作者： TAI Deyi XU Fuyuan School of Management University of Shanghai for Science & Technology Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University

To realize an energy-saving and resource-sharing green manufacturing,a new cooperation model of green manufacturing based on supply and demand network of enterprises with multifunction and opening characteristics（SDN） was *** essential attribute of green manufacturing was *** with dynamic,diversity,fully open and inclusive cooperation concepts was introduced as a new paradigm of manufacturing *** model of green manufacturing cooperation based on SDN was proposed,from three-dimension of lever,function and ***,Green manufacturing for automobile enterprises based on SDN was discussed.

关键词： green manufacturing SDN manufacturing cooperation energy saving

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Lycopene Content Prediction Based on Support Vector machine with Particle Swarm Optimization

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Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural machinery 2012年第4期43卷 143-147+155页

作者： Liu, Wei Wang, Jianping Liu, Changhong Ying, Tiejin School of Electrical Engineering and Automation Hefei University of Technology Hefei 230009 China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University Hefei 230601 China School of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310058 China

Color-difference was presented to assess the lycopene content conveniently and non-destructively. Due to excessive affecting factors and strong correlation among the parameters in the process, the support vector machine (SVM) was used to set up the predict model. The selection and simplification of the feature parameters was discussed. A compound optimal objective function based on Akaike information criterion (AIC) was constructed. The particle swarm optimization (PSO) algorithm was used to search the optimal value of the objective function and enhance the efficiency. The predictable method had good performance in assessing the lycopene content of different maturity stages.

关键词： Support vector machines

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Design and implement of wireless measure and control system for greenhouse

Design and implement of wireless measure and control system ...

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作者： Du, Xiaodong Wang, Jun Ji, Ping Gan, Kaifeng Key Lab of Machine Vision and Intelligence Control Technology Hefei University Hefei 230601 China

ISBN: (纸本)9789881725592

With the rapid development of computer technology, MEMS technology, network technology, and so on, sensors are becoming miniaturization, intelligence, and integration, and has bring out a new networkWireless Sensor Networks(WSN). Based on the existent CAN-bus measure and control system which can achieve automatic measure and control of the greenhouse environment and nutrient solution in our lab, this paper studies wireless sensor networks, mainly including multifunctional wireless sensor nodes, wireless control nodes, main node, and system integration demonstration. We design and study the wireless sensor networks node's hardware platform deeply, consider low-power characteristics in node hardware and software design, analyze the consumption of the node generally and give out the corresponding energy-saving strategies supplied with solar power and battery, and compose star networks. The results of the experiment in the greenhouse environment show that the wireless sensor network will bring a lot of convenience for the greenhouse environment monitoring and control. © 2011 Chinese Assoc of Automati.

关键词： Solar energy

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Adaptive inverse optimal control for a class of nonlinear system

Adaptive inverse optimal control for a class of nonlinear sy...

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作者： Wang, Jun Ji, Ping Chu, Zhong Liu, Wei Key Lab of Machine Vision and Intelligence Control Technology Hefei University Hefei 230601 China

ISBN: (纸本)9789881725592

This paper introduces the basic idea of adaptive inverse optimal control, gives the solvable theorem of inverse optimal gain assignment problem, design inverse optimal controller using Backstepping algorithm and an adaptive update law for strict-feedback nonlinear continuous system with unknown time-varing bounded disturbance and constant unknown parameters, which is nonlinear, continuous and easier to realize. The adaptive control law and the parameter update laws can be obtained at the same time by this design scheme. The results designed show simultaneously that inverse optimal systems yield stability margins, namely, achieving locally robustness, which is a nonlinear analog of Kalman's margins for the linear quadratic regulator. © 2011 Chinese Assoc of Automati.

关键词： Adaptive control systems

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Research and design of mobile robot moving object tracking system on hierarchical control

Research and design of mobile robot moving object tracking s...

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2010 International Conference on Computer Application and System Modeling, ICCASM 2010

作者： Liuwei Tanmin Wang, Lian-Ping Zhang, Chongwei Wangjun School of Electrical Engineering and Automation Hefei University of Technology Hefei China Hefei University Key Laboratory of Machine Vision and Intelligence Control Technology Hefei China

ISBN: (纸本)9781424472369

A intelligent control model structure of double-level- three-stage is presented to deal with the moving robot detecting and tracking system. According to basic ideas of imitation of human intelligence control, it includes Decision-making level and Execution level, each level is decomposed into 3 stages. In the process of tracking, the moving objects state forecast and two-step increment tracking algorithm based on Kalman filter are adopted to drive the mobile robot quickly and smoothly. The robot system to detect and track moving objects with the model structure is designed and its application in automobile stake is illustrated. © 2010 IEEE.

关键词： Kalman filters

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Research and design of mobile robot moving object tracking system on hierarchical control

Research and design of mobile robot moving object tracking s...

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International Conference on Computer Application and System Modeling (ICCASM)

作者： Liu Wei Tanmin Jian-ping Wang Zhang chongwei Wang Jun School of Electrical Engineering and Automation Hefei University Key Laboratory of Machine Vision and Intelligence Control Technology Hefei China School of Electrical Engineering and Automation Hefei University of Technology Hefei China Hefei University Key Laboratory of Machine Vision and Intelligence Control Technology Hefei China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University Hefei China Hefei University Hefei CN

A intelligent control model structure of double-level-three-stage is presented to deal with the moving robot detecting and tracking system. According to basic ideas of imitation of human intelligence control, it includes Decision-making level and Execution level, each level is decomposed into 3 stages. In the process of tracking, the moving objects state forecast and two-step increment tracking algorithm based on Kalman filter are adopted to drive the mobile robot quickly and smoothly. The robot system to detect and track moving objects with the model structure is designed and its application in automobile stake is illustrated.

关键词： Image segmentation Image recognition Humans Robot kinematics

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Robust stabilization for uncertain singular Markovian jump systems

Robust stabilization for uncertain singular Markovian jump s...

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作者： Li, Yafeng Kang, Yu Hu, Yong Wang, Jun Department of Automation University of Science and Technology of China Hefei 230026 China Key Lab. of Machine Vision and Intelligence Control Technology Hefei University Hefei Anhui 230601 China

ISBN: (纸本)9787894631046

In this paper, the problems of robust stability and stabilization for singular Markovian jump systems with uncertainties are considered. In the system, the uncertainties are unknown time-varying but norm bounded. The system is transformed into an equivalent one by premultiplying and postmultiplying matrices. Sufficient conditions are given and the controllers are designed such that the system is regular, impulse-free and stochastically stable in mean square sense for the uncertainty. Finally, numerical examples are given to demonstrate the effectiveness of the proposed methods.

关键词： Stabilization

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PREDICTIVE control OF GREENHOUSE TEMPERATURE BASED ON MIXED LOGICAL DYNAMICAL SYSTEMS

PREDICTIVE CONTROL OF GREENHOUSE TEMPERATURE BASED ON MIXED ...

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World Automation Congress 2010

作者： LINLIN QIN CHUN SHI QING LING GANG WU JUN WANG XIAOJUN QIAO Department of Automation University of Science and Technology of China Machine Vision and Intelligence Control Technology Key Laboratory Hefei University National Engineering Research Center for Information Technology in Agriculture

Most of the greenhouse climate control equipments in China are on-off control and without displacement ***,modeling and control theories based on continuous control devices are not *** the other hand,conventional on-off control algorithms require frequent switch actions of equipments,which leads to equipment spoilage and energy *** address these issues,this paper proposes to control greenhouse climate using a hybrid system *** the interactive dynamics between the actions of ventilation window and the output of the control system（temperature）according to the value of inside temperature and operational constrains,the ventilation window temperature system in a greenhouse can be regarded as a hybrid dynamical *** addition to building models of greenhouse temperature,a model predictive control（MFC）algorithm of greenhouse air temperature is proposed for the mixed logical dynamical *** results in a greenhouse prove the effectiveness of our modeling and control algorithms.

关键词： air temperature system greenhouse hybrid systems mixed logical dynamical（MLD） systems model predictive control（MPC）

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Output-Feedback Robust Adaptive control for Strict-feedback Stochastic Nonlinear Systems under Inverse Optimality Costs

Output-Feedback Robust Adaptive Control for Strict-feedback ...

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The 22nd China control and Decision Conference(2010年中国控制与决策会议)

作者： Jingsheng Wang Jun Wang Wei Liu Ping Ji Key Lab. of Machine Vision and Intelligence Control Technology Hefei University Hefei 230022 P. R. China

The solvable problem of adaptive inverse optimal stabilization in probability is discussed, and control laws of global asymptotic stability in probability and adaptive inverse optimal stabilization in probability are developed for output-feedback stochastic nonlinear continuous systems with additive standard Wiener noises and constant unknown parameters by using It(o)'s differentiation rule and adaptive backstepping algorithms. The adaptive control law and the parameter update laws can be obtained at same time by this design scheme.

关键词： Output-feedback Wiener noises Backstepping algorithm Inverse optimality Stability in probability

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