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World Congress on Intelligent control and Automation (WCICA)

作者： Tong Wang Jianbin Qiu Huijun Gao Jialu Fan Tianyou Chai Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China School of Information Bohai University Jinzhou China State Key Laboratory of Synthetical Automation of Process Industries Northeastern University Shenyang China

This paper investigates the output feedback control problem for a class of complex industrial processes in double-layer (upper operation layer and local device layer) network environment with radial basis function (RBF) performance index. First, sampled-data local plants at the device layer with sampling period T d are controlled by local output feedback proportional integral (PI) controllers. Then, the outputs and inputs of local plants are sampled at operation layer with sampling period T u to form the index prediction by using RBF neural networks. In addition, consider the effect of Ethernet between operation and device layer, a Bernoulli random binary distribution is employed to model the packet dropout phenomenon during data transmission. Furthermore, considering the nonlinearity of RBF neural networks, the Lagrange multipliers approach is utilized to solve the real time optimization (RTO) problem at operation layer and an output feedback compensator is designed to regulate the dynamic setpoints. Finally, a rougher flotation process model is employed to demonstrate the effectiveness of the proposed method.

关键词： Indexes Process control Optimization Output feedback Symmetric matrices Neurons Automation

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Optimal Tracking control for a Class of Continuous Time Complex-valued systems Based on Adaptive Dynamic Programming Algorithm

Optimal Tracking Control for a Class of Continuous Time Comp...

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第三十三届中国控制会议

作者： Ruizhuo Song Frank L.Lewis Qinglai Wei Wendong Xiao School of Automation and Electrical Engineering University of Science and Technology Beijing University of Texas at Arlington Research Institute University of Texas at Arlington State Key Laboratory of Synthetical Process Automation Northeastern University The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781479947249

Based on the adaptive dynamic programming(ADP) algorithm,a new optimal tracking control method is proposed for a class of complex-valued nonlinear systems in this *** tracking error is rst de ned,and then the performance index function which is about the tracking error is *** transformation,the complex-valued tracking error system is mapped into *** optimal control method for the tracking error system is *** two neural networks are used to be as the critic network and action network,*** is proven that the closed-loop system is uniformly ultimately bounded based on Lyapunov ***,the simulation study is given to show the effectiveness of the proposed optimal tracking control method for complex-valued nonlinear system.

关键词： Adaptive dynamic programming,optimal control,neural network,complex-valued

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Research on Multi-Dimensional Data Visualization Analysis of Large Enterprise's Purchasing Fund

Research on Multi-Dimensional Data Visualization Analysis of...

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Minhui Lv Hongxia Zhao School of Management Huazhong University of Science and Technology Department of Equipment Economics and Management Naval University of Engineering The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

With the continuous development of data storage technology,the complexity,category and size of data increase sharply;on the other hand,the wide expansion of its application domain brings great challenges on the traditional data processing and analysis *** this paper,the data analysis and processing technology and its development status are introduced and by multi-dimensional data visualization analysis method and combining the knowledge of domain experts,the equipment purchasing fund data of a large enterprise is analyzed to provide reliable management decision to the investment and investment volume of business fund.

关键词： data analysis data mining visualization corporate purchasing fund

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A Stochastic Model for Budget Distribution over Time in Search Advertisements

A Stochastic Model for Budget Distribution over Time in Sear...

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Rui Qin Yong Yuan Juanjuan Li Yanwu Yang The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences School of Management Huazhong University of Science and Technology

In search advertisements,advertisers have to seek for an effective allocation strategy to distribute the limited budget over a series of sequential temporal slots(e.g.,days).However,advertisers usually have no sufficient knowledge to determine the optimal budget for each temporal slot,because there exist much uncertainty in search advertising *** this paper,we present a stochastic model for budget distribution over a series of sequential temporal slots under a finite time horizon,assuming that the best budget is a random *** study some properties and feasible solutions for our model,taking the best budget being characterized by either normal distribution or uniform distribution,***,we also make some experiments to evaluate our model and identify strategies with the real-world data collected from practical advertising *** results show that a)our strategies outperform the baseline strategy that is commonly used in practice;b)the optimal budget is more likely to be normally distributed than uniformly distributed.

关键词： search advertisement budget distribution optimal budget stochastic programming budget constraint

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PI controller design for network control system based on minimum entropy control

PI controller design for network control system based on min...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Xinlan Guo Tao Li Hongxia Zhao Engineering Department Nanjing Communications Institute of Technology Nanjing Jiangsu Enterprise Custom Department Huawei Nanjing Institute Nanjing Jiangsu The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479960590

This paper designs PI controller which is easy to operate in an actual random framework for NCS, for nonlinear ARMAX model is difficult to achieve in the practical application. Based on the nature of the network control system is a random system and PI controller design is easy to operate in an actual random framework for NCS, the iterative learning ideas to batch control system output probability density function, so that the output probability density function of the system with increasing batch tracking a given probability density function. In order to achieve the NCS system of tracking error probability density function control, this paper introduces the minimum entropy control algorithm.

关键词： Entropy Robustness

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A signal split optimization approach based on model predictive control for large-scale urban traffic networks

A signal split optimization approach based on model predicti...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Ye, Bao-Lin Wu, Weimin Zhou, Xuanhao Mao, Weijie Li, Jixiong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou 310027 China Zhejiang SUPCON Software Co. Ltd. Hangzhou Zhejiang 310053 China

ISBN: (纸本)9781479915156

It is generally recognized that Model Predictive control (MPC) has many advantages in signal control of urban traffic networks. However, the computational complexity grows exponentially with the increase in network scale and predictive time horizon. In order to overcome this drawback, a signal split optimization approach is proposed in this paper, in which a large-scale traffic network was decomposed into a set of subnetworks. Based on the store-and-forward modeling paradigm, the optimization framework of each subnetwork is developed firstly. Then, Lagrange multipliers are employed to deal with interconnecting constraints among subnetworks, and the dual optimization problem corresponding to the whole network is constructed. Moreover, the dual optimization problem is optimized under a two-level optimization structure by interaction prediction approach. In the end, simulation experiments are given to illustrate the effectiveness of the proposed approach. © 2013 IEEE.

关键词： Model predictive control

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Improved stability and stabilization criteria of singular system with time-delay and parameter uncertainties

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Journal of Information and Computational Science 2013年第18期10卷 6067-6076页

作者： Ding, Yuanchun Weng, Falu Mao, Weijie School of Resources and Environmental Engineering Jiangxi University of Science and Technology Jiangxi 341000 China Faculty of Electrical Engineering and Automation Jiangxi University of Science and Technology Ganzhou Jiangxi 341000 China State Key Lab of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou 310027 China

The problems of delay-dependent robust stability and stabilization for continuously singular timedelay systems with norm-bounded uncertainties are investigated in this paper. Based on a Lyapunov functional, which includes some non-positive items, the modified delay-dependent LMIs-based conditions are established for the singular time-delay systems to be regular, impulse free, and stable. Then, by solving the obtained LMIs, the state-feedback control law can be obtained. These conditions are also extended to the uncertain case. Finally, numerical examples are given to illustrate that the proposed results are effective and less conservative than the existing ones. © 2013 Binary Information Press.

关键词： Time delay

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Analysis on Refinery System as a Complex Task-resource Network

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Chinese Journal of Chemical Engineering 2013年第3期21卷 253-262页

作者：刘苏昱荣冈 Department of Control Science and Engineering Institute of Cyber-System and Control State Key Laboratory ofIndustrial Control Technology Zhejiang University Hangzhou 310027 China

Refinery system, a typical example of process systems, is presented as complex network in this paper. The topology of this system is described by task-resource network and modeled as directed and weighted graph, in which nodes represent various tasks and edges denote the resources exchanged among tasks. Using the properties of node degree distribution, strength distribution and other weighted quantities, we demonstrate the heterogeneity of the network and point out the relation between structural characters of vertices and the functionality of correspond- ing tasks. The above phenomena indicate that the design requirements and principles of production process contrib- ute to the heterogeneous features of the network. Besides, betweenness centrality of nodes can be used as an impor- tance indicator to provide additional information for decision making. The correlations between structure and weighted properties are investigated to further address the influence brought by production schemes in system con- nectivity patterns. Cascading failures model is employed to analyze the robustness of the network when targeted at- tack happens. Two capacity assignment strategies are compared in order to improve the robustness of the network at certain cost. The refinery system displays more reliable behavior when the protecting strategy considers heteroge- neous properties. This phenomenon further implies the structure-activity relationship of the refinery system and provides insightful suggestions for process system design. The results also indicate that robustness analysis is a _promising applicat!on of methodologies from complex networks to process system engineering..

关键词： zomplex network refinery system structure-activity relationship heterogeneity robusmess

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A two-stage fuzzy budget allocation model in search auctions

A two-stage fuzzy budget allocation model in search auctions

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Rui Qin Yong Yuan Juanjuan Li The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479960590

Budget optimization is an important issue faced by advertisers in search auctions, and has significant impact on the design of various advertising strategies. Given a limited budget on a search market during a certain period, an advertiser has to distribute her budget to a series of sequential temporal slots (i.e., days, weeks, or months), during which advertisers must avoid the budget being used up quickly, so as to keep the budget for potential clicks with better performance in the future. Considering the optimal budgets over these temporal slots as fuzzy variables, we establish a two-stage fuzzy budget allocation model, and use particle swarm optimization (PSO) algorithm to solve it in case when these optimal budgets are characterized by discrete fuzzy variables. We also conduct experiments to validate our model and algorithm. The experimental results show that our model can outperform other five budget allocation strategies in terms of reducing the revenue loss of the advertiser.

关键词： Artificial intelligence

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A Glucose sensor based on glucose oxidase immobilized by electrospinning nanofibrous polymer membranes modified with carbon nanotubes

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Sensors and Transducers 2013年第5期152卷 180-185页

作者： Wang, You Xu, Hui Wang, Zhengang Hu, Ruifen Luo, Zhiyuan Xu, Zhikang Li, Guang National Laboratory of Industrial Control Technology Institute of Cyber-systems and Control Zhejiang University Hangzhou 310027 China Institute of Polymer Science Key Laboratory of Macromolecular Synthesis and Functionalization Zhejiang University Hangzhou 310027 China Computer Learning Research Centre Royal Holloway University of London Egham Surrey TW20 0EX United Kingdom

A glucose biosensor based on glucose oxidase immobilized by electrospinning nanofibrous membranes has been developed. Nanofibrous membranes were electrospun from the solution of poly(acrylonitrile-co-acrylic acid) containing carbon nanotubes suspension and directly deposited on Pt electrodes for immobilizing glucose oxidase. The morphologies and structure of the nanofibrous membranes with or without carbon nanotubes were characterized by scanning electron microscopy. The fabrication parameters of nanofibers were optimized such as thickness of the nanofibrous membranes and mass ration of carbon nanotubes. The biosensor showed the relationship with a concentration range of 0.1-10 mM and response time was 60 s. The sensitivity of carbon nanotubes modified biosensors was two times larger than which of no carbon nanotubes modified ones. The pH effect, interference and lifetime of biosensors were discussed. © 2013 by IFSA.

关键词： Electrospinning

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