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Communications in Computer and Information Science 2013年 355卷 221-229页

作者： Xu, Wei Wang, Raofen Gu, Xingsheng Sun, Youxian State Key Laboratory of Industrial Control Technology Zhejiang University 310027 Hangzhou China Department of Automation Shanghai University of Engineering Science 201620 Shanghai China Key Laboratory of Advanced Control Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology 200237 Shanghai China

Quantum neural computing has nowadays attracted much attention, and tends to be a candidate to improve the computational efficiency of neural networks. In this paper, a new quantum neural network (QNN) is proposed based on quantum mechanics of superposition and collapse, etc. Instead of gradient descent methods and evolutionary algorithms, extreme learning machine (ELM) is introduced to analytically identify the parameters of the QNN. The ELM-QNN model is applied to the online and real-time assessment of the syngas components in a Texaco gasification process. The application would effectively avoid the problems of time delay and low accuracy which result from the manual analysis. In order to eliminate the redundant information stored in variables, principal component analysis (PCA) is adopted to reduce the number of input variables of ELM-QNN. The results indicate that ELMQNN combined with PCA method has satisfied computational accuracy and efficiency. The PCA-ELM-QNN is very capable of being used for the real-time measurement of Texaco syngas components. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Principal component analysis

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Fast consensus of directed network via optimal pinning control

Fast consensus of directed network via optimal pinning contr...

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第三十二届中国控制会议

作者： YANG Wen WANG Ying WANG Xiaofan Key Laboratory of Advanced Control and Optimization for Chemical Processes(East China University of Science and Technology) Ministry of Education Department of Automation Shanghai Jiaotong University

ISBN: (纸本)9781479900305

In this paper,we consider fast and desired consensus of directed network via pinning ***,we provide a sufficient condition for the stability of desired consensus ***,we investigate the problem of selecting optimal pinned nodes for driving fastest consensus,which is formulated as an Mixed-Integer Semidefinite ***,we illustrate all the results by simulating on some typical directed networks.

关键词： Node selection Fast consensus Convex optimization

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Synchronization of Kuramoto Oscillators with Non-identical Natural Frequencies: a Quantum Dynamical Decoupling Approach

Synchronization of Kuramoto Oscillators with Non-identical N...

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IEEE Annual Conference on Decision and control

作者： Zhifei Zhang Alain Sarlette Zhihao Ling SYSTeMS research group Faculty of Engineering and Architecture Ghent University Technologiepark Zwijnaarde 914 9052 Zwijnaarde(Ghent) Belgium Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology No.130 Meilong Road Shanghai 200237 China

ISBN: (纸本)9781467360890

This paper proposes a method to counter the drift associated to unknown non-identical natural frequencies in the Kuramoto model of coupled oscillators. Inspired by the quantum dynamical decoupling technique, it builds on a time-varying variant of the dynamics to effectively bring the oscillator phases closer to the same value. This allows effective synchronization despite arbitrarily large differences in natural frequencies. For two agents admitting instantaneous position exchanges, we exactly compute how the relative phase converges to a stable periodic fixed point. The latter tends to zero when the dynamics switches at a faster rate. With continuous state evolutions, using a related dynamic controller instead of instantaneous jumps, we show with a Lyapunov function that exact phase synchronization is obtained. We generalize the method to multiple oscillators with instantaneous state exchanges, that can be implemented by cycling through a predefined or random sequence of exchanges. Simulation results illustrate the effectiveness of the algorithms.

关键词： Natural frequencies Oscillators DECOUPLING phase synchronization coupled oscillators dynamics quanta

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Fixed-Time Consensus for Multi-Agent Systems Under Directed and Switching Interaction Topology

Fixed-Time Consensus for Multi-Agent Systems Under Directed ...

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American control Conference

作者： Zongyu Zuo Wen Yang Lin Tie Deyuan Meng The Seventh Research Division Beihang University (BUAA) Beijing 100191 China Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China School of Automation Science and Electrical Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479932757

In this paper, we address the fixed-time consensus problem for multi-agent systems in networks with directed and switching interaction topology. With the introduction of mirror operation, two global distributed nonlinear consensus protocols are constructed for each first-order agent under strongly connected information flow. The distinctive feature of this paper is to address the explicit bounds of the finite settling time for both protocols are independent of initial condition, which makes it possible for network consensus problems of a multi-agent team with guaranteed convergence time. Further, the second protocol is valid for the networks of multi-agents with switching topology provided that the sum of time intervals, in which the information flow is strongly connected, is larger than the estimated upper-bound for settling time. Finally, simulations are provided to demonstrate the performance and effectiveness of our theoretical results.

关键词： Protocols Switches Topology Multi-agent systems Network topology Convergence Eigenvalues and eigenfunctions

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Statistical Monitoring of Chemical Processes Based on Sensitive Kernel Principal Components

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Chinese Journal of Chemical Engineering 2013年第6期21卷 633-643页

作者： JIANG Qingchao YAN Xuefeng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education EastChina University of Science and Technology Shanghai 200237 China

The kernel principal component analysis （KPCA） method employs the first several kernel principal components （KPCs）, which indicate the most variance information of normal observations for process monitoring, but may not reflect the fault information. In this study, sensitive kernel principal component analysis （SKPCA） is proposed to improve process monitoring performance, i.e., to deal with the discordance of T2 statistic and squared prediction error SVE statistic and reduce missed detection rates. T2 statistic can be used to measure the variation di rectly along each KPC and analyze the detection performance as well as capture the most useful information in a process. With the calculation of the change rate of T2 statistic along each KPC, SKPCA selects the sensitive kernel principal components for process monitoring. A simulated simple system and Tennessee Eastman process are employed to demonstrate the efficiency of SKPCA on online monitoring. The results indicate that the monitoring performance is improved significantly.

关键词： statistical process monitoring kernel principal component analysis sensitive kernel principal compo-nent Tennessee Eastman process

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Research on electromagnetic coupling artificial neural network with spatial topology

Research on electromagnetic coupling artificial neural netwo...

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6th International Conference on Brain Inspired Cognitive Systems, BICS 2013

作者： Wang, Ziyin Liu, Mandan Ren, Xiang Cheng, Yicheng Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai 200237 China

ISBN: (纸本)9783642387852

In this paper, an emerging artificial neural network (ECANN) is proposed. Abstracting from a latest research in neuroscience, electromagnetic coupling among neuron activities is introduced into the model. Besides, the overall network can be viewed as a system with physical significance of circuitry, and each neuron is presented as differential equation. At the mean time, the spatial grid topology is employed in order to develop its parallelism. This artificial neural network is designed for fitting and predicting dynamic data, and has successfully worked in simulation part of this paper. © 2013 Springer-Verlag.

关键词： Neural networks

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Fault Diagnosis in Chemical Process Based on Self-organizing Map Integrated with Fisher Discriminant Analysis

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Chinese Journal of Chemical Engineering 2013年第4期21卷 382-387页

作者：陈心怡颜学峰 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education EastChina University of Science and Technology Shanghai 200237 China

Fault diagnosis and monitoring are very important for complex chemical process. There are numerous methods that have been studied in this field, in which the effective visualization method is still challenging. In order to get a better visualization effect, a novel fault diagnosis method which combines self-organizing map (SOM) with Fisher discriminant analysis (FDA) is proposed. FDA can reduce the dimension of the data in terms of maximizing the separability of the classes. After feature extraction by FDA, SOM can distinguish the different states on the output map clearly and it can also be employed to monitor abnormal states. Tennessee Eastman (TE) process is employed to illustrate the fault diagnosis and monitoring performance of the proposed method. The result shows that the SOM integrated with FDA method is efficient and capable for real-time monitoring and fault diagnosis in complex chemical process.

关键词： self-organizing maps Fisher discriminant analysis fault diagnosis monitoring Tennessee Eastman process

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A Hybrid Algorithm Based on Differential Evolution and Group Search optimization and Its Application on Ethylene Cracking Furnace

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Chinese Journal of Chemical Engineering 2013年第5期21卷 537-543页

作者：年笑宇王振雷钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes (l~Iinistry of Education) East ChinaUniversity of Science and Technology Shanghai 200237 China

To find the optimal operational condition when the properties of feedstock changes in the cracking furnace online,a hybrid algorithm named differential evolution group search optimization(DEGSO) is proposed,which is based on the differential evolution(DE) and the group search optimization(GSO).The DEGSO combines the advantages of the two algorithms:the high computing speed of DE and the good performance of the GSO for preventing the best particle from converging to local optimum.A cooperative method is also proposed for switching between these two *** the fitness value of one algorithm keeps invariant in several generations and less than the preset threshold,it is considered to fall into the local optimization and the other algorithm is *** on benchmark functions show that the hybrid algorithm outperforms GSO in accuracy,global searching ability and *** optimization of ethylene and propylene yields is illustrated as a case by *** optimization,the yield of ethylene and propylene is increased remarkably,which provides the proper operational condition of the ethylene cracking furnace.

关键词： group search optimization differential evolution ethylene and propylene yields cracking furnace

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Modeling and optimization of the Steam Turbine Network of an Ethylene Plant

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Chinese Journal of Chemical Engineering 2013年第5期21卷 520-528页

作者：李泽秋赵亮杜文莉钱锋 Key Laboratory of Advanced Control and Optimization for chemical Process (hTlinistry of t~ducation) East ChinaUniversity of Science and Technology Shanghai 200237 China

In this paper,we developed a hybrid model for the steam turbines of a utility system,which combines an improved neural network model with the thermodynamic ***,a nonlinear programming(NLP) model of the steam turbine network is formulated by utilizing the developed steam turbine models to minimize the total steam cost for the whole steam turbine ***,this model is applied to optimize the steam turbine network of an ethylene *** obtained results demonstrate that this hybrid model can accurately estimate and evaluate the performance of steam turbines,and the significant cost savings can be made by optimizing the steam turbine network operation at no capital cost.

关键词： hybrid model steam turbine network utility system economic objective

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Isobaric Vapor-Liquid Equilibrium of Binary Systems： p-Xylene ＋（Acetic Acid, Methyl Acetate and n-Propyl Acetate） and Methyl Acetate ＋ n-Propyl Acetate in an Acetic Acid Dehydration Process

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Chinese Journal of Chemical Engineering 2013年第2期21卷 171-176页

作者： HUANG Xiuhui ZHONG Weimin PENG Changjun QIAN Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The vapor-liquid equilibrium data of four binary systems (acetic acid +p-xylene, methyl acetate +n-propyl acetate, n-propyl acetate +p-xylene and methyl acetate +p-xylene) are measured at 101.33 kPa with Ellis equilibrium still, and then both the NRTL and UNIQUAC models are used in combination with the HOC model for correlating and estimating the vapor-liquid equilibrium of these four binary systems. The estimated binary VLE results using correlated parameters agree well with the measured data except the methyl acetate +p-xylene system which easily causes bumping and liquid rushing out of the sampling tap due to their dramatically different boiling points. The correlation results by NRTL and UNIQUAC models have little difference on the average absolute deviations of temperature and composition of vapor phase, and the results by NRTL model are slightly better than those by UNIQUAC model except for the methyl acetate +n-propyl acetate system, for which the latter gives more accurate correlations.

关键词： vapor-liquid equilibrium p-xylene acetic acid methyl acetate n-propyl acetate parameter correlation

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