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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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A Hybrid Improved Genetic Algorithm and Its Application in Dynamic optimization Problems of chemical processes

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Chinese Journal of chemical Engineering 2013年第2期21卷 144-154页

作者： SUN Fan DU Wenli QI Rongbin QIAN Feng ZHONG Weimin Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature. 13enetic algorithm （GA） has been proved to be a teasibte method when the gradient is difficult to calculate. Its advantage is that the control profiles at all time stages are optimized simultaneously, but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum. In this study, a hybrid improved genetic algorithm （HIGA） for solving dynamic optimization problems is proposed to overcome these defects. Simplex method （SM） is used to perform the local search in the neighborhood of the optimal solution. By using SM, the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved. The hybrid algorithm presents some improvements, such as protecting the best individual, accepting immigrations, as well as employing adaptive crossover and Ganssian mutation operators. The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems. At last, HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable.

关键词： genetic algorithm simplex method dynamic optimization chemical process

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Hellinger Distance Based Probability Distribution Approach to Performance Monitoring of Nonlinear control Systems

Hellinger Distance Based Probability Distribution Approach t...

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第25届中国过程控制会议

作者： Chen Li Biao Huang Feng Qian Key Laboratory of Advanced Control and Optimization Ministry of Education East China University of Science and Technology Department of Chemical and Materials Engineering University of Alberta Edmonton Alberta T6G 2G6 Canada

control performance monitoring has attracted great attention in both academia and industry over the past two ***,most research efforts have been devoted to the performance monitoring of linear control systems,without considering the pervasive nonlinearities(*** stiction)which present in most industrial control *** this work,a novel probability distribution distance based index is proposed to monitor the performance of non-linear control *** proposed method uses Hellinger distance to evaluate change of control system *** simulation examples are given to illustrate effectiveness of the proposed method.

关键词： control performance monitoring,kernel density estimation,Hellinger distance,nonlinear system

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Modeling of batch process based on higher order partial least squares

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Huagong Xuebao/CIESC Journal 2014年第9期65卷 3527-3534页

作者： Wang, Jianping Hu, Yi Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai200237 China

The products of batch processes are closely related to the daily life of modern people, and it is crucial for batch process monitoring to establish a model based on the normal process data sets. In this paper, according to the characteristics of batch process, a new generalized multilinear regression model, termed the higher order partial least squares (HOPLS), is introduced with the aim to better model the three-way batch data. It differs substantially from the traditional modeling approach, and instead of unfolding the three-way array to a two-way array, it explains the data by a sum of orthogonal Tucker tensors. Higher order orthogonal iteration (HOSVD), tensor transformation and higher order orthogonal iteration (HOOI) are used to find the latent vectors, which contain the maximum information of independent variables and dependent variables simultaneously. And the loading vectors are calculated at the same time. For the new observation values, the dependent variables will be predicted through the output of the model. Finally, the feasibility and efficiency of the method are verified through the PenSim2.0 simulation platform. © All Rights Reserved

关键词： Tensors

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Separation model of Generalized Reference Curve Measurement for HPLC-DAD and it solution by multi-target Bare Bones Particle Swarm optimization

Separation model of Generalized Reference Curve Measurement ...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Lizhi Cui Josiah Poon Simon K. Poon Paul Kwan Junbin Gao Zhihao Ling School of Information Technologies The University of Sydney School of Science and Technology University of New England School of Computing and Mathematics Charles Sturt University Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781479956708

In order to separate the chromatogram peaks and spectra from the High Performance Liquid Chromatography with Diode Array Detector (HPLC-DAD) data set, a separation model of Generalized Reference Curve Measurement and its solution by multi-target Bare Bones Particle Swarm optimization (GRCMmBBPSO) is proposed in this paper. Firstly, parameters are constructed which will generate Reference Curves (RCs) for chromatogram peaks. Secondly, the GRCM model is proposed to transform all these parameters to scalar values, which indicate the possibility for the HPLC-DAD data set containing chromatogram peaks similar to the RCs constructed by corresponding parameters. Then, the algorithm of mBBPSO is introduced to calculate the optimal parameters by minimizing the scalar values. Finally, the spectra are estimated. Through simulations and experiments, following conclusions are drawn: (1) the GRCMmBBPSO method can extract chromatogram peaks from the simulation data set without knowing the number of the compounds in advance even when a severe overlap and white noise exist;(2) the GRCMmBBPSO method can be applied to real HPLC-DAD data set.

关键词： HPLC-DAD separation Generalized Reference Curve Measurement model Multi-target Bare Bones PSO algorithm

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Welding procedure expert system based on intelligent inference

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Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University 2014年 48卷 101-104页

作者： Wang, Xue-Wu Li, Yi-Xuan Yang, Shang-Yong Ding, Dong-Yan Gu, Xing-Sheng Key Laboratory of Advanced Control and Optimation for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China

Intelligent welding procedure expert system was developed to improve welding procedure selection for welding process in this paper. The expert system was designed based on Client/Server (C/S) mode, and the main functions include system management, knowledge base management, intelligent inference, remote access, etc. BP model and DEPSO based BP model were established to realize parameter estimation. Reasonable parameters can be derived based on the intelligent inference model and input welding condition. Obtained welding procedure can be presented as welding procedure card and multimedia display of welding process. Besides it, the output function makes the data share more convenient. The system is beneficial to welding parameters selection and welding engineer training. ©, 2014, Shanghai Jiao Tong University. All right reserved.

关键词： Neural networks

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Sliding mode control for T-S fuzzy stochastic systems with Markovian switching

Sliding mode control for T-S fuzzy stochastic systems with M...

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第三十三届中国控制会议

作者： Bei Chen Yugang Niu Tinggang Jia Central Academe Shanghai Electric Group Co.Ltd. Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education Automation Division Shanghai Electric Group Co.Ltd.

This paper is concerned with the sliding mode control(SMC)problem for a class of T-S fuzzy stochastic systems with Markovian *** purpose of the problem addressed is to integrate the SMC method such that,for all admissible parameter uncertainty,external disturbance and state-dependent noise,the closed-loop system is globally asymptotically ***,it is not required that each nominal local system model shares the same input channel,which is usually assumed in some existing *** is shown that both the reachability of sliding surfaces and the stability of sliding mode dynamics can be ensured.

关键词： Markovian jumping systems,State-dependent noise,T-S fuzzy model,Sliding mode control

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Distributed predictive control for energy management of multi-microgrids systems

Distributed predictive control for energy management of mult...

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13th IFAC Symposium on Large Scale Complex Systems: Theory and Applications, LSS 2013

作者： Xu, Jun Zou, Yuanyuan Niu, Yugang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China Univ. of Science and Technology Shanghai 200237 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China

In this paper, a distributed model predictive control (DMPC) scheme is presented to optimize the power flow management of microgrids in smart grid environment. For a multi-microgrids system in which local microgrid links with each other through particular channels for power and information, the proposed method can maximize the overall energy efficiency. The DMPC optimization problem is formulated by minimizing the surplus/insufficient energy in each microgrid and a constraint restriction is imposed to guarantee the closed-loop stability. A simulation example is carried out to demonstrate the feasibility and effectiveness of this energy management strategy. © IFAC.

关键词： Electric power distribution

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Three Stage Equilibrium Model for Coal Gasification in Entrained Flow Gasifiers Based on Aspen Plus

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Chinese Journal of chemical Engineering 2013年第1期21卷 79-84页

作者：孔祥东钟伟民杜文莉钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and Technology Automation Institute East China University of Science and Technology

A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas *** reaction stage. Part of the water produced in thepyrolysis and combust!on stag.e is assumed to be involved inthe second stage to react with the unburned carbon. Carbon conversion is then estimated in the second stage by steam participation ratio expressed as a function of temperature. And the gas product compositions are calculated from gas phase reactions in the third stage. The simulation results are consistent with published experimental data.

关键词： coal gasification Texaco gasifier equilibrium model carbon conversion product gas composition

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Novel control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic optimization of chemical processes

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Chinese Journal of chemical Engineering 2013年第1期21卷 64-71页

作者：孙帆钟伟民程辉钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and Technology Department of Automation East China University of Science and Technology

Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.

关键词： control vector pararneterization differential evolution algorithm dynamic optimization chemical processes

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