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Statistical Monitoring of chemical processes Based on Sensitive Kernel Principal Components

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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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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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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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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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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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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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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Automatic Sleep Stage Classification for Daytime Nap Based on Hopfield Neural Network

Automatic Sleep Stage Classification for Daytime Nap Based o...

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第25届中国控制与决策会议

作者： Xi Chen Bei Wang Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education School of Information Science and Engineering East China University of Science and Technology

ISBN: (纸本)9781467355339

In this study, automatic method of sleep stage classification for daytime nap is investigated. The ultimate objective is to identify the changing of sleep level during one's nap. The sleep data is recorded according to the polysomnographic (PSG) measurement. The Electroencephalograph (EEG) is analyzed for sleep stage classification. Totally, 4 parameters are selected and calculated for each 20-second segment of EEG data. The main method is based on Hopfield Neural Network (HNN). The neural network is trained by using standard mode. The sleep stages are classified based on HNN for each consecutive segment. The obtained result showed about 80.6% consistence comparing with the visual inspection. The automatic classification results indicated the changing of sleep level during nap, which can be useful for daytime nap sleep evaluation.

关键词： Sleep Stage Determination, Daytime Nap, EEG, Hopfield Neural Network

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Modeling and optimization for ethylene cracking furnace systems scheduling with consideration of changing feedstock

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Huagong Xuebao/CIESC Journal 2013年第12期64卷 4304-4312页

作者： Shang, Baopeng Du, Wenli Jin, Yangkun 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

An ethylene plant employs multiple cracking furnaces in parallel to convert various hydrocarbon feedstocks to smaller hydrocarbon molecules. The continuous operational performance of cracking furnaces gradually decays because of coke formation in the reaction coils, which requires each furnace to be periodically shut down for decoking. Given multiple feeds and different cracking furnaces as well as various product prices and manufacturing costs, the operational scheduling for the entire furnace system should be optimized to achieve the best economic performance. In this paper, a new MINLP(mixed-integer nonlinear programming) model is developed to obtain cyclic scheduling strategies for cracking furnace systems. Compared to previous studies, the new model has more capabilities to address operation profitability of multiple feeds cracked in multiple furnaces. Meanwhile, solving the problem of the choice for the right time of changing feedstock in the process of cracking furnace, case studies demonstrate the efficacy of the developed methodology. © All Rights Reserved.

关键词： Feedstocks

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