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作者： Wang, Lina Cao, Cuiwen Xu, Zhenhao Gu, Xingsheng 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)9783642277078

This paper develops an improved particle swarm optimization algorithm based on cultural algorithm for constrained optimization problems. Firstly, chaos method is utilized in the initialization process of single swarm in population space to assure the searching breadth, and evolves with standard particle swarm optimization (PSO). Secondly, fixed proportion elites are selected from population space to construct the swarm of belief space through acceptance function. Then, the belief space updates its normative knowledge and situational knowledge according to the elite particles, and the elite-swarm in the belief space performs PSO operation according to the update knowledge and generates new particles. After that, the belief space renews the knowledge again, and passes down the new knowledge which has been updated twice to give better guidance to all the particles in the population space. The efficiency of the initialization strategy and the double evolving knowledge strategy are verified in six constrained optimization problems. © 2012 Springer-Verlag GmbH Berlin Heidelberg.

关键词： Constrained optimization

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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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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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Second Level Adaptive control Based on Combination Multiple Model 29

Second Level Adaptive Control Based on Combination Multiple ...

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第29届中国控制与决策会议

作者： Yong Chen Xin Wang Zhenlei Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Center of Electrical and Electronic Technology Shanghai Jiao Tong University

ISBN: (纸本)9781509046584

Since all of adaptive models converge to the same point in parameter space,classical second level multiple model adaptive control method cannot deal with linear time-varying *** order to deal with this drawback,this paper proposes a modified second level adaptive control method based on combining the advantages of adaptive model and fixed model for a class linear discrete time-varying plant where only a little prior information which is ***,multiple adaptive models are selected in the space of parameters,and the parameters are identifying and the controller is designed based on second level adaptive ***,when one of sub-model of the adaptive models are closed to the real parameters of the system,all of these adaptive models are fixed,and then the controller is designed based on multiple fixed ***,simulations have demonstrated that this method is effectively to a class of linear time-varying system.

关键词： adaptive model fixed model second level adaptive control multi-model

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Plant-wide optimization for high value added products - A steam cracking case study 30

Plant-wide optimization for high value added products - A st...

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30th Ethylene Producers Conference 2018 - Topical Conference at the 2018 AIChE Spring Meeting and 14th Global Congress on Process Safety

作者： Van Geem, Kevin M. Marin, Guy B. Muñoz, Andrés E.G. Zhang, Yu Du, Wenli Qian, Feng Laboratory for Chemical Technology Ghent University Belgium AVGI Syria Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology China

ISBN: (纸本)9781510864375

Recent progress in accurate modeling of steam cracking plants has enabled global optimization to be performed at a plant-wide level. This paper presents a real time optimization (RTO) system developed by East China University of Science and Technology (ECUST) to maximize the net profit of the ethylene plant of Sinopec Shanghai Petrochemical Company (SSPC). The system has a three-layer structure consisting of the global RTO, the local RTO and the advanced process control (APC) layer from top to bottom, among which the APC layer has already been applied to SSPC and is currently in service. COILSIM1D-RTO is used to simulate the steam cracking reactors. A simplified radiant box model and a convection section model are developed to account for the fuel consumption and superheated high pressure steam generation. The downstream compression and separation units are modeled in Aspen Plus to evaluate the maximum allowed process gas load and energy consumption. As the plant-wide RTO system is currently under implementation and no real time optimization results can be obtained, a case study is performed using historical operating data from year 2017 to illustrate the benefit that this plantwide RTO system can deliver. optimization results show that most of the crackers should be operated under higher cracking severity to improve yields of the high value added products. By optimizing the cracking severity and dilution steam ratio, the estimated increase of net profit of the ethylene plant in Case 1 and Case 2 is about 29.50 million and 30.75 million yuan per year, respectively (i.e. approx. 4.7 million USD and 4.9 million USD, at current exchange rates). Copyright © American Institute Of chemical Engineers. All rights reserved.

关键词： Global optimization

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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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Enhancing the Performance of JADE Using Two-phase Parameter control Scheme and Its Application

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International Journal of Automation and computing 2018年第4期15卷 462-473页

作者： Qin-Qin Fan Yi-Lian Zhang Xue-Feng Yan Zhi-Huan Wang Logistics Research Center Shanghai Maritime UniversityShanghai 201306China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237China Key Laboratory of Marine Technology and Control Engineering Ministry of Communications Shanghai Maritime UniversityShanghai 201306China

The search efficiency of differential evolution （DE） algorithm is greatly impacted by its control parameters. Although many adaptation/self-adaptation techniques can automatically find suitable control parameters for the DE, most techniques are based on pop- ulation information which may be misleading in solving complex optimization problems. Therefore, a self-adaptive DE （i.e., JADE） using two-phase parameter control scheme （TPC-JADE） is proposed to enhance the performance of DE in the current study. In the TPC-JADE, an adaptation technique is utilized to generate the control parameters in the early population evolution, and a well-known empirical guideline is used to update the control parameters in the later evolution stages. The TPC-JADE is compared with four state-of-the-art DE variants on two famous test suites （i.e., IEEE CEC2005 and IEEE CEC2015）. Results indicate that the overall performance of the TPC-JADE is better than that of the other compared algorithms. In addition, the proposed algorithm is utilized to obtain optimal nutrient and inducer feeding for the Lee-Ramirez bioreactor. Experimental results show that the TPC-JADE can perform well on an actual dynamic optimization problem.

关键词： Differential evolution(DE)algorithm evolutionary computation dynamic optimization control parameter adaptation chemical processes.

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Performance and Implementations of Vibrotactile Brain-Computer Interface with Ipsilateral and Bilateral Stimuli

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Journal of Donghua University(English Edition) 2018年第6期35卷 439-445页

作者： SUN Hongyan JIN Jing ZHANG Yu WANG Bei WANG Xingyu Key Laboratory of Advanced Control and Optmization for Chemical Processes East China University of Science and Technology

The tactile P300 brain-computer interface( BCI) is related to the somatosensory perception and response of the human brain,and is different from visual or audio BCIs. Recently,several studies focused on the tactile stimuli delivered to different parts of the human body. Most of these stimuli were symmetrically *** a fewstudies explored the influence of tactile stimuli *** the current study,we extensively tested the performance of a vibrotactile BCI system using ipsilateral stimuli and bilateral *** vibrotactile P300-based paradigms were tested. The target stimuli were located on the left and right forearms for the left forearm and right forearm( LFRF) paradigm,and on the left forearm and calf for the left forearm and left calf( LFLC)paradigm. Ten healthy subjects participated in this study. Our experiments and analysis showed that the bilateral paradigm( LFRF) elicited larger P300 amplitude and achieved significantly higher classification accuracy than the ipsilateral paradigm( LFLC). However, both paradigms achieved classification accuracies higher than 70% after the completion of several trials on average,which was usually regarded as the minimum accuracy level required for BCI system to be deemed useful.

关键词： brain-computer interface (BCI) tactile P300 ipsilateral stimuli bilateral stimuli paradigm left forearm right forearm left calf

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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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2014 American control Conference, ACC 2014

作者： Zuo, Zongyu Yang, Wen Tie, Lin Meng, Deyuan Beijing 100191 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai 200237 China Beijing 100191 China

ISBN: (纸本)9781479932726

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. © 2014 American Automatic control Council.

关键词： Multi agent systems

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Research on industrial modeling of ethylene oxide hydration reactor

Research on industrial modeling of ethylene oxide hydration ...

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作者： Sun, Fan Luo, Na Qi, Rongbin 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 Automatic Institute Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China

Focusing on ethylene oxide (EO) hydration reactor industrial equipment, the reaction mechanism model is established. Based on the principle of material balance, energy balance and kinetics of the reactions of ethylene oxide with water, partial least squares regression (PLSR) was used in the model to establish a corresponding relationship between the reaction rate constant and the reaction temperature. With kinetic parameters correction by using field data, the results are more tallies with the actual operation. Influences of water/EO molar ratio and inlet temperature on product quality, outlet temperature and energy consumption are analyzed according to the established model. The results showed that the model can preferably reflect the performance of EO hydration reactor and have certain guidance functions to the further advanced control strategies. © 2011 Zhejiang University.

关键词： Hydration

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