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Octane model based on principal component analysis and neural network by near-infrared spectroscopy and its application in online gasoline blending process 3

Octane model based on principal component analysis and neura...

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3rd International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2013

作者： He, Kaixun Cheng, Hui Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

For the gasoline pipeline blending process, recipe optimization system is greatly dependent on the near-infrared spectroscopy online analyzer, whose spectral model plays an important role in the measurement. The sepectral model's accuracy and adaptability directly affect the applicability of the entire online blending system. This paper studies how to establish model for gasoline octane number for the gasoline pipeline blending process with near-infrared spectroscopy online analyzer. It is proposed using principal component analysis (PCA) together with Artificial Neural Network (ANN) method to establish spectral-model for octane number. Multivariate linear regressions(MLR) and partial least squares (PLS) method have also been used to establish gasoline octane model for comparison purpose. The results show that the model established by PCA and ANN has strong anti-jamming capability and suitable for gasoline online blending application.

关键词： Principal component analysis

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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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Improved performance of process monitoring based on selection of key principal components

Improved performance of process monitoring based on selectio...

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作者： Song, Bing Ma, Yuxin Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai200237 China

Conventional principal component analysis (PCA) can obtain low-dimensional representations of original data space, but the selection of principal components (PCs) based on variance is subjective, which may lead to information loss and poor monitoring performance. To address dimension reduction and information preservation simultaneously, this paper proposes a novel PC selection scheme named full variable expression. On the basis of the proposed relevance of variables with each principal component, key principal components can be determined. All the key principal components serve as a low-dimensional representation of the entire original variables, preserving the information of original data space without information loss. A squared Mahalanobis distance, which is introduced as the monitoring statistic, is calculated directly in the key principal component space for fault detection. To test the modeling and monitoring performance of the proposed method, a numerical example and the Tennessee Eastman benchmark are used. © 2015 Elsevier B.V.

关键词： Principal component analysis

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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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Simulation and Analysis on Multiple Steady States of an Industrial Acetic Acid Dehydration System

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Chinese Journal of chemical Engineering 2011年第6期19卷 983-989页

作者：李绍军黄定伟 Key Laboratory of Advanced Control and Optimization for Chemical Processes （East China University of Science and Technology） Ministry of Education Shanghai 200237 China

In this work, an industrial acetic acid dehydration system via heterogeneous azeotropic distillation is simulated by Aspen Plus software. Residue curves are used to analyze the distillating behavior, and appropriate operating region of the system is determined. Based on steady states simulation, a sensitivity analysis is carried out to detect the output multiple steady states in the system. Different solution branches are observered when the flow rates of the feed stream and the organic reflux stream are selected as manipulated variables. The performance of the column under different steady states is different. A method is oroposed to achieve the desired steady state.

关键词： acetic acid dehydration heterogeneous azeotropic distillation residue curve multiple-steady states

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Introducing Robustness in controllability of Neuronal Networks 34

Introducing Robustness in Controllability of Neuronal Networ...

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第三十四届中国控制会议

作者： TANG Yang DU Wei The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology The Institute of Textiles and Clothing The Hong Kong Polytechnic University

ISBN: (纸本)9781467374439

This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain,in which uncertainties in determination of driver nodes and control gains are considered. A framework by including interval uncertainties is proposed for robust controllability. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affect the controllability of neuronal networks.

关键词： Synchronization,Neuronal networks,controllability,Robustness,Multiobjective optimization

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