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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Ji, Zhanfeng Wang, Xingyu Sugi, Takenao Goto, Satoru Nakamura, Masatoshi Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai China Department of Advanced Systems Control Engineering Saga University Saga Japan Research Institute of Systems Control Saga University Saga Japan

ISBN: (纸本)9781424493524

Automatic EEG spike detection provide valuable information for diagnosis of epilepsy. In the past 30 years, a number of algorithms were proposed. However, the basic idea of most algorithms is to identify spike activities. We have developed an algorithm based on identify non-spike activities for off-line analysis. In this paper, we improved the algorithm for online application using real-time template. Template method is a typical spike detection method. It was not widely employed because of the difficulty of making template. Our results suggested that multi-channel template is meaningful and effective for real-time detection. Spike activities can be detected with a delay of about 2 s. We also designed an simple user-friendly monitor interface for monitor and review spike events in real-time. © 2011 IEEE.

关键词： multi-channel template real-time spike detection Spike spike spikes jigs(templates) Real time algorithms MONITOR analysis of flowline

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Explicit MPC for multi-rate control systems

Explicit MPC for multi-rate control systems

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作者： Jiang, Yali Zou, Yuanyuan Niu, Yugang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China

ISBN: (纸本)9780956715708

In this paper, explicit model predictive control (MPC) schemes for discrete-time linear-invariant multi-rate systems with constraints on inputs and states are studied. The optimization problem of multi-rate predictive control systems can be formulated by solving a multiparametric linear program (mp-LP), and the explicit state feedback control laws are developed. Further, based on the closed-loop multi-rate piecewise affine (PWA) structure, stability analysis is presented by linear matrix inequality (LMI). The simulation results show the effectiveness of the explicit MPC for multi-rate system. © 2011 Shanghai Jiaotong Univ.

关键词： Linear matrix inequalities

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Evolutionary algorithm based on the evolution of Pareto archive and individual migration

Evolutionary algorithm based on the evolution of Pareto arch...

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作者： Qi, Rongbin Ma, Tianyi Sun, Fan Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Shanghai Business School Shanghai China

An evolutionary algorithm based on the parallel evolution of multiple single objective populations and Pareto archive population is proposed, which is not only suitable for solving multi-objective optimization, but also effective for multimodal function. For each single objective population, single objective evolutionary algorithm is applied to optimize separately each of multi-objective functions, where individuals generated by tournament selection from the union of single objective and Pareto Archive population form the single objective population of next generation. Especially, individuals in Pareto archive population also join evolutionary operations. Simulations manifest that the proposed method can realize the search from multiple directions to obtain the non-dominated solutions scattered more uniformly over the Pareto frontier with better convergence metric compared to well-known NSGA-II algorithm. Individual migration from Pareto archive population by tournament selection is also proved to have the advantage in improving the converging speed and converging precision. Moreover, for multimodal single objective function, simulations also show that ideal optimizing solution can be obtained by properly separating single objective function into multi-objective function and applying the above method. © 2011 Zhejiang University.

关键词： Evolutionary algorithms

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Gross Error Detection and Data Reconciliation using Historical Data

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Procedia Engineering 2011年 15卷 55-59页

作者： Shaochao Sun Dao Huang Yanxue Gong Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Ecust shanghai 20037 China

With the information technology applied widely to process industry, a large amount of historical data which could be used for obtaining the prior probabilities of gross error occurrence is stored in database. To use the historical data to enhance the efficiency of gross error detection and data reconciliation, a new strategy which includes two steps is proposed. The first step is that mixed integer program technique is incorporated to use the prior information to detect gross errors. The second step is to estimate all detected gross errors and adjust process data with material, energy, and other balance constrains. In this step an improved method is proposed to achieve the same effect with traditional method through adjusting the covariance matrix. Novel prior information criteria are described and performance of this new strategy is compared and discussed by applying the strategy for a challenging test problem.

关键词： data rectification gross error detection mixed integer program projection matrix historical data

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Automatic spike detection based on real-time multi-channel template

Automatic spike detection based on real-time multi-channel t...

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2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

作者： Zhanfeng Ji Xingyu Wang Satoru Goto Masatoshi Nakamura Takenao Sugi Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Sc Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Sc Department of Advanced Systems Control Engineering Saga University Saga Japan

Automatic EEG spike detection provide valuable information for diagnosis of epilepsy. In the past 30 years, a number of algorithms were proposed. However, the basic idea of most algorithms is to identify spike activities. We have developed an algorithm based on identify non-spike activities for off-line analysis. In this paper, we improved the algorithm for online application using real-time template. Template method is a typical spike detection method. It was not widely employed because of the difficulty of making template. Our results suggested that multichannel template is meaningful and effective for real-time detection. Spike activities can be detected with a delay of about 2 s. We also designed an simple user-friendly monitor interface for monitor and review spike events in real-time.

关键词： spike detection real-time multi-channel template

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An application of the improved hybrid particle swarm optimization method in the gasoline blending process

An application of the improved hybrid particle swarm optimiz...

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International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011

作者： Shu, Yue Cheng, Hui Liu, Yi Qi, Rongbin Liu, Zhao 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 SinoPec Jinling Petrochemical Ltd. Nanjing 210033 China

In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline blending process. In addition, the proposed method has been applied onsite in a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the blending process and decrease the quality giveaways and blending cost significantly.

关键词： Genetic algorithms

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An adaptive optimal clustering number algorithm for FKCM

An adaptive optimal clustering number algorithm for FKCM

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2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Chen, Guihua Wang, Zhenlei Wang, Xin 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 Center of Electrical and Electronic Technology Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781612841816

In order to overcome the drawbacks of fuzzy kernel clustering method (FKCM) give the clustering number in advance, sensitive to the initial cluster centers and easy to be trapped into local optimum, the adaptive algorithm for optimal clustering number of FKCM (SAICFKCM) is proposed. The proposed method uses density-based algorithm to initialize cluster centers and kernel Xie-Beni validity index to determine the optimal number of categories, to achieve unsupervised fuzzy partition of data set. The simulation experiment and the classification of naphtha attribute data verify the feasibility and effectiveness of the proposed method. © 2011 IEEE.

关键词： Cluster analysis

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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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International Symposium on advanced control of Industrial Processes (ADCONIP)

作者： Fan Sun Na Luo Rongbin Qi Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Automatic Institute Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 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.

关键词： Inductors Mathematical model optimization Laboratories Kinetic theory Equations Production

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Real Time optimization of the Gasoline Blending Process with Unscented Kalman Filter

Real Time Optimization of the Gasoline Blending Process with...

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2011 International Conference on Internet Computing and Information Services （ICICIS 2011）

作者： Hui Cheng Weimin Zhong Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

Gasoline blending is a critical process in petroleum refineries. Real-time optimization(RTO) techniques have been popular with the applications for the blending process for optimization purpose. However the dependency of RTO on the measurement of the component impairs its applicability. Therefore how to utilize the blending model and the product measurement to free RTO from the component measurement is the major research topic in this paper. Unscented Kalman Filter, due to its ability to estimate the parameter for nonlinear model, is chosen to estimate component properties based on the product measurement. The RTO strategy is then proposed with the UKF method for the recipe calculation periodically. Furthermore, the proposed RTO is tested with the gasoline blending benchmark problem, while the results are compared with the ideal blending case. The accuracy of the component estimation and the efficiency of the RTO are verified with the results.

关键词： Gasoline Blending Unscented Kalman Filter Real-Time optimization(RTO)

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MPA EEG Model-based Vigilance Level Estimation by Artificial Neural Network

MPA EEG Model-based Vigilance Level Estimation by Artificial...

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2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

作者： Bei Wang Jiesen Wang Xingyu Wang Masatoshi Nakamura Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationSc Research Institute of Systems Control Institute for Advanced Research and Education Saga University

In this paper, the vigilance levels during day time short nap sleep were estimated on the basis of Markov Process Amplitude (MPA) EEG model. The ultimate purpose was to adopt the MPA model to discriminate three levels of vigilance through a simple neural network. A set of parameters were firstly calculated based on MPA EEG model. Secondly, correlation analysis was adopted to extract effective parameters to ensure a small amount of inputs of the artificial neural network. The outputs of artificial neural network were the classified three levels: wakeful, drowsy and sleep. The obtained estimation result showed that the accuracy of wakeful was about 90.0％, drowsy 80.0％, and sleep 93.3％.

关键词： MPA EEG model correlation analysis artificial neural network power spectrum

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