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IEEE International Conference on Computer and Communications, ICCC 2015

作者： Wang, Haiqiang Zhang, Yu Jin, Jing Wang, Xingyu Key Laboratory for Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology China

ISBN: (纸本)9781467381253

Until now, the canonical correlation analysis (CCA)-based method has been most widely applied to steady-state visual evoked potential (SSVEP). Artificial sine-cosine signals are used as the original references in the CCA method, which could hardly reflect the real SSVEP features buried in electroencephalogram (EEG). In this study, we use principal component analysis (PCA) to extract EEG features multivariate linear regression (MLR) is implemented on EEG and the specific sample labels. Experimental results show that the proposed MLR method outperformed other two competing methods for SSVEP recognition, especially in short time window. © 2015 IEEE.

关键词： Brain computer interface

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Strategy of changing cracking furnace feedstock based on improved group search optimization

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Chinese Journal of chemical Engineering 2015年第1期23卷 181-191页

作者：年笑宇王振雷钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education

The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the "excellent" infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained.

关键词： Cracking furnace Scheduling of feedstock Group search optimizer Adaptive penalty function Double fitness values

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Activated sludge model parameters calibration based on multi-objective PSO

Activated sludge model parameters calibration based on multi...

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International Conference on Environmental Engineering and Computer Application, ICEECA 2014

作者： Wang, R.R. Cao, L.L. Liu, M.D. Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology China

ISBN: (纸本)9781138028074

The model of an Orbal oxidation ditch activated sludge process was set up based on ASM3 and Takacs’s double index settlement rate of secondary sedimentation tank model in this paper. According to the condition of the multi-objective output simulation model, multi-objective particle swarm optimization algorithm (MOPSO) is used to calibrate part of the high sensitivity parameters in the activated sludge process model. Simulation results show that the effectiveness of MOPSO for parameter calibration is obvious, which can further improve the accuracy of the model. © 2015 Taylor & Francis Group, London.

关键词： Activated sludge process

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An aligned mixture probabilistic principal component analysis for fault detection of multimode chemical processes

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Chinese Journal of chemical Engineering 2015年第8期23卷 1357-1363页

作者：杨雅伟马玉鑫宋冰侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.

关键词： Multimode process monitoring Mixture probabilistic principal component analysis Model alignment Fault detection

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A hybrid specific index-related process monitoring strategy based on a novel two-step information extraction method

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Journal of Central South University 2018年第12期25卷 2896-2909页

作者： ZHAO Bo SONG Bing TAN Shuai SHI Hong-bo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

A two-step information extraction method is presented to capture the specific index-related information more *** the first step,the overall process variables are separated into two sets based on Pearson correlation *** is process variables strongly related to the specific index and the other is process variables weakly related to the specific *** performing principal component analysis(PCA)on the two sets,the directions of latent variables have *** other words,the correlation between latent variables in the set with strong correlation and the specific index may become ***,the correlation between latent variables in the set with weak correlation and the specific index may be *** the second step,the two sets are further divided into a subset strongly related to the specific index and a subset weakly related to the specific index from the perspective of latent variables using Pearson correlation coefficient,*** subsets strongly related to the specific index form a new subspace related to the specific ***,a hybrid monitoring strategy based on predicted specific index using partial least squares(PLS)and T2statistics-based method is proposed for specific index-related process monitoring using comprehensive *** specific index reflects real-time information for the specific index.T2statistics are used to monitor specific index-related ***,the proposed method is applied to Tennessee Eastman(TE).The results indicate the effectiveness of the proposed method.

关键词： specific index hybrid monitoring strategy two-step information extraction subspace

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High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

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Chinese Journal of chemical Engineering 2015年第9期23卷 1509-1517页

作者：田颖杜文莉钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

Purified terephthalic acid(PTA) is an important chemical raw material. P-xylene(PX) is transformed to terephthalic acid(TA) through oxidation process and TA is refined to produce PTA. The PX oxidation reaction is a complex process involving three-phase reaction of gas, liquid and solid. To monitor the process and to improve the product quality, as well as to visualize the fault type clearly, a fault diagnosis method based on selforganizing map(SOM) and high dimensional feature extraction method, local tangent space alignment(LTSA),is proposed. In this method, LTSA can reduce the dimension and keep the topology information simultaneously,and SOM distinguishes various states on the output map. Monitoring results of PX oxidation reaction process indicate that the LTSA–SOM can well detect and visualize the fault type.

关键词： Self-organizing map Local tangent space alignment Fault diagnosis Visualization P-xylene oxidation

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Soft Sensor for Ammonia Concentration at the Ammonia Converter Outlet Based on an Improved Group Search optimization and BP Neural Network

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Chinese Journal of chemical Engineering 2012年第6期20卷 1184-1190页

作者：阎兴頔杨文马贺贺侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

The ammonia synthesis reactor is the core unit in the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects directly the production efficiency. However, it is hard to be measured reliably online in real applications. In this paper, a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration. A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN. GSO-NH is integrated with BPNN to build a soft sensor model. Finally, the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application. Three other modeling methods are applied for comparison with GSO-NH-NN. The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy. Moreover, the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.

关键词： ammonia synthesis ammonia concentration soft sensor group search optimization

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Furnace firing control: The key to extending your run length 27

Furnace firing control: The key to extending your run length

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27th Ethylene Producers Conference 2015 - Topical Conference at the 2015 AIChE Spring Meeting and 11th Global Congress on process Safety

作者： Vervust, Alexander J. Zhang, Yu Qian, Feng Reyniers, Pieter A. Schietekat, Carl M. Van Geem, Kevin M. Marin, Guy B. Laboratory for Chemical Technology Ghent University Belgium Key Laboratory of Advanced Control and Optimization East China University of Science and Technology China

ISBN: (纸本)9781510806924

control and regulation of furnace firing is essential to extend the runiength of new and existing furnaces. Accurate Computational Fluid Dynamic simulations of the furnace are essential for this purpose. This requires among others accounting for the detailed geometry of the burners. Also the so-called "shadow effect" 6 arising from the projected shadows between adjacent reactors leads to significant heat flux non-uniformities. This phenomenon is important but its effect on product yields is often ignored as only a single reactor is simulated. For the USC furnace simulated in this work, shadow effects cause a maximum difference in COT of 29 K and a difference in P/E-ratioof 0.1 between two different U-coils in the furnace. In order to obtain more uniform TMT's, COTs and olefin yields for the individual reactors, different furnace optimization methods were compared and their results are discussed. Full furnace CFD simulations prove to be essential in design and during debottlenecking, when aiming for a more uniform COT distribution to the reactors by fuel distribution.

关键词： Furnaces

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Multimode process Monitoring Based on Fuzzy C-means in Locality Preserving Projection Subspace

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Chinese Journal of chemical Engineering 2012年第6期20卷 1174-1179页

作者：解翔侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of Education

For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring strategy based on fuzzy C-means. The high dimensional historical data are transferred to a low dimensional subspace spanned by locality preserving projection. Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operational mode. The distance statistics of each cluster are integrated though the membership values into a novel BID (Bayesian inference distance) monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman benchmark process.

关键词： multimode process monitoring fuzzy C-means locality preserving projection integrated monitoring index Tennessee Eastman process

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Containment control for the Cooperative Output Regulation of Linear Multi-Agent Systems

Containment Control for the Cooperative Output Regulation of...

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第三十二届中国控制会议

作者： SHEN Yanchao YAN Huaicheng ZHANG Hao SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and Engineering East China University of Science and Technology

ISBN: (纸本)9781479900305

In this paper, the containment control problem is studied for the cooperative output regulation of linear multi-agent systems(MASs). The output regulation problem initiated from single-leader-follower region is extended to the multi-leaders-follower region. The purpose of this paper is to design a containment control algorithm such that all the followers can move into the convex hull formed by the leaders. A sufficient and necessary condition in term of a linear matrix inequality (LMI) is derived for the existence of a containment controller protocol that guarantees the followers are capable to follow the trail of leader and the output error will converge to zero with the time elapsing. Then, a controller design procedure is given to construct the feedback gain matrix and select the proper gain matrix for achieving final consensus of the MASs. Compared with the existing algorithms, the proposed one requires less information and calculation of the velocities measurement of the agents. Finally, a numerical example is illustrated to show the usefulness of the designed containment controller.

关键词： Containment control, Linear system, Multi-agent systems, Output regulation

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