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Global Inference Preserving Projection for Semi-supervised Discriminant Analysis

Journal of Donghua University(English Edition) 2012年第2期29卷 144-147页

作者：谷小婧孙韶媛方建安 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology College of Information Science&Technology Donghua University

Semi-supervised dimensionality reduction is an important research area for data classification. A new linear dimensionality reduction approach, global inference preserving projection （GIPP）, was proposed to perform classification task in semi-supervised case. GIPP provided a global structure that utilized the underlying discriminative knowledge of unlabeled samples. It used path-based dissimilarity measurement to infer the class label information for unlabeled samples and transformd the diseriminant algorithm into a generalized eigenequation problem. Experimental results demonstrate the effectiveness of the proposed approach.

关键词： semi-supervised learning dimensionality reduction manifoM structure

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Modified Self-adaptive Immune Genetic Algorithm for optimization of Combustion Side Reaction of p-Xylene Oxidation

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Chinese Journal of chemical Engineering 2012年第6期20卷 1047-1052页

作者：陶莉莉孔祥东钟伟民钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology Automation Institute East China University of Science and Technology

In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.

关键词： self-adaptive immune genetic algorithm artificial neural network measurement p-xylene oxidation process

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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, BMEI 2011

作者： Wang, Jiesen Wang, Bei Wang, Xingyu Nakamura, Masatoshi Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai China Research Institute of Systems Control Institute for Advanced Research and Education Saga University Saga Japan

ISBN: (纸本)9781424493524

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%. © 2011 IEEE.

关键词： Markov processes

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Improved Kernel PLS-based Fault Detection Approach for Nonlinear chemical processes

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Chinese Journal of chemical Engineering 2014年第6期22卷 657-663页

作者：王丽侍洪波 School of Electrical and Electronic Engineering Shanghai Institute of Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in comparison to KPLS monitoring.

关键词： nonlinear process fault detection kernel partial least squares statistical local approach

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Robust Semi-Global Leaderless Consensus and Containment control of Identical Linear Systems with Imperfect Actuators

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Journal of Systems Science & Complexity 2018年第1期31卷 69-86页

作者： SHI Liangren ZHAO Zhiyun LIN Zongli Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240 China Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 USA

This paper investigates both the robust semi-global leaderless consensus problem and the robust semi-global containment control problem for a group of identical linear systems with imperfect actuators. The imperfect actuators are characterized by nonlinearities such as saturation and dead zone and there input output relationships are not precisely known. The dynamics of follower agents are also affected by the input additive disturbances. Low-and-high gain feedback consensus protocols are constructed to solve these problems. More specifically, it is shown that robust semi-global leaderless consensus can be achieved over a connected undirected graph and robust semi-global containment control can be achieved when each follower agent has access to the information of at least one leader agent. Numerical simulation illustrates the theoretical results.

关键词： Consensus containment control dead zone leaderless consensus multi-agent systems saturation

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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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On set stabilization for genetic regulatory networks 35

On set stabilization for genetic regulatory networks

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第35届中国控制会议

作者： LI Fangfei LI Jianning YU Zhaoxu School of Automation Hangzhou Dianzi University Department of Mathematics East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781509009107

Set stabilization for Boolean networks which is a kind of genetic regulatory networks is considered in this paper. An algorithm is provided to achieve the set stability for Boolean networks by changing the columns of the transition matrices of Boolean networks. Then, pinning nodes can be selected. Furthermore, pinning control design algorithm is given. Finally, the model for infection of the bacterium is presented to illustrate the effectiveness of the proposed results.

关键词： Boolean networks set stabilization pinning control semi-tensor product

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Parameter estimation of industrial PET reactor using multi-objective kernel density estimation of distribution algorithm

Parameter estimation of industrial PET reactor using multi-o...

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作者： Luo, Na Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai 200237 China State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China

With a multitude of reaction pathways, poly (ethylene-terephthalate) (PET) polymerization of industrial practice is complex, and the quality of PET is normally described in terms of several experimentally measured indices. In this paper, parameters estimation of industrial PET reactors is presented as a multi-objective problem to make the mathematic model consistent with the actual industrial process. Considering the interrelation among parameters and the failure of general optimization algorithms, a new multi-objective estimation of distribution algorithm is proposed. Kernel density estimation is used to make the new population more suitable for real-life problems instead of Gaussian model during the evolution of the algorithm. Strategies including selection of kernel width, sampling method and Pareto domination selection are used to explore and exploit the search space more efficiently. With industrial operating data identified in steady state and eliminated from gross error, kinetic parameters are estimated by minimizing carboxyl end group concentration and degree of polymerization simultaneously using the proposed algorithm. The simulation results show that the model with estimated parameters has better predictive performance compared with the experimental parameters. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.

关键词： Parameter estimation

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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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Integral control on nonlinear spaces: two extensions

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IFAC-PapersOnLine 2016年第18期49卷 1000-1005页

作者： Zhang, Zhifei Ling, Zhihao Sarlette, Alain Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Department of Electronics & Information Systems Ghent University Shanghai China Key Laboratory of A.C.O.C.P. ECUST Shanghai China Department of Electronics & Information Systems Ghent University QUANTIC lab INRIA Paris France

This paper applies the recently developed framework for integral control on nonlinear spaces to two non-standard cases. First, we show that perfect target stabilization in presence of actuation bias holds also if this bias is state dependent. This might not be surprising, but in practice it provides an easy way to robustly cancel nonlinear dynamics of the uncontrolled plant. We specifically illustrate this for robust stabilization of a pendulum at arbitrary angle. Second, as previous work has been restricted to systems with as many control inputs as configuration dimensions, we here provide results for integral control of a non-holonomic system. More precisely, we design robust steering control of a rigid body under velocity bias. © 2016

关键词： Feedback linearization Lie groups Stabilization Arbitrary angles control inputs Geometric control Integral control Nonholonomic systems Robust stabilization State dependent Steering control

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