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作者： Jiang, Qingchao Yan, Xuefeng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology MeiLong Road No. 130 Shanghai200237 China

Multiblock principal component analysis (MBPCA) methods are gaining increasing attentions in monitoring plant-wide processes. Generally, MBPCA assumes that some process knowledge is incorporated for block division;however, process knowledge is not always available. A new totally data-driven MBPCA method, which employs mutual information (MI) to divide the blocks automatically, has been proposed. By constructing sub-blocks using MI, the division not only considers linear correlations between variables, but also takes into account non-linear relations thereby involving more statistical information. The PCA models in sub-blocks reflect more local behaviors of process, and the results in all blocks are combined together by support vector data description. The proposed method is implemented on a numerical process and the Tennessee Eastman process. Monitoring results demonstrate the feasibility and efficiency. © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： process monitoring

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L2- L∞ State Estimation for Discrete-time Delayed Neural Networks with Missing Measurements and Randomly Occurring Sensor Linearity

L2- L∞ State Estimation for Discrete-time Delayed Neural Ne...

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第35届中国控制会议

作者： Hao Zhang Huaicheng Yan Hongbo Shi Hao Zhang Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education Department of Control Science and Engineering Tongji University

ISBN: (纸本)9781509009107

This paper is concerned with the L-L state estimation problem for discrete-time delay neural networks with missing measurements and randomly occurring sensor *** phenomena of missing measurements and randomly occurring sensor linearity are constructed with two sequences of random variables,which obey the partial Bernoulli distribution.A sufficient condition is firstly given such that the augmented filtering error system is stochastically stable with a guaranteed optimal L-L performance by solving a set of linear matrix inequalities(LMIs).Finally,a simulation example is given to show the effectiveness of the proposed method.

关键词： L2-L∞ state estimation discrete-time delayed neural networks missing measurements randomly occurring sensor linearity

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An improved discrete artificial bee colony algorithm for hybrid flow shop problems

Communications in Computer and Information Science

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Communications in Computer and Information Science 2013年 355卷 294-302页

作者： Cui, Zhe Gu, Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China

Being a typical NP-hard combinatorial optimization problem, the hybrid flow shop (HFS) problem widely exists in manufacturing systems. In this paper, we firstly establish the model of the HFS problem by employing the vector representation. Then an improved discrete artificial bee colony (IDABC) algorithm is proposed for this problem to minimize the makespan. In the IDABC algorithm, a novel differential evolution and a modified variable neighborhood search are studied to generating new solutions for the employed and onlooker bees. The destruction and construction procedures are utilized to obtain solutions for the scout bees. The simulation results clearly imply that the proposed IDABC algorithm is highly effective and efficient as compared to six state-of-the-art algorithms on the same benchmark instances. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Manufacture

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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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Research on Optimized Fuzzy controller based on GA for Precise Aeration System

Research on Optimized Fuzzy Controller based on GA for Preci...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Wenyong Wang Ziqiang Sun Huanlai Cao Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E

It is known that the characteristic of Dissolved Oxygen (DO) control system is non-linear, variability and uncertainty, etc. This paper presents Genetic Algorithm (GA) to optimize the fuzzy controller, which adjusts the membership function of fuzzy controller parameters by GA. The results show that the optimized fuzzy controller based on GA is well up for the shortage of the traditional fuzzy controller. With this controller we can get target such as: obtaining better control result, improving the efficiency of sewage treatment, having significant effect for stable and secure running and reducing energy consumption.

关键词： Sewage treatment Dissolved oxygen Fuzzy control Genetic algorithm

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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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Study on an improved bee colony algorithm and its application in optimization of PX oxidation process

Study on an improved bee colony algorithm and its applicatio...

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

作者： Li, Xinmao Xing, Jianliang Luo, Na Zhong, Weimin Cheng, Hui Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China College of Chemical Engineering East China University of Science and Technology Shanghai China

For the deficiencies of the basic bee colony algorithm based on the mechanism of nectar (ABC), such as the population diversity scarcity in the early iterations and easily sticking into the local optimum, a strategy which integrates an improved differential evolution (DE) method into bee colony algorithm (DE-ABC) is proposed. The primary idea of DE-ABC is to introduce DE into the mutation of employed bee instead of random search strategy, and combination of incremental strategy of the crossover probability factor and the scaling factor, strategy of stagnation judgment and treatment. Four benchmark functions are used to make a comparison, and results show that DE-ABC converges with a faster accelerated rate and a higher accuracy optimization. Then DE-ABC is applied to the optimization of p-xylene oxidation process. With the purpose of reducing the exhaust CO, CO2 of the reactor and the first crystallizer, an excellent solution of the operating variables is obtained under the process operating parameters constraints, which gives a guide to the plant operation.

关键词： optimization

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Consensus based distributed estimation with sensor selection strategies in energy constrained wireless sensor networks

Consensus based distributed estimation with sensor selection...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Wen Yang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of

In the applications of wireless sensor networks(WSNs), sensor energy saving is essential to increase the life of sensor networks. In this paper, we consider the problem of performing consensus based estimation over energy constrained WSNs, in which energy is conserved by selecting only a subset of sensors to observe the state of the dynamical system at each time step. First, we derive an sufficient condition for the convergence of the state estimation covariance. Second, we propose a sensor selection strategy to schedule sensors to measure the system state for next step with the goal of minimizing the state estimation error subject to sensor energy constraint. Finally, we provide some numerical examples to illustrate the performance and effectiveness of the proposal strategy.

关键词： consensus problem Kalman filter state estimation convex optimization

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A Comparison of Navigation System Based on P300 BCI and SSVEP BCI

A Comparison of Navigation System Based on P300 BCI and SSVE...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Lijing Meng Jing Jin Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationSc Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education S

A navigation system based on P300 brain computer interface system (BCIs) and steady-state visual evoked potentials (SSVEP) BCIs respectively was designed in this paper. In the experiment, subjects were required to move a ball on the computer screen to the target position by P300 BCI system and SSVEP BCI system. Bayesian linear discriminant analysis (BLDA) is used to detect P300 potentials and canonical correlation analysis (CCA) is used to detect SSVEP. The aim of this paper is to show the drawbacks and advantages of these two BCIs, when they were used in navigation task. The online experimental results show that P300 BCIs is more robust for subjects compared to SSVEP BCIs.

关键词： P300 Steady-State Visual Evoked Potentials (SSVEP) Brain Computer Interface Navigation System

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Delay-dependent output feedback integral sliding mode control of singularly perturbed systems

Delay-dependent output feedback integral sliding mode contro...

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International Conference on control and Automation (ICCA)

作者： Jing Xu Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Process East China University of Science and Technology Shanghai China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper presents a descriptor system method for output feedback integral sliding mode control of singularly perturbed systems. The fast state, representing the derivative of output, is approximated with aid of an artificial time-delay estimator. Then, a delay-dependent integral sliding mode controller is designed to ensure the occurrence of sliding phase since the initial time instant. The finite frequency uncertainty is divided into the matched and uncertainty uncertainty. On this basis, the proposed controller contains the nominal part to attain the robustness to the unmatched uncertainty, and the switching part to compensate the matched uncertainty. Finally, the effectiveness of the design method is verified in a mass-damper-spring system subject to finite frequency perturbations.

关键词： Uncertainty Output feedback Perturbation methods Sliding mode control Linear matrix inequalities Delay effects Matrix decomposition

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