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Multi-mode process monitoring based on a novel weighted local standardization strategy and support vector data description

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Journal of Central South University 2016年第11期23卷 2896-2905页

作者：赵付洲宋冰侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education(East China University of Science and Technology) Shanghai 200237China

There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.

关键词： multiple operating modes weighted local standardization support vector data description multi-mode monitoring

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Prediction Consensus-Based Distributed Kalman Filtering with Packet Loss 36

Prediction Consensus-Based Distributed Kalman Filtering with...

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第36届中国控制会议

作者： Sha Fan Huaicheng Yan Hao Zhang Mengling Wang Xisheng Zhan Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University Department of Control Science and Engineering Tongji University

ISBN: (纸本)9781538629185

This paper is concerned with the problem of distributed state estimation for linear discrete system with packet loss.A state prediction consensus mechanism is introduced to promote the estimation *** applying matrix theory,a sufficient condition for the convergence of the estimation error system is ***,a numerical example is given to show the algorithm proposed in this paper has better consensus performance compared with a classical Kalman consensus filtering（KCF） by some simulations in real and packet-dropping cases,***,the influence of consensus coefficient and prediction consensus coefficient on the estimation error covariance are presented by simulation.

关键词： Distributed state estimation Packet loss Kalman consensus filtering（KCF） State prediction consensus mechanism

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GPU-based coevolutionary particle swarm optimization 36

GPU-based coevolutionary particle swarm optimization

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第36届中国控制会议

作者： ZHAO Liang Zhu Yanxing ZHANG Jianyu Ye Zhencheng Key Laboratory of Advanced Control and Optimization for Chemical Process(Ministry of Education) East China University of Science and Technology Ethylene Plant of Jilin Petrochemical Company Ltd.PetroChina

ISBN: (纸本)9781538629185

Coevolutionary particle swarm optimization（CPSO） algorithm has been investigated and applied in the real world *** tackling the large-scale and complex real time optimization problems,the running time of CPSO algorithm is a *** this paper,Graphics Processing Unit（GPU） is introduced to provide speedup in order to meet the real time *** CPSO algorithm has been implemented on GPU concurrently using the CUDA *** performance and run time of CPU-based and GPU-based CPSO algorithms are compared in *** experiment result shows that the GPU-based parallel computation mode can shorten the run time of CPSO algorithm apparently.

关键词： GPU CUDA Particle swarm optimization Coevolutionary particle swarm optimization

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BCI-based strategies on stroke rehabilitation with avatar and FES feedback

arXiv

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arXiv 2018年

作者： Qiu, Zhaoyang Chen, Shugeng Allison, Brendan Z. Jia, Jie Wang, Xingyu Jin, Jing Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China Department of Neurology Huashan hospital Fudan University Shanghai China Department of Cognitive Science University of California at San Diego San DiegoCA United States

Background: Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor function after rehabilitation therapy. Some studies have shown that motor imagery (MI) based BCI has a positive effect in poststroke rehabilitation. It could help patients promote the reorganization processes in the damaged brain regions. However, offline motor imagery and conventional online motor imagery with feedback (such as rewarding sounds and movements of an avatar) could not reflect the true intention of the patients. Method: In this study, both virtual limbs and functional electrical stimulation (FES) were used as feedback to provide patients a closed-loop sensorimotor integration for motor rehabilitation. Motor imagery based BCI system acquired, analyzed and recognized the EEG data of motor imagery from patients. The FES system would activate if the user was imagining hand movement of instructed side. Ten stroke patients (7 male, aged 22-70 years, mean 49.5±15.1) were involved in this study. All of them participated in BCI-FES rehabilitation training for 4 weeks. Results: The average motor imagery accuracies of the ten patients in the last week were 71.3%, which has improved 3% than that in the first week. Five patients' Fugl-Meyer Assessment (FMA) scores have been raised. Patient 6, who has have suffered from stroke over two years, achieved the greatest improvement after rehabilitation training (pre FMA: 20, post FMA: 35). In the aspect of brain patterns, the active patterns of the five patients gradually became centralized and shifted to sensorimotor areas (channel C3 and C4) and premotor area (channel FC3 and FC4). Conclusions: In this study, motor imagery based BCI and FES system were combined to provided stoke patients with a closed-loop sensorimotor integration for motor rehabilitation. Result showed evidences that the BCI-FES system is effective in restoring upper extremities motor function in stroke. In future work, more cases are

关键词： Brain computer interface

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Thermal Decomposition Behavior of Terephthalate in Inert Gas

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China Petroleum Processing & Petrochemical Technology 2017年第3期19卷 1-8页

作者： Yu Jing Wang Jiming Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237 DuPont China Holding Co. LtdShanghai 201203 School of Chemical Engineering East China University of Science and TechnologyShanghai 200237

Several metal terephthalates were synthesized by hydrothermal solvent method. Firstly, the coordination type of metal ions and carboxylates in terephthalate was studied by FTIR spectroscopy. The results showed that the binding type of zinc terephthalate and aluminum terephthalate are mainly bridged coordination, while the chelating coordination mode dominated in the magnesium terephthalate and cerium terephthalate. Secondly, the thermal decomposition mechanism of zinc terephthalate in nitrogen atmosphere was studied by TG and Py-GC/MS techniques. Finally, the activation energy of the thermal decomposition process was obtained by the Friedman method and the Flynn-Wall-Ozawa(FWO) method, and the most probabilistic function was obtained by multiple linear fitting. The results showed that the decomposition process of zinc terephthalate was an one-step reaction and the activation energy was equal to 187.38 kJ/mol.

关键词： terephthalate TG/DTG thermal decomposition mechanism kinetics

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Finite time boundedness of switched delay systems by sliding mode technique 36

Finite time boundedness of switched delay systems by sliding...

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第36届中国控制会议

作者： Haijuan Zhao Yugang Niu Tinggang Jia Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education Automation Division of Shanghai Electric Group Co. Ltd.

ISBN: (纸本)9781538629185

In this paper,the finite-time boundedness（FTB） problem of sliding mode control（SMC） is investigated for a class of switched delay systems subject to uncertain parameter and nonlinear perturbation.A SMC law is constructed to drive the state trajectories onto the integral sliding surface during a finite time *** FTB of the controlled systems on both reaching phase and siding motion phase are analyzed by means of average dwell time ***,a numerical example is given.

关键词： Switched delay system Finite time boundedness Sliding mode control Average dwell time

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A new lumped kinetic model of an industrial hydrocracking process

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chemical Engineering Transactions 2017年 61卷 673-678页

作者： Song, Wenjiang Zhong, Weimin Yang, Minglei Du, Wenli Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

Hydrocracking is a catalytic cracking process for the conversion of heavy oil fractions, such as vacuum gas oil (VGO), into valuable products with lower boiling point, such as diesel, kerosene and gasoline. Due to the flexibility of the process, high yields and good quality of liquid products, hydrocracking has become an important unit in modern refinery. However, the study of kinetic modelling towards hydrocracking reactor (HCR) is limited due to its complicated reaction mechanism. In this study, the reactor model is established based on a new six-lump model considering the velocity change along the reactor, different thermal effects and kinetic differences between hydrotreater (HT) and hydrocracker (HC). Compared with the previously reported lumped kinetic models, the fine-tuned model (calibrated by differential evolution algorithm) can predict products yields more accurately, in particular outlet temperature of each beds and the detailed yields and temperature distribution along with the reactor beds. The proposed lump based kinetic model can be applied to the optimization and control of industrial hydrocracking process. © 2017, AIDIC Servizi S.r.l.

关键词： Kinetic theory

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Smart and Optimal Manufacturing： The key for the Transformation andDevelopment of the Process Industry

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Engineering 2017年第2期3卷 151-151页

作者： Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and TechnologyShanghai 200237 China

In recent years, smart manufactur-ing has been the focus of competitionand collaboration between countriesaround the world. The major developedand developing countries are speedingup their strategic planning and layoutfor smart manufacturing. Germany, theUnited States, and China have releasedthe Industry 4.0, Smart Process Man-ufacturing, and Made in China 2025initiatives, respectively, which aim ata deep integration of information andcommunication technology and man-ufacturing technology, thus achieving seamless integration of prod-ucts, equipment, humans, and organizations.

关键词：期刊编辑工作人物介绍工程

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Teaching-Learning-Based optimization with Learning Enthusiasm Mechanism and Its Application in chemical Engineering

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Journal of Applied Mathematics 2018年第none期2018卷 1-19页

作者： Chen, Xu Xu, Bin Yu, Kunjie Du, Wenli School of Electrical and Information Engineering Jiangsu University Zhenjiang Jiangsu212013 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China School of Mechanical Engineering Shanghai University of Engineering Science Shanghai201620 China School of Electrical Engineering Zhengzhou University Zhengzhou450001 China

Teaching-learning-based optimization (TLBO) is a population-based metaheuristic search algorithm inspired by the teaching and learning process in a classroom. It has been successfully applied to many scientific and engineering applications in the past few years. In the basic TLBO and most of its variants, all the learners have the same probability of getting knowledge from others. However, in the real world, learners are different, and each learner's learning enthusiasm is not the same, resulting in different probabilities of acquiring knowledge. Motivated by this phenomenon, this study introduces a learning enthusiasm mechanism into the basic TLBO and proposes a learning enthusiasm based TLBO (LebTLBO). In the LebTLBO, learners with good grades have high learning enthusiasm, and they have large probabilities of acquiring knowledge from others;by contrast, learners with bad grades have low learning enthusiasm, and they have relative small probabilities of acquiring knowledge from others. In addition, a poor student tutoring phase is introduced to improve the quality of the poor learners. The proposed method is evaluated on the CEC2014 benchmark functions, and the computational results demonstrate that it offers promising results compared with other efficient TLBO and non-TLBO algorithms. Finally, LebTLBO is applied to solve three optimal control problems in chemical engineering, and the competitive results show its potential for real-world problems. © 2018 Xu Chen et al.

关键词： Computational efficiency

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Soft sensor based on recursive kernel partial least squares for 4-carboxybenzaldehyde of an industrial terephthalic acid hydropurification process

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chemical Engineering Transactions 2017年 61卷 463-468页

作者： Li, Zhi Zhong, Weimin Peng, Xin Du, Wenli Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

Terephthalic acid is a raw material for polyester and textile industry. However, the by-product 4-Carboxybenzaldehyde in TA is harmful to the polymer process since it can lower the polymerization rate and the average molecular weight. Thus, a hydropurification process is built to decrease 4-CBA. In this process, 4-CBA in TA is purified by hydrogen in water at 270 °C-290 °C under 7.9 MPa pressure over 0.5 wt. % carboncoated palladium catalyst in a fixed-bed reactor. The activity of the catalyst will gradually decrease with the process running. The most important quality index for this process is the content of 4-CBA in the product. However, in real plant, the content of 4-CBA is analysed every two hours in a laboratory. It is a very large delay for control system so the operation conditions of the process could not be adjusted in time. These may results in a maximum two hours product failure. In this paper, a first principle model of the process is developed based on Aspen Plus. The accuracy of the model is verified by the model results and the actual plant results. Based on this model, a series of sensitive analysis are performed. Six variables include 4-CBA content in TA, react temperature, react pressure, hydrogen flow rate, catalyst activity and Slurry concentration are the main factors influencing the 4-CBA content in the product. Though the aspen model is accurate, these parameters in aspen model are not easy to adjust quickly. In order to predict 4-CBA content quickly, a soft sensor for 4-CBA is developed using recursive kernel partial least squares considering the nonlinearity and slow time-varying of the process. Results show that the prediction accuracy of this method is very high and it is easy for engineers to handle. Copyright © 2017, AIDIC Servizi S.r.l.

关键词： chemical reactors

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