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Cooperative game based cost analysis of multi-plant heat exchanger network integration in chemical Industry Park

chemical Engineering Transactions 2017年 61卷 1219-1224页

作者： Jin, Yuhui Li, Shaojun Jiang, Da Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai200237 China

Industrial energy saving is essential to the plant in the chemical industry park. Heat exchanger network of multi-plant can recover more potential energy. To ensure the network construction successfully, co-construct cost must be allocated reasonably. Cooperative game-theory based approach combines "Core" and "Riskbased Shapley value" with the network structure is put forward to give a contribute-equal cost imputation. A case study which includes three chemical plants is used to describe the approach and shows its practice value. The case study used Risk-based Shapley value illustrated plant which is confronted with high risk-loss will participate in the co-construction with lower cost, which means high risk and high yielded side by side. Copyright © 2017, AIDIC Servizi S.r.l.

关键词： Energy conservation

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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and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution.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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Improved Estimation of Distribution Algorithm for Solving Unrelated Parallel Machine Scheduling Problem

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Journal of Donghua University(English Edition) 2016年第5期33卷 797-802页

作者：孙泽文顾幸生 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

Scheduling problem is a well-known combinatorial optimization *** effective improved estimation of distribution algorithm(IEDA) was proposed for minimizing the makespan of the unrelated parallel machine scheduling problem(UPMSP).Mathematical description was given for the *** IEDA which was combined with variable neighborhood search(IEDA_VNS) was proposed to solve the UPMSP in order to improve local search ability.A new encoding method was designed for representing the feasible solutions of the *** knowledge of the UPMSP were taken consideration in IEDA_ VNS for probability matrix which was based the processing time *** simulation results show that the proposed IEDA_VNS can solve the problem effectively.

关键词： Scheduling neighborhood scheduling minimizing processed unrelated probabilistic intelligent heuristic representing

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Variable Classification-based Co-estimation of Distribution Algorithm Assisted by a Cooperative Particle Swarm Optimizer

Variable Classification-based Co-estimation of Distribution ...

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2017第二届亚太计算智能与信息技术学术会议 (APCIIT 2017)

作者： Wen Liu Xuefeng Yan East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology

Since estimation of distribution algorithms(EDAs) were proposed,many methods have been made to improve EDAs' performance. In this paper,a variable classification-based cooperative estimation of distribution algorithm(VC-CEDA) is proposed to balance the global and local searching ability of estimation of distribution algorithms. This study proposes a variable classification method to improve the efficiency and accuracy of probability model development. And a cooperative particle swarm optimizer that can improve the local searching ability is proposed. The VC-CEDA combines the advantages of traditional algorithm and cooperative operations. VC-CEDA shows significantly better performance on 10 test functions. In this study,the experimental results show that the VC-CEDA performs better than traditional EDAs.

关键词： Variable Classification-based Co-estimation of Distribution Algorithm Assisted by a Cooperative Particle Swarm Optimizer Swarm

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Variable Classification-based Co-estimation of Distribution Algorithm Assisted by a Cooperative Particle Swarm Optimizer

Variable Classification-based Co-estimation of Distribution ...

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2017 Asia-Pacific Computational Intelligence and Information Technology Conference

Since estimation of distribution algorithms(EDAs) were proposed,many methods have been made to improve EDAs' *** this paper,a variable classification-based cooperative estimation of distribution algorithm(VC-CEDA) is proposed to balance the global and local searching ability of estimation of distribution *** study proposes a variable classification method to improve the efficiency and accuracy of probability model *** a cooperative particle swarm optimizer that can improve the local searching ability is *** VC-CEDA combines the advantages of traditional algorithm and cooperative ***-CEDA shows significantly better performance on 10 test *** this study,the experimental results show that the VC-CEDA performs better than traditional EDAs.

关键词： Variable Classification-based Co-estimation of Distribution Algorithm Assisted by a Cooperative Particle Swarm Optimizer Swarm

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Exponential dissipative control of stochastic systems under wireless communication networks 35

Exponential dissipative control of stochastic systems under ...

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第35届中国控制会议

作者： SONG Jun NIU Yugang ZOU Yuanyuan Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education

ISBN: (纸本)9781509009107

In this work,the problem of dissipative control is investigated for stochastic systems under the unreliable wireless network,in which there may exist stochastic fading ***,a modified Rice fading model with disturbance-dependent noise is *** then,a state-feedback controller with fading measurements is designed and the some sufficient conditions are derived such that the closed-loop system is finite-time stochastic bounded with a prescribed exponentially dissipative ***,numerical simulation results are provided.

关键词： Stochastic systems fading channel dissipative control

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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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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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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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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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