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Communications in Computer and Information Science 2014年 461卷 33-38页

作者： Chen, Lanlan Zhao, Y. Zhang, Jian Zou, Junzhong Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology 130 Meilong Road Shanghai200237 China

ISBN: (纸本)9783662452820

In the present study, twelve volunteers were participated in a 2 h continuous mental arithmetic task without any break, which was designed to induce mental fatigue. The negative influence was investigated through EEG coherence, which was used as a measure of synchronization of different underlying brain regions. It was observed that the sustained mental task led to increased EEG coherence, which did not result in more efficient performance. The change of EEG coherence was widespread not limited to specific brain regions or frequency bands. The variation of EEG coherence combined with behavior performance validated the impact of mental fatigue caused by a continuous mental task. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Brain

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Particle swarm optimization algorithm of self-adaptive parameter based on ant system and its application

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Kongzhi Lilun Yu Yingyong/control Theory and Applications 2010年第11期27卷 1479-1488页

作者： Yang, Fan Hu, Chun-Ping Yan, Xue-Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China Shanghai Nuclear Engineering Research and Design Institute Shanghai 200233 China

To adjust the inertia weight in particle swarm optimization(PSO), we propose a novel self-adaptive particle swarm optimization algorithm based on ant system(AS-PSO). First, the inertia weight space is divided into several regions;each of them is given the same initial intensity of pheromone trails. The probability for selecting a parameter region for each particle is determined by the intensity of the region pheromone trails and the particle's a priori knowledge of the search space. The evolution search is then performed in spaces of solutions. Finally the trail of the regions is updated according to the information of evolution. Experiments indicate that the promising AS-PSO algorithm realizes the evolution and the self-adaptation of the inertia weight by ant colony algorithm without increasing the function calls in evaluation. Results show that AS-PSO obviously outperforms the original self-adaptive PSO and the APSO-VI, in which the parameter is adjusted according to the velocity information. Furthermore, satisfactory results have been obtained when AS-SPO algorithm is applied to estimate the parameter of complex system models.

关键词： Particle swarm optimization (PSO)

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optimization of Catalytic Naphtha Reforming Process Based on Modified Differential Evolution Algorithm ∗

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IFAC-PapersOnLine 2015年第8期48卷 373-378页

作者： Min Wei Minglei Yang Feng Qian Wenli Du Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education Shanghai CO 200237 PRC Tel: ***

Catalytic naphtha reforming is one of the most important processes for high octane gasoline manufacture and aromatic hydrocarbons production. In this article, a modified differential evolution (DE) algorithm is proposed to optimize an actual continuous catalytic naphtha reforming (CCR) process. The optimization problem considers to minimize the energy consumption and maximize the aromatics yield. The CCR process model is established by adopting the 27-lumped kinetics reaction network, and all parameters are adjusted based on the actual process data. The DE algorithm is modified to maintain the diversity of the population. In this mechanism, individuals further from the best individual have larger possibilities to be selected in the mutation operator. The modified DE is evaluated by solving 6 benchmark functions, and the performance is compared with classic DEs. The results demonstrate that the modified DE has better global search ability and higher computation efficiency. Furthermore, the optimization results of catalytic naphtha reforming process indicate that the proposed algorithm has the ability of locating the optimal operating points, in which the aromatics yield is improved, while energy consumption is reduced. Meanwhile, the optimal operating points and results are discussed at the end of the article.

关键词： Catalytic naphtha reforming process Energy consumption Differential evolution Global search

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Leader selection in multi-agent networks with switching topologies via submodular optimization

arXiv

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arXiv 2019年

作者： Chen, Kaile He, Wangli Tang, Yang Zhang, Wenle Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

In leader-follower multi-agent networks with switching topologies, choosing a subset of agents as leaders is a critical step to achieve desired performances. In this paper, we concentrate on the problem of selecting a minimum-size set of leaders that ensure the tracking of a reference signal in a high-order linear multi-agent network with a set of given topology-dependent dwell time (TDDT). First, we derive a sufficient condition that guarantees the states of all agents converging to an expected state trajectory. Second, by exploiting submodular optimization method, we formulate the problem of identifying a minimal leader set which satisfies the proposed sufficient condition. Third, we present an algorithm with the provable optimality bound to solve the formulated problem. Finally, several numerical examples are provided to verify the effectiveness of the designed selection scheme. Copyright © 2019, The Authors. All rights reserved.

关键词： Topology

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Energy consumption monitoring of the steam pipe network based on affinity propagation clustering

Energy consumption monitoring of the steam pipe network base...

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World Congress on Intelligent control and Automation (WCICA)

作者： Xiazhu You Wenli Du Liang Zhao Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

The steam system is an important part of chemical utility system, but there are widespread phenomenon about lack of testing information, energy consumption configuration depend on given experience and wasting energy. So this paper puts forward a method about the steam pipe network system's status identification of different energy consumption based on the steam pipe network's characteristics of complex structure, much steam equipment, lack of testing information and difficult to build accurate mathematical model. The method based on affinity propagation clustering that can solve big set of data's clustering problem quickly and effective. As it is hard to find preference parameters and damping factor, this paper uses PSO to find the most optimal parameters in order to achieve the best clustering effect. This method is applied test both in classic data set and the steam pipe network of ethylene plant's status identification, the results show the effectiveness of this method.

关键词： Energy consumption Indexes optimization Clustering algorithms Temperature measurement Pattern recognition Frequency modulation

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Surrogate model of aromatic isomerization process based on adaptive sampling algorithm

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Huagong Xuebao/CIESC Journal 2020年第2期71卷 688-697页

作者： Xie, Yuheng Li, Zhi Yang, Minglei Du, Wenli State Key Laborotory of Chemical Engineering Key Laboratory of Advanced Control and Optimization for Chemical Processed of Ministry of Education East China University of Science and Technology Shanghai200237 China

Isomerization is an important part in the production of aromatics. Improving the modeling and optimization efficiency of isomerization is of great significance to industrial production. However, the optimization process using the mechanism model directly takes a long time and the optimization efficiency is low. The surrogate model can effectively approximate the mechanism model and greatly reduce the computation time. The surrogate model sampling method has a great influence on the accuracy of the model. A new adaptive sampling algorithm based on sparsity and nearest neighbor expectation is proposed in this paper, which can balance global search and local search. By solving the optimization problem, we can find new sampling points that reflect the key information of the object function, and then add the new point to the sample set, so that the accuracy of the surrogate model is continuously improved. The results of multiple test functions show that compared with other adaptive sampling algorithms, the algorithm can effectively improve the accuracy and modeling efficiency of the surrogate model. The algorithm is also validated in the aromatic isomerization surrogate model. Compared with other algorithms, our algorithm model error is reduced by more than 5%, and the modeling time is reduced by more than 30%. © All Right Reserved.

关键词： Isomerization

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A new brain-computer interface paradigm based on P300 and SSVEP

A new brain-computer interface paradigm based on P300 and SS...

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Chinese control Conference (CCC)

作者： Minjue Wang Jing Jin Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China

Brain-Computer Interface (BCI) is a novel communication system without depending on conventional brain output paths (such as peripheral nerve and muscle tissue) of the brain. The evaluation of effective EEG patterns is one of the crucial issues in the current research of BCI. Most of the traditional visual evoked paradigms only evoke one kind of EEG pattern for the subsequent feature classification. This study presents a new paradigm based on P300 and Steady-State Visual Evoked Potential (SSVEP) that involves event-related stimulation and frequency flashing stimulation. P300 and SSVEP patterns are evoked simultaneously to enhance the discriminability of features. Offline comparison is implemented among the proposed paradigm and the traditional P300 and SSVEP paradigms. The results show that the new paradigm evokes more significant P300 features while weaken SSVEP features a little without destroying the online feasibility of the BCI system. Therefore, the proposed paradigm can satisfy requirements from different subjects to enlarge the user of group.

关键词： Electroencephalography Brain-computer interfaces Educational institutions Visualization Electronic mail Steady-state Correlation

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Quantized H∞ control for stochastic nonlinear networked systems

Quantized H∞ control for stochastic nonlinear networked sys...

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Chinese control and Decision Conference, CCDC

作者： Huaicheng Yan Hongbo Shi Hao Zhang Haitao Zhao Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Shanghai 200237 China Tongji University Shanghai Shanghai CN

In this paper, we are concerned with the quantized H ∞ control problem for a class of stochastic systems with random communication delays. The system under consideration involves signals quantization, Itô stochastic disturbance as well as random communication delays. The measured output and the control input quantization are considered simultaneously. We aim at designing an observer-based controller such that the dynamics of the filtering error is guaranteed to be exponentially stable in the mean square, and a prescribed H ∞ disturbance attenuation level is also achieved. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

关键词： Educational institutions Delays Quantization (signal) Electronic mail Stochastic systems Laboratories optimization

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Quantized and networked predictive control for input-saturated systems

Quantized and networked predictive control for input-saturat...

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Chinese control Conference (CCC)

作者： Yuanyuan Zou Bei Chen Tinggang Jia Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

This paper investigates the problem of stabilizing predictive control for constrained systems with quantization and communication delays. Based on the quantization matrix, the input-saturated control systems with logarithmic quantizers are described as constrained control systems with structured norm-bounded uncertainties. A quantized and networked predictive control algorithm is presented by using a multirate delay compensation strategy. It is shown that the proposed predictive controller not only efficiently reduces the negative effects of the quantization and communication delays but also guarantees the closed-loop stability and constraints satisfaction. The simulation example shows the effectiveness of the derived method.

关键词： Delay Predictive control control systems Quantization Stability analysis Uncertainty Prediction algorithms

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Early Warning Technology for Cracking Severity Basedon Improved Cultural Differential Algorithm

Early Warning Technology for Cracking Severity Basedon Impro...

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The 8th World Congress on Intelligent control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Yunxia Pu Mandan Liu Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

Effective monitoring and early warning for cracking severity are directly related to the ethylene production stability and the overall economic benefits. Elman neural network is used to establish the early warning model of cracking severity, and an improved Cultural Differential Evolution algorithm(ICDE) is proposed to training the model. This hybrid algorithm integrates Cultural algorithm(CA) and Differential Evolution algorithm(DE) together, and increases some measure indicators of evolution direction, to make the algorithm more adaptive. Simulation results show that this method gains accurate warning signals to the cracking working conditions timely and effectively, obtained satisfactory results.

关键词： Cultural differences Artificial neural networks Furnaces Training Next generation networking Predictive models Production

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