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A data-approach for industrial utility systems optimization under uncertainty

Energy 2019年 182卷 559-569页

作者： Zhao, Liang You, Fengqi Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China Robert Frederick Smith School of Chemical and Biomolecular Engineering Cornell University IthacaNY14853 United States

Energy optimization of utility system helps to reduce the operating cost and save energy for the industrial plants. Widespread uncertainties such as device efficiency and process demand pose new challenges for this issue. A hybrid modeling framework is presented by introducing the operating data into mechanism model to adapt the changes of device efficiency and operating conditions. Mathematical models of boilers, steam turbines, and letdown valves are then developed in the framework. Based on the process historical data of a real-world plant, a Dirichlet process mixture model is used to capture the support information of uncertain parameters. Bridging data-driven robust optimization (DDRO) and utility system optimization under uncertainty, a robust mixed-integer nonlinear programming (MINLP) model is developed by utilizing the derived uncertainty set. The robust counterpart of the developed model can be reformulated as a tractable MINLP problem including conic quadratic constraints that could be solved efficiently. A real-world case study is carried out to demonstrate the effectiveness of the proposed approach in protecting against uncertainties and achieving a good trade-off between optimality and robustness of the operational decisions for industrial utility systems. © 2019 Elsevier Ltd

关键词： Boilers

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Distribution Adaptation Local Outlier Factor for Multimode process monitoring

Distribution Adaptation Local Outlier Factor for Multimode P...

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Chinese control Conference (CCC)

作者： Yutang Xiao Yang Tao Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In modern industrial processes, the production process includes multiple operating modes, due to changes in production goals and conditions. And the data generated in this process is a mixture of Gaussian and non-Gaussian distributions. Therefore, the data distribution of multimode processes is uncertain and complex. It is difficult to monitor multimode processes accurately by using traditional Multivariate Statistical process Monitoring (MSPM) methods. In this case, the absence of labeled data is considered more valuable. This paper proposes a new unsupervised domain adaptive method called the Distribution Adaptation Local Outlier Factor (DALOF). This method can extract useful information from multimode data through domain adaptation, which can reduce the distribution difference of training data and improve the accuracy of modeling. In the DALOF model, data from different modes in the training set are defined as the source domain and the target domain. Weight the training data according to their correlation, and then project these data into a low-dimensional subspace. In this space, the distribution distance between the source and target domain is minimum. To solve the nonlinear characteristics of multimode data, this paper uses LOF to build a model and formed a density-based monitoring index. Numerical examples and Tennessee Eastman (TE) process simulation demonstrate the effectiveness of DALOF.

关键词： Monitoring Training data Adaptation models Data models Training Production process control

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Automatic detection of awake state during sleep based on the approximate entropy of EMG

Automatic detection of awake state during sleep based on the...

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International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)

作者： Qihui Ai Bei 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 China

ISBN: (数字)9781728180229

ISBN: (纸本)9781728180236

Sleep is important to human beings. A good sleep can bring sufficient energy and keep healthy. Sleep process contains several sleep stages. There are also several short-duration awake states appeared in sleep process. The amount of those awake states during sleep would be related to evaluate the sleep quality. In this study, the automatic detection method of awake state is investigated on the sleep recording of patient with sleep disorder. Two nonlinear features of ApEN and Mc-ApEN are calculated based on the EMG signal recorded during one's overnight sleep process. The detection performance is analyzed and compared. The obtained results showed that the presented method is feasible for awake state detection during sleep, where Mc-ApEN is slightly better than ApEN. It can be an assistant tool for sleep evaluation.

关键词： Tools Electromyography Entropy Informatics

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Sliding Mode control for Networked control System Under Fading Channels

Sliding Mode Control for Networked Control System Under Fadi...

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control Technology and Applications (CCTA),

作者： Jiarui Li Yugang Niu Yuanyuan Zou Key Laboratory of Advanced Control and optimization for Chemical Process (East China University of Science and Technology) Ministry of Education Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China

In this work, the discrete-time sliding mode control problem for the networked control systems under fading channels is investigated. Moreover, the state signals will be quantized through a logarithmic quantizer before transmitted to the controller. Subsequently, a sliding surface relating to fading coefficient is designed to cope with the fading measurements. It is shown that the designed sliding mode controller can drive the state trajectories into the neighborhood of the specified sliding surface and the closed-loop system is asymptotically stable in the sense of mean square. In the end, a numerical simulation is given.

关键词： Fading channels Quantization (signal) Symmetric matrices Sliding mode control Closed loop systems Lyapunov methods Networked control systems

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Improving the performance of online classifier by removing the error samples from offline training data

Improving the performance of online classifier by removing t...

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International Conference on Computer and Communications (ICCC)

作者： Hanhan Zhang Jing Jin Sijie Zhou Yu Zhang Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

Brain-computer interface (BCI) plays an important role in helping the people with severe motor disability. In event-related potential (ERP) based BCIs, subjects were asked to count the target stimulus in the offline experiment, the recorded electroencephalogram (EEG) data was used to train the classification mode. However, subjects may make mistakes in counting the target stimulus or be affected by the non-target stimulus. The target trials may not contain expected ERPs and the non-target trials may contain unexpected ERPs, which was called error samples. This paper intends to survey whether the classification accuracy could be improved after removing these error samples from offline training data. The result showed that the online performance of BCI system could be improved after selecting the offline samples for training the classification mode.

关键词： Electroencephalography Feature extraction Training Classification algorithms Electrodes Band-pass filters Brain modeling

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Real Time optimization of the Gasoline Blending process with Unscented Kalman Filter

Real Time Optimization of the Gasoline Blending Process with...

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International Conference on Internet Computing and Information Services (ICICIS)

作者： Hui Cheng Weimin Zhong Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

Gasoline blending is a critical process in petroleum refineries. Real-time optimization (RTO) techniques have been popular with the applications for the blending process for optimization purpose. However the dependency of RTO on the measurement of the component impairs its applicability. Therefore how to utilize the blending model and the product measurement to free RTO from the component measurement is the major research topic in this paper. Unscented Kalman Filter, due to its ability to estimate the parameter for nonlinear model, is chosen to estimate component properties based on the product measurement. The RTO strategy is then proposed with the UKF method for the recipe calculation periodically. Furthermore, the proposed RTO is tested with the gasoline blending benchmark problem, while the results are compared with the ideal blending case. The accuracy of the component estimation and the efficiency of the RTO are verified with the results.

关键词： Mathematical model Petroleum optimization Equations Kalman filters Vectors Covariance matrix

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An Optimized BCI System Based on P300 and Visual Mismatch Negativity

An Optimized BCI System Based on P300 and Visual Mismatch Ne...

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International Conference on Information Science and control Engineering (ICISCE)

作者： Sijie Zhou Jing Jin Yu Zhang Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9781467368513

This paper presents a brain-computer interface (BCI) in which the face paradigm was optimized for the visual mismatch negativity (MMN). There were 12 cells in a LCD monitor. A single letter was at the bottom of each cell. In the new paradigm, a color face appeared above each of the 12 cells randomly while the gray faces appeared in others 11 cells. A traditional face paradigm with single character pattern was compared. Three healthy subjects participated in the experiment. Results showed that the new paradigm elicited larger N200 and N400 components than traditional face paradigm and had better performance in online session. The results demonstrated the advantages of the new paradigm in our P300 speller system.

关键词： Face Frequency modulation Visualization Accuracy Brain-computer interfaces Electroencephalography Electrodes

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Pulse-Modulated Intermittent control for Scaled Consensus of Second-Order Multi-Agent Systems

Pulse-Modulated Intermittent Control for Scaled Consensus of...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Hualiang Guo Wangli He The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

The scaled consensus problem for second-order multi-agent systems is studied in this paper. A novel scaled consensus algorithm combining impulsive control and sampled control is proposed to make the agents' states achieve a common quantity but of their own scales. In the proposed algorithm, a special function, named intermittent function, is introduced to represent the control duration and the rest duration. Specifically, by selecting special functions as the proposed intermittent functions, the scaled consensus algorithm can drop into impulsive control or sampled control. Several necessary and sufficient conditions are derived to ensure scaled consensus of the controlled second-order multi-agent systems under directed graph. An example is provided to validate the theoretical analysis.

关键词： Multi-agent systems Convergence Graph theory control systems Satellites Continuous time systems Nickel

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Integration of multi-feature for moving target detection algorithm

Integration of multi-feature for moving target detection alg...

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International Conference on Electrical and control Engineering, ICECE 2010

作者： Yu, Jin Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9780769540313

Moving object segmentation and marking object area is one of the key technologies of intelligent surveillance. In this paper, combining the background modeling in pixel level, the proposed algorithm presented gradient-based spatial characteristics in order to improve detection accuracy. For the trade-off problem of background modeling, established the velocity characteristics for each property of moving targets, to make online updates of the GMM more adaptable. The results indicate that this technique can improve the efficiency and stability of detection. © 2010 IEEE.

关键词： Economic and social effects

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Impulsive consensus of leader-following nonlinear multi-agent systems under DoS attacks

Impulsive consensus of leader-following nonlinear multi-agen...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Yiting Wang Wangli He Ministry of Education The Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China

This paper investigates impulsive consensus of nonlinear multi-agent systems in the leader-following framework subject to denial-of-service (DoS) attacks. The case that the communication network suffers from DoS attacks is considered, which will destroy the communication link, resulting in switching topologies. Based on the assumption that the system can recover from DoS attacks, sufficient conditions on the design of the impulse interval and the impulse attack ratio that the system can sustain is provided. A numerical example is given to validate the effectiveness of our theoretical results.

关键词： Multi-agent systems Topology Switches Denial-of-service attack Network topology Communication networks

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