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High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

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Chinese Journal of Chemical Engineering 2015年第9期23卷 1509-1517页

作者：田颖杜文莉钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

Purified terephthalic acid(PTA) is an important chemical raw material. P-xylene(PX) is transformed to terephthalic acid(TA) through oxidation process and TA is refined to produce PTA. The PX oxidation reaction is a complex process involving three-phase reaction of gas, liquid and solid. To monitor the process and to improve the product quality, as well as to visualize the fault type clearly, a fault diagnosis method based on selforganizing map(SOM) and high dimensional feature extraction method, local tangent space alignment(LTSA),is proposed. In this method, LTSA can reduce the dimension and keep the topology information simultaneously,and SOM distinguishes various states on the output map. Monitoring results of PX oxidation reaction process indicate that the LTSA–SOM can well detect and visualize the fault type.

关键词： Self-organizing map Local tangent space alignment Fault diagnosis Visualization P-xylene oxidation

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Guaranteed cost filtering for discrete-time multi-layer neural networks with time-varying delays and unideal measurements

Guaranteed cost filtering for discrete-time multi-layer neur...

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International Conference on Information and Automation (ICIA)

作者： Hao Zhang Huaicheng Yan Congzhi Huang Mengling Wang East China University of Science and Technology Shanghai Shanghai CN Key Laboratory of Adv Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781509041039

This paper is concerned with the guaranteed cost filtering problem for discrete-time multi-layer neural networks with unideal measurements and time-varying delays. First, the innovative state space model of multi-layer neural networks can be described by the weighted-nonlinear function, which means that there have connections among neural layers. Then, the unideal measurements are made up by combination of random sensor nonlinearity and partial missing measurements, where partial missing measurements is the product of two mutually independent stochastic variables and normal measurements. Moreover, by using proportionate-additive filter and constructing a unified Lyapunov function, a novel criterion is proposed so that the augmented filtering error system achieves robust stability and has a guaranteed cost index. Finally, simulation results are presented to demonstrate the effectiveness of the derived method.

关键词： Delays Multi-layer neural network Robustness Linear matrix inequalities Radio frequency

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A fast MPC algorithm for reducing computation burden of MIMO

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Chinese Journal of Chemical Engineering 2015年第12期23卷 2087-2091页

作者：祁荣宾梅华陈超钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is proposed in this paper to solve this problem, in which real-time values are modulated to bit streams to simplify the multiplication. In addition, manipulated variables in the prediction horizon are deduced to the current control horizon approximately by a recursive relation to decrease the dimension of QR optimization. The simulation results demonstrate the feasibility of this fast algorithm for MIMO systems.

关键词： Fast MPC algorithm Computation burden One-bit operation Dimension reduction

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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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IEEE International Conference on Computer and Communications, ICCC 2015

作者： Zhang, Hanhan Jin, Jing Zhou, Sijie Zhang, Yu Wang, Xingyu 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)9781467381253

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. © 2015 IEEE.

关键词： Brain computer interface

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Distributed event triggered H∞ filtering with nonhomogeneous Markov switching topologies

Distributed event triggered H∞ filtering with nonhomogeneou...

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UKACC International Conference on control (control)

作者： Wen Song Hao Zhang Huaicheng Yan Chen Peng Department of Control Science and Engineering Tongji University Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

The distributed H ∞ state estimation problem over a filtering network with Markov switching topology is studied in this paper by employing event-triggered strategy. The strategy at each node is built on the output estimation error of its own and those received from its neighbours. Based on the communication uncertainty of practical networks, switching topology which subjects to a heterogeneous Markov chain is considered in filter design. By utilizing stochastic Markov stability theory, switching topology-dependent filters are designed such that the underlying error system is stochastically stable in mean square and the disturbance rejection attenuation level guarantees an H ∞ performance bound. An illustrative example is presented to show the applicability of the obtained results.

关键词： Network topology Switches Topology Symmetric matrices Markov processes Estimation error Attenuation

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Robust Stabilization of Input Constrained Uncertain Systems with Nonhomogeneous Markov Switching

Robust Stabilization of Input Constrained Uncertain Systems ...

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第28届中国控制与决策会议

作者： Yanyan Yin Zongli Lin Ministry of Education Key Laboratory of Advanced Process Control for Light Industry Institute of AutomationJiangnan University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

ISBN: (纸本)9781467397155

This paper addresses the problem of robust stabilization for uncertain systems subject to input saturation and nonhomogeneous Markov *** uncertainties are assumed to be norm bounded and the transition probabilities are time-varying and *** expressing the saturated linear feedback law on a convex hull of a group of auxiliary linear feedback laws and the time-varying transition probabilities inside a polytope,we establish conditions under which the closed-loop system is asymptotically *** on these conditions,the problem of designing the state feedback gains for achieving fast transience response with a guaranteed size of the domain of attraction is formulated and solved as a constrained optimization problem with linear matrix inequality(LMI) *** results are then illustrated by a numerical example.

关键词： Robust stabilization actuator saturation Markov jumps time-varying transition probabilities uncertainties

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Design of a visual information-based brain-computer interface control system 11

Design of a visual information-based brain-computer interfac...

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11th International Conference on Natural Computation, ICNC 2015

作者： Hu, Huiping Jin, Jing Zhang, Yu Wang, Xingyu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai200237 China

ISBN: (纸本)9781467376792

Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to pay attention not only to the target stimulus, but also to the real control target which would bring high workload to users and affect the control efficiency of BCI systems. In this paper, a real-time monitoring system was developed to solve this problem by showing the environment information from the camera on the computer screen. Five subjects took part in this experiment and all of them were asked to control a small car to the target position. Our result showed that all subjects could finish the task within two or three minutes. In this study, subject did not need to switch their attention on the car which was out of their sight, and it would help to improve the usability of BCI in the practical application. © 2015 IEEE.

关键词： Cameras

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Consensus control for Second-Order Multi-Agent with Time-Delay on Antagonistic Networks

Consensus Control for Second-Order Multi-Agent with Time-Del...

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第35届中国控制会议

作者： Penglin LI Yue LIU Yadong ZHAO Jie YANG Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University State Key Laboratory of Industrial Control Technology Institute of Industrial Process ControlCollege of Control Science and EngineeringZhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781509009107

In this paper,we discuss consensus problems for antagonistic networks with double integrator *** cases are analyzed:(1) undirected graphs with fixed topology on antagonistic networks;(2) undirected graphs with fixed topology and time-delay on antagonistic *** both cases,distributed consensus protocols are proposed,with sufficient and necessary conditions *** is proved that the largest tolerable time-delay is only related to the largest eigenvalue of the graph ***,simulations are provided to demonstrate the obtained theoretical results.

关键词： Consensus Fixed Topology Multi-agent Antagonistic Networks Time-delay

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Hierarchical method of task assignment for multiple cooperating UAV teams

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Journal of Systems Science & Complexity 2015年第5期28卷 1000-1009页

作者： Xiaoxuan Hu Huawei Ma Qingsong Ye He Luo School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

The problem of task assignment for multiple cooperating unmanned aerial vehicle(UAV) teams is considered. Multiple UAVs forming several small teams are needed to perform attack tasks on a set of predetermined ground targets. A hierarchical task assignment method is presented to address the problem. It breaks the original problem down to three levels of sub-problems: target clustering, cluster allocation and target assignment. The first two sub-problems are centrally solved by using clustering algorithms and integer linear programming, respectively, and the third sub-problem is solved in a distributed and parallel manner, using a mixed integer linear programming model and an improved ant colony algorithm. The proposed hierarchical method can reduce the computational complexity of the task assignment problem considerably, especially when the number of tasks or the number of UAVs is large. Experimental results show that this method is feasible and more efficient than non-hierarchical methods.

关键词： unmanned aerial vehicle （UAV） task assignment clustering integer linear programming ant colony optimization（ACO） algorithm

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Improved performance of process monitoring based on selection of key principal components

Improved performance of process monitoring based on selectio...

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作者： Song, Bing Ma, Yuxin Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai200237 China

Conventional principal component analysis (PCA) can obtain low-dimensional representations of original data space, but the selection of principal components (PCs) based on variance is subjective, which may lead to information loss and poor monitoring performance. To address dimension reduction and information preservation simultaneously, this paper proposes a novel PC selection scheme named full variable expression. On the basis of the proposed relevance of variables with each principal component, key principal components can be determined. All the key principal components serve as a low-dimensional representation of the entire original variables, preserving the information of original data space without information loss. A squared Mahalanobis distance, which is introduced as the monitoring statistic, is calculated directly in the key principal component space for fault detection. To test the modeling and monitoring performance of the proposed method, a numerical example and the Tennessee Eastman benchmark are used. © 2015 Elsevier B.V.

关键词： Principal component analysis

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