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Chinese control Conference (CCC)

作者： Zhaoxu Yu Shugang Li Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai 200237 China Department of Industrial Engineering and Logistics Shanghai Jiao Tong University China 200240 China

This paper focuses on the problem of adaptive output feedback stabilization for a class of stochastic nonlinear system with unknown control directions. By using a linear state transformation, the unknown control coefficients are lumped together, such that the original system is transformed to a new system for which control design becomes feasible. By employing the input-driven observer, a novel adaptive neural network (NN) output-feedback controller which only contains one adaptive parameter is developed for such systems by using backstepping technique and NNs' parameterization. The proposed control design guarantees that all the signals in the closed-loop systems are 4-moment semi-globally uniformly ultimately bounded.

关键词： Adaptive systems Artificial neural networks Nonlinear systems control design Observers

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Automatic Identification of Diffuse and Localized Activity for Topographical Distribution of EEG Rhythm Based on Suitable Reference Selection with Pre-judgments

Automatic Identification of Diffuse and Localized Activity f...

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2013 ICME International Conference on Complex Medical Engineering(2013 ICME复合医学工程国际会议)

作者： Bei Wang Xingyu Wang Akio Ikeda Takashi Nagamine Hiroshi Shibasaki Masatoshi Nakamura Key Laboratory of Advanced Control and Optimization for Chemical Processes(East China University of Department of Neurology Kyoto University Kyoto Japan Department of System Neuroscience Sapporo Medical University Hokkaido Japan Takeda General Hospital Kyoto Japan Research Institute of Systems Control Institute for Advanced Research and Education Saga Universit

ISBN: (纸本)9781467329705

An automatic reference selection method with prejudgments was developed in order to identify the two patterns of diffuse and localized EEG activity,as well as the topographical *** diffuse activity is identified and the effect of adopted reference is analyzed by using two *** localized activity is analyzed where the focal and distributed electrodes are derived based on an iterative detection ***,the suitable reference is determined which is adaptive to the actual characteristics of diffuse and localized ***,the topographical distribution is obtained automatically during the reference selection *** presented method has the performance to be an assistant and subjective tool for clinical application,especially for the quantitative interpretation on EEG rhythm.

关键词： Topographical distribution of EEG rhythm Automatic Identification Pre-judgments Reference selection Diffuse and localized activity

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Denoising and Rhythms Extraction of EEG under +Gz Acceleration Based on Wavelet Packet Transform

Denoising and Rhythms Extraction of EEG under +Gz Accelerati...

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2013 ICME International Conference on Complex Medical Engineering(2013 ICME复合医学工程国际会议)

作者： Yifeng Li Tao Zhang Lue Deng Bei Wang Masatoshi Nakamura Department of Automation Tsinghua University Beijing 100084 China Air Force Institute of Aeromed Department of Automation Tsinghua University Beijing 100084 China Key Laboratory of Advanced Con Air Force Institute of Aeromedicine Beijing 100142 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Shanghai 200237 China Research Institute of Systems Control Saga University Saga 840-0047 Japan

ISBN: (纸本)9781467329705

Filtering and feature extraction are very important in the analysis and study of EEG signal under +Gz *** this study,a new filter of different frequency characteristics of EEG signal under +Gz acceleration is constructed and four kinds of rhythms of EEG signal are extracted by using wavelet packet *** under different G loads is analyzed and compared,and then EEG dynamic characteristics are studied in order to analyze its advantages and *** results show that wavelet packet method can effectively suppress interference bands in EEG,such as EMG,power and so on,and effectively reflect the dynamic characteristics of different rhythms,exhibiting good *** proposed method is also applicable for analyzing and studying other dynamic biomedical signals.

关键词： EEG wavelet packet filtering denoising rhythms extraction

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Synchronization of nonlinear coupled networks with time-delay via distributed impulsive control

Synchronization of nonlinear coupled networks with time-dela...

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Chinese control Conference (CCC)

作者： Hao Zhang Gang Feng Huaicheng Yan Qijun Chen Department of Control Science and Engineering Tongji University Shanghai 200092 China Department of Mechanical & Biomedical Engineering City University of Hong Kong Hong Kong Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and Engineering East China University of Science and Technology Shanghai 200237 China

In this paper, the synchronization of a nonlinear network with time-varying coupling delay is investigated via distributed impulsive control. Our objective is to design the distributed impulsive controller with minimum coupling strength such that the nonlinear network with coupling delay is globally exponentially synchronous. Some sufficient conditions have been derived based on Lyapunov-Razumikhin method in terms of matrix inequalities. An example is presented to illustrate the effectiveness of the proposed control methods.

关键词： Couplings Synchronization Oscillators Linear matrix inequalities Delays Network topology Topology

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Global Inference Preserving Projection for Semi-supervised Discriminant Analysis

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Journal of Donghua University(English Edition) 2012年第2期29卷 144-147页

作者：谷小婧孙韶媛方建安 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology College of Information Science&Technology Donghua University

Semi-supervised dimensionality reduction is an important research area for data classification. A new linear dimensionality reduction approach, global inference preserving projection （GIPP）, was proposed to perform classification task in semi-supervised case. GIPP provided a global structure that utilized the underlying discriminative knowledge of unlabeled samples. It used path-based dissimilarity measurement to infer the class label information for unlabeled samples and transformd the diseriminant algorithm into a generalized eigenequation problem. Experimental results demonstrate the effectiveness of the proposed approach.

关键词： semi-supervised learning dimensionality reduction manifoM structure

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A Discrete Artificial Bee Colony Algorithm for Minimizing the Total Flow Time in the Blocking Flow Shop Scheduling

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Chinese Journal of chemical Engineering 2012年第6期20卷 1067-1073页

作者：邓冠龙徐震浩顾幸生 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.

关键词： blocking flow shop scheduling artificial bee colony algorithm total flow time

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Soft Sensor for Ammonia Concentration at the Ammonia Converter Outlet Based on an Improved Group Search optimization and BP Neural Network

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Chinese Journal of chemical Engineering 2012年第6期20卷 1184-1190页

作者：阎兴頔杨文马贺贺侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

The ammonia synthesis reactor is the core unit in the whole ammonia synthesis production. The ammonia concentration at the ammonia converter outlet is a significant process variable, which reflects directly the production efficiency. However, it is hard to be measured reliably online in real applications. In this paper, a soft sensor based on BP neural network (BPNN) is applied to estimate the ammonia concentration. A modified group search optimization with nearest neighborhood (GSO-NH) is proposed to optimize the weights and thresholds of BPNN. GSO-NH is integrated with BPNN to build a soft sensor model. Finally, the soft sensor model based on BPNN and GSO-NH (GSO-NH-NN) is used to infer the outlet ammonia concentration in a real-world application. Three other modeling methods are applied for comparison with GSO-NH-NN. The results show that the soft sensor based on GSO-NH-NN has a good prediction performance with high accuracy. Moreover, the GSO-NH-NN also provides good generalization ability to other modeling problems in ammonia synthesis production.

关键词： ammonia synthesis ammonia concentration soft sensor group search optimization

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Multimode Process Monitoring Based on Fuzzy C-means in Locality Preserving Projection Subspace

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Chinese Journal of chemical Engineering 2012年第6期20卷 1174-1179页

作者：解翔侍洪波 Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of Education

For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring strategy based on fuzzy C-means. The high dimensional historical data are transferred to a low dimensional subspace spanned by locality preserving projection. Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operational mode. The distance statistics of each cluster are integrated though the membership values into a novel BID (Bayesian inference distance) monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman benchmark process.

关键词： multimode process monitoring fuzzy C-means locality preserving projection integrated monitoring index Tennessee Eastman process

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Peak Traffic Forecasting Using Nonparametric Approaches

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上海交通大学学报（英文版） 2012年第1期17卷 76-81页

作者： ZHANG Yang WANG Meng-ling Shanghai Municipal Transportation Information Center Shanghai 200032 China Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

States of traffic situations can be classified into peak and nonpeak periods. The complexity of peak traffic brings more difficulty to forecasting models. Travel time index (TTI) is a fundamental measure in transportation. How to master the characteristics and provide accurate real-time forecasts is essential to intelligent transportation systems (ITS). Cooperating with state space approach, least squares support vector machines (LS-SVMs) are investigated to solve such a practical problem in this paper. To the best of our knowledge, it is the first time to apply the technique and analyze the forecast performance in the domain. For comparison purpose, other two nonparametric predictors are selected because of their effectiveness proved in past research. Having good generalization ability and guaranteeing global minima, LS-SVMs perform better than the others. Providing sufficient improvement in stability and robustness reveals that the approach is practically promising.

关键词： traffic forecasting peak traffic nonparametric techniques

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Weighted least square support vector machine integrated with parameter optimization and its application in chemical process

Weighted least square support vector machine integrated with...

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2012 8th International Conference on Natural Computation, ICNC 2012

作者： Cui, Wen-Tong Yan, Xue-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)9781457721311

Considering that outliers can disrupt the correlation structure of least square support vector machine (LS-SVM), and that the parameters of LS-SVM play an important role in the performance, a novel weighted least square support vector machine integrated with parameter optimization is proposed to obtain the optimal parameters and to eliminate the effect of outliers. Several LS-SVM variants are applied in simulation experimentation and chemical process respectively to demonstrate the satisfactory performance of the proposed method. © 2012 IEEE.

关键词： Vectors

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