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第三十二届中国控制会议

作者： Bei Chen Tinggang Jia Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education Automation Division Shanghai Electric Group Co.Ltd.

ISBN: (纸本)9781479900305

This paper investigates the problem of sliding mode control for a class of stochastic Markovian jumping systems with partially known transition rate.A key feature in this work is to relax the requirement that all the elements in transition rate matrix are known,which is usually encountered in some existing *** is shown that the reachability of the specified sliding surface can be ensured by the designed sliding mode ***,the suffcient conditions for the stability of the sliding motion on the sliding surface are also derived.

关键词： Markovian jumping systems incomplete transition rate state-dependent noise sliding mode control

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Brain control: Human-computer Integration control Based on Brain-computer Interface Approach

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Acta Automatica Sinica 2013年第3期39卷 208-221页

作者： Xing-Yu WANG Jing JIN Yu ZHANG Bei WANG Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education School of Information science and Technology East China University of Science and Technology Shanghai 200237 China

Recently, a new system called brain control system has been developed rapidly. Brain control system is a human-computer integration control system based on brain-computer interface (BCI), which relies on human's ideas and thinking. Brain control system has been successfully applied in wide fields, assisting disabled patients daily life, training patients with stroke or limb injury, monitoring the state of human operator, as well as entertainment and smart house etc. In this paper, the background, basic principle, system structure and developments are firstly introduced briefly. The current research status focusing on the problems of electroencephalograph (EEG) signal pattern, control signal transfer algorithm and system application is summarized and analyzed in detail. The further research direction and problems are discussed. Finally, the future development of brain control is analyzed and prospects are given.

关键词： Brain control brain-computer interface (BCI) human-computer integration control electroencephalogram (EEG)

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Containment control for the cooperative output regulation of linear multi-agent systems

Containment control for the cooperative output regulation of...

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Chinese control Conference (CCC)

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

In this paper, the containment control problem is studied for the cooperative output regulation of linear multi-agent systems(MASs). The output regulation problem initiated from single-leader-follower region is extended to the multi-leadersfollower region. The purpose of this paper is to design a containment control algorithm such that all the followers can move into the convex hull formed by the leaders. A sufficient and necessary condition in term of a linear matrix inequality (LMI) is derived for the existence of a containment controller protocol that guarantees the followers are capable to follow the trail of leader and the output error will converge to zero with the time elapsing. Then, a controller design procedure is given to construct the feedback gain matrix and select the proper gain matrix for achieving final consensus of the MASs. Compared with the existing algorithms, the proposed one requires less information and calculation of the velocities measurement of the agents. Finally, a numerical example is illustrated to show the usefulness of the designed containment controller.

关键词： Eigenvalues and eigenfunctions Educational institutions Lead Topology Laplace equations Multi-agent systems Algorithm design and analysis

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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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Adaptive neural output feedback control for stochastic nonlinear systems with unknown control directions

Adaptive neural output feedback control for stochastic nonli...

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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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Neural network modeling for parabolic distributed parameter system based on improved GSO algorithm

Neural network modeling for parabolic distributed parameter ...

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Chinese control Conference (CCC)

作者： Mengling Wang Xingdi Yan Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology 130 Meilong Road Shanghai 200237 China

This paper proposes an artificial neural network (ANN) based time/space separation modeling approach to predict nonlinear parabolic DPSs. First, the spatial-temporal output is divided into a few dominant spatial basis functions and low-dimensional time series by PCA method. Then a three-layer feed-forward ANN is identified by low-dimensional time series, where the improved group search optimization (GSO) is proposed to optimize the connection weights and thresholds to solve the problem of falling into the local optima. Finally, the nonlinear spatiotemporal dynamics is determined after the time/space reconstruction. Simulations are presented to demonstrate the accuracies and effectiveness of the proposed methodologies.

关键词： Artificial neural networks Distributed parameter systems optimization Computational modeling Electronic mail Aerospace electronics

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Automatic Estimation of Sleep Level for Nap Based on Conditional Probability of Sleep Stages and An Exponential Smoothing Method

Automatic Estimation of Sleep Level for Nap Based on Conditi...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Bei Wang Xingyu Wang Tao Zhang Masatoshi Nakamura Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Department of Automation Tsinghua University Research Institute of Systems Control Institute for Advanced Research and Education Saga University

ISBN: (纸本)9781457702150

An automatic sleep level estimation method was developed for monitoring and regulation of day time nap sleep. The recorded nap data is separated into continuous 5-second segments. Features are extracted from EEGs, EOGs and EMG. A parameter of sleep level is defined which is estimated based on the conditional probability of sleep stages. An exponential smoothing method is applied for the estimated sleep level. There were totally 12 healthy subjects, with an averaged age of 22 yeas old, participated into the experimental work. Comparing with sleep stage determination, the presented sleep level estimation method showed better performance for nap sleep interpretation. Real time monitoring and regulation of nap is realizable based on the developed technique.

关键词： Sleep level estimation Sleep stage Conditional probability Nap regulation

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Assessment of Texaco syngas components using extreme learning machine based quantum neural network

Communications in Computer and Information Science

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Communications in Computer and Information Science 2013年 355卷 221-229页

作者： Xu, Wei Wang, Raofen Gu, Xingsheng Sun, Youxian State Key Laboratory of Industrial Control Technology Zhejiang University 310027 Hangzhou China Department of Automation Shanghai University of Engineering Science 201620 Shanghai China Key Laboratory of Advanced Control Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology 200237 Shanghai China

Quantum neural computing has nowadays attracted much attention, and tends to be a candidate to improve the computational efficiency of neural networks. In this paper, a new quantum neural network (QNN) is proposed based on quantum mechanics of superposition and collapse, etc. Instead of gradient descent methods and evolutionary algorithms, extreme learning machine (ELM) is introduced to analytically identify the parameters of the QNN. The ELM-QNN model is applied to the online and real-time assessment of the syngas components in a Texaco gasification process. The application would effectively avoid the problems of time delay and low accuracy which result from the manual analysis. In order to eliminate the redundant information stored in variables, principal component analysis (PCA) is adopted to reduce the number of input variables of ELM-QNN. The results indicate that ELMQNN combined with PCA method has satisfied computational accuracy and efficiency. The PCA-ELM-QNN is very capable of being used for the real-time measurement of Texaco syngas components. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Principal component analysis

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Fast consensus of directed network via optimal pinning control

Fast consensus of directed network via optimal pinning contr...

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Chinese control Conference (CCC)

作者： Wen Yang Ying Wang Xiaofan Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China Department of Automation Shanghai Jiaotong University 200240 China

In this paper, we consider fast and desired consensus of directed network via pinning control. First, we provide a sufficient condition for the stability of desired consensus algorithm. Second, we investigate the problem of selecting optimal pinned nodes for driving fastest consensus, which is formulated as an Mixed-Integer Semidefinite Program. Finally, we illustrate all the results by simulating on some typical directed networks.

关键词： Convergence Eigenvalues and eigenfunctions Switches Complex networks optimization

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Modeling of Binary Phase Equilibrium in Supercritical Ethylene coordination Polymerization System

Modeling of Binary Phase Equilibrium in Supercritical Ethyle...

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Asian Polyolefin Workshop (APO2013)2013亚洲聚烯烃研讨会

作者： Keran Chen Tian Zhou Boping Liu State Key Laboratory of Chemical Engineering East China University of Science and Technology Meilong Road 130 Shanghai 200237 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Meilong Road 130 Shanghai 200237

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