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Joint 48th IEEE Conference on Decision and control and 28th Chinese control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu the Department of Systems and Control Beihang University (BUAA) the Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications the School of Electrical Engineering and Automation Henan Polytechnic University

This paper is concerned with the iterative learning control(ILC) problem for discrete-time systems with iterationvarying *** the so-called super-vector approach to ILC,the discrete domain bounded real lemma is employed to develop a sufficient condition ensuring both the stability and the desired H∞ performance of the ILC *** is shown that this sufficient condition can be presented in terms of linear matrix inequalities(LMIs),which can also determine the learning gain matrix.A numerical simulation example is included to validate the theoretical results.

关键词： Iterative learning control discrete-time systems iteration-varying disturbances H_∞ performance linear matrix inequality

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Distributed shift target estimation using multiple cooperative agents

Distributed shift target estimation using multiple cooperati...

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Asian control Conference

作者： Jiangping Hu Yiguang Hong Xiaoming Hu School of Automation Engineering University of Electronic Science and Technology Chengdu China Kay Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy and Sciences Beijing China Optimization and Systems Theory Royal Institute of Technology Stockholm Sweden

In this paper we discuss the estimation of a moving target by cooperative agents equipped with sensors. To locate a moving target, a distributed algorithm is given for the networked agents based on a time-based shift. A nonlinear filter with fusing collected sensor information is proposed to estimate the trajectory of the target with unknown dynamics. The convergence of the estimation in the sensor network is analyzed and proved via a theoretic approach.

关键词： Trajectory Collaboration Information processing Sensor fusion Target tracking Convergence Information filtering Information filters Robotics and automation Distributed algorithms

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A novel fingerprint recognition algorithm using 2DPCA and RBFNN

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Journal of Information and Computational science 2009年第4期6卷 1899-1906页

作者： Ni, Jianyun Xu, Qinmin Lei, Ming Luo, Jing Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin University of Technology Tianjin 300191 China School of Electrical Engineering Tianjin University of Technology Tianjin 300191 China School of Computer Science and Technology Tianjin University of Technology Tianjin 300191 China College of Electrical Engineering and Automation Tianjin Polytechnic University Tianjin 300160 China

Fingerprint recognition algorithm based on minutiae has large computation, slow recognition speed as a result of complex processing, such as image enhance, smooth, binary, and thinning. A novel fingerprint recognition algorithm Using 2DPCA(Two-Dimensional Principal Component Analysis) has been proposed in this paper. Firstly, original images are decomposed into high-frequency and lowfrequency components with the help of Wavelet Transform (WT), and high-frequency components are ignored, so the prime features of original images can be attained. Secondly, the projected features are solved by 2DPCAFinallyfingerprint recognition can be realized by Radial Basis Function Neural Network (RBFNN). The algorithm combines the optimization of the 2DPCA and the adaptability of RBFNN. The experimental results based on FVC2002 have verified that the proposed algorithm has higher robustness to the fingerprint images which has the change of shift and rotation and light than IDFFWNN. © 2009 Binary Information Press.

关键词： Wavelet transforms

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Automatic interpretation of hyperventilation-induced electroencephalogram fitting to visual inspection

Automatic interpretation of hyperventilation-induced electro...

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ICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009

作者： Zhang, Xiu Wang, Xingyu Sugi, Takenao Ikeda, Akio Nagamine, Takashi Shibasaki, Hiroshi Nakamura, Masatoshi Department of Automation East China University of Science and Technology Shanghai China Department of Electrical and Electronic Engineering Saga University Saga Japan Department of Neurology Graduate School of Medicine Kyoto University Kyoto Japan Department of System Neuroscience Sapporo Medical University Hokkai-do Japan Takeda General Hospital Kyoto Japan Research Institute of Systems Control Institute for Advanced Research and Education Saga University Saga Japan

ISBN: (纸本)9784907764333

Quantitative analysis and detection of abnormalities for electroencephalogram (EEG) recordings during evoked activities are essential for clinical diagnosis on neurological disorders. However, the process of interpreting EEG is time consuming and requires experienced electroencephalographers (EEGers). In this study, a method of automatic EEG interpretation during hyperventilation was proposed. The purpose is to provide a quantitative interpretation of EEG which is able to conform to EEGers' visual inspection. The final integrated results of automatic interpretation were compared with EEGers' evaluation, and showed high consistence. © 2009 SICE.

关键词： Electroencephalography

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Adaptive multi-class support vector machine for microarray classification and gene selection

Adaptive multi-class support vector machine for microarray c...

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SICE Annual Conference

作者： Juntao Li Yingmin Jia Junping Du Fashan Yu Department of Systems and Control Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper proposes an adaptive multi-class support vector machine for simultaneous microarray classification and gene selection. By evaluating the gene ranking significance, the adaptive multi-class support vector machine is shown to encourage an adaptive grouping effect in the process of building classifiers, thus leading a sparse multi-classifiers with enhanced interpretability. Based on a reasonable correlation between the two regularization parameters, an efficient solution path algorithm is developed for solving the proposed support vector machine. Experiments performed on the leukaemia data set are provided to verify the obtained results.

关键词： Support vector machines Support vector machine classification Electronic mail Programmable control Adaptive control Gene expression Learning systems Automatic control control systems Telecommunication control

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Distributed H∞ consensus control for networks of multiple agents with linear coupling dynamics

Distributed H∞ consensus control for networks of multiple a...

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SICE Annual Conference

作者： Yang Liu Yingmin Jia Junping Du Fashan Yu Department of Systems and Control Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper is devoted to the consensus control for a network of autonomous agents with high-dimension linear coupling dynamics and subject to external disturbances. By transforming the consensus control problem into an H infin control problem, we propose a distributed state feedback protocol, and obtain conditions in terms of linear matrix inequalities (LMIs) to ensure the consensus with a prescribed H infin performance level for networks with zero and nonzero communication delays, respectively. Furthermore, the undetermined feedback matrix of the proposed protocol is also solved. A numerical example is included to validate the theoretical results.

关键词： control systems Communication system control Protocols Multiagent systems Vehicle dynamics Automatic control Telecommunication control Electronic mail Linear feedback control systems State feedback

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Decentralized Excitation control of Multi-machine Multi-load Power Systems Using Hamiltonian Function Method

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Acta Automatica Sinica 2009年第7期35卷 919-925页

作者： Yan-Hong LIU Chun-Wen LI Yu-Zhen WANG School of Electrical Engineering Zhengzhou University Zhengzhou 450001 P. R. China Department of Automation Tsinghua University Beijing 100084 P. R. China Key Laboratory of Informationed Electric Apparatus in Henan State Zhengzhou 450002 P. R. China School of Control Science and Engineering Shandong University Jinan 250061 P. R. China

Using the Hamiltonian function method, we investigate the excitation control of multi-machine multi-load power systems presented by nonlinear diffierential algebraic equations. First, the power system is reformulated as a novel Hamiltonian realization structure via pre-feedback state control. Then, based on the dissipative Hamiltonian realization of the system, a decentralized nonlinear excitation control scheme is constructed. The stability of the closed loop system is analyzed as well. The proposed strategy takes advantage of the intrinsic properties especially including the internal power balance of the power system. Simulation illustrates the effectiveness of the control strategy.

关键词： Nonlinear differential algebraic systems multi-machine multi-load power systems dissipative Hamiltonian realization decentralized stabilization

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Robust fault tolerant H∞ control for a class of interval systems with delayed states

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of science and Technology (Natural science Edition) 2009年第SUPPL. 1期37卷 36-39页

作者： Zhang, Dengfeng Wang, Zhiquan Wang, Shubin School of Mechannical Engineering Nanjing University of Science and Technology Nanjing 210094 China School of Automation Nanjing University of Science and Technology Nanjing 210094 China College of Information and Control Engineering University Petroleum of China Dongying 257062 China

The problem of robust fault-tolerant control is investigated for a class of interval systems model with time-varying delays in states. The dynamics of actuator faults in the gain is described by an interval matrix. Based on robust H∞ control theory of uncertain systems, the exponential stability is proved and the time-delay dependent fault-tolerant H∞ control law is obtained by linear matrix inequality (LMI) technique. Simulative example illustrated the validity of the proposed method.

关键词： Linear matrix inequalities

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Particle Swarm Optimization in Solving Vehicle Routing Problem

Particle Swarm Optimization in Solving Vehicle Routing Probl...

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International Conference on Intelligent Computation Technology and automation, ICICTA

作者： Hai Shen Yunlong Zhu Ting Liu Li Jin College of Physics Science and Technology Shenyang Normal University Shenyang China Key Laboratory of Industrial Informatics Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China Key Laboratory of Industrial Informatics Shenyang Institute of Automation Chinese Academy and Sciences Beijing China Department of Automatic Control School of Information Science and Engineering Northeastern University Shenyang China Chinese Academy of Sciences Beijing Beijing CN

The vehicle routing problem (VRP) is a NP complete problem and is also a hot topic in the operational research. But traditional methods might suffer from slow convergence and the curse of large sizes, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO) is known to effectively solve engineering optimization problems. In this paper, the PSO in solving VRP is comprehensive surveyed from two basic aspects: the improved PSO algorithms and the particle encoding method. For each application, technical details that are required are all discussed. Finally, a summary is given together with suggestions for future research.

关键词： Particle swarm optimization Vehicles Routing automation Encoding Laboratories Computer industry Industrial control Informatics Educational institutions

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Intelligent modified predictive optimal control of reheater steam temperature in a large-scale boiler unit

Intelligent modified predictive optimal control of reheater ...

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IEEE General Meeting Power& Energy Society

作者： Kwang Y. Lee Liangyu Ma Chang-Jin Boo Won-Hee Jung Sung-Ho Kim Department of Electrical and Computer Engineering Baylor University Waco TX USA Automation Department School of Control Science and Engineering North China Electric Power University Baoding Hebei China Department of Electrical Engineering Cheju National University Jelu South Korea Corporate Research and Development Institute Doosan Heavy Industries and Construction Company Limited Taejon South Korea

A modified predictive optimal control (MPOC) scheme based on neural network modeling and particle swarm optimization (PSO) techniques is proposed in this paper for reheater steam temperature (RST) control of a large-scale boiler unit. A recurrent neural network is trained to directly model the temperature dynamic response of the reheater system. The neural network direct model is then used to evaluate the performance of the MPOC in search of the optimal control, where optimization is carried out with the PSO. A simplified PSO algorithm with search direction control is designed to find the nearest and optimal controls for the reheater steam temperature. To further improve the optimal search accuracy, each last-step prediction error between the direct model output and the actual RST is added to the current-step cost function to compensate for the model error. control tests on a full-scope simulator of a large scale power generating unit have shown the validity of the proposed method.

关键词： Optimal control Large-scale systems Boilers Predictive models Neural networks Temperature control Particle swarm optimization Recurrent neural networks Algorithm design and analysis Accuracy

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