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1) Ear Recognition based on 2D Images
Li Yuan Zhi-chun Mu
Univ. of Sci. & Technol. Beijing, Beijing
Link: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4401941
2) Compound Structure Classifier System for Ear Recognition
Haijun Zhang Zhichun Mu
Dept. of Autom., Shenyang Inst. of Aeronaut. Eng., Shenyang
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4636551
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[1] Neuro-sliding mode control with its applications to seesaw systems
Chun-Hsien Tsai; Hung-Yuan Chung; Fang-Ming Yu
Neural Networks, IEEE Transactions on
Volume 15, Issue 1, Jan. 2004 Page(s):124 - 134
Digital Object Identifier 10.1109/TNN.2003.811560
Summary:This paper proposes an approach of cooperative control that is based on the concept of combining neural networks and the methodology of sliding mode control (SMC). The main purpose is to eliminate the chattering phenomenon. Next, the system performance can be improved by using the method of SMC. In the present approach, two parallel Neural Networks are utilized to realize a neuro-sliding mode control (NSMC), where the equivalent control and the corrective control are the outputs of neural network 1 and neural network 2, respectively. Based on expressions of the SMC, the weight adaptations of neural network can be determined. Furthermore, the gradient descent method is used to minimize the control force so that the chattering phenomenon can be eliminated. Finally, experimental results are given to show the effectiveness and feasibility of the approach.
[2] Intelligent Sliding-Mode Control Using RBFN for Magnetic Levitation System
Faa-Jeng Lin; Li-Tao Teng; Po-Huang Shieh
Industrial Electronics, IEEE Transactions on
Volume 54, Issue 3, June 2007 Page(s):1752 - 1762
Digital Object Identifier 10.1109/TIE.2007.894710
Summary:An intelligent sliding-mode control system using a radial basis function network (SMCRBFN) is proposed to control the position of a levitated object of a magnetic levitation system to compensate the uncertainties including the friction force in this study. First, the dynamic model of the magnetic levitation system is derived. Then, a sliding-mode approach is proposed to compensate the uncertainties that occurred in the magnetic levitation system. Moreover, to relax the requirement of uncertainty bound in the design of a tra***ional sliding-mode control system and further increase the robustness of the magnetic levitation system, a radial basis function network estimator is proposed to estimate the uncertainties of the system dynamics online. The effectiveness of the proposed control scheme is verified by some experimental results. With the proposed SMCRBFN system, the position of the levitated object of the magnetic levitation system possesses the advantages of good transient control performance and robustness to uncertainties for tracking periodic trajectories
[3] Application of neural network in sliding mode control
Mkrttchian, V.; Lazaryan, A.
Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on
Volume , Issue , 2000 Page(s):653 - 657
Digital Object Identifier 10.1109/CCA.2000.897504
Summary:In this paper, a combination of neural network with sliding mode control (SMC) is proposed. As a result, the chattering is eliminated and error performance of SMC is improved. In such an approach two parallel neural networks (NNs) are proposed to realize the SMC. The equivalent control and the corrective control term of SMC are the outputs of the NNs. The training algorithms applied to NNs are based on the SMC equation with a gradient descent method to minimize the control and chattering while optimizing the error performance. In this paper, a sliding mode neurocontroller in power systems is proposed, and experimental results are presented. Two parallel NNs are used to realize the neuro-SMC. To increase the first neural network structure flexibility hidden layer neuron pruning and node splitting algorithms are considered

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Rice Hulls-To-Silicon Revisited
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4059822&isnumber=4059528
An innovative method for insulators washing in energised lines
Portillo, M. Fernandez, L. Andres, A.
RED Electr. de Espana;
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=14674&isnumber=668342
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Hybrid ARQ and adaptive modulation and coding schemes for high speed downlink packet access
Dottling, M.; Michel, J.; Raaf, B.
Personal, Indoor and Mobile Radio Communications, 2002. The 13th IEEE International Symposium on
Volume 3, Issue , 15-18 Sept. 2002 Page(s): 1073 - 1077 vol.3
Digital Object Identifie
HARQ and AMC schemes for high speed downlink packet access
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nhờ bác giúp 3 tài liệu này, vô cùng cám ơn, email của em là little_crab220587@yahoo.com
[1] Design of main steam temperature control system of sub-critical 600MW power unit and its application
Feng Jian Kao Zhi-qiang Han Zhong-xu Dang Zeng-kui Liang Zhen-wu Xue Jian-hong
Beijing GuoDian Zhishen Control Technol. Co. Ltd., Beijing;
This paper appears in: Control and Decision Conference, 2008. CCDC 2008. Chinese
Publication Date: 2-4 July 2008
On page(s): 4920-4924
Location: Yantai, Shandong,
ISBN: 978-1-4244-1733-9
INSPEC Accession Number: 10143142
Digital Object Identifier: 10.1109/CCDC.2008.4598263
Current Version Published: 2008-08-12
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4598263
[2] Design and implementation of a Laguerre self-tuner for boilerdrum-level control
Elshafei, A.L.; Abdel-Magied, M.; Rashad, H.; Bahgat, A.
American Control Conference, 1995. Proceedings of the
Volume 3, Issue , 21-23 Jun 1995 Page(s):2024 - 2028 vol.3
Digital Object Identifier
Summary:Boiler drum-level control is an important and difficult task. The system is non-minimum phase. As a tra***ional PID controller is not the best choice for such systems, a Laguerre based self-tuner is being tried out. The advantages of using Laguerre models are discussed. Then, a predictive controller based on those models is derived and analyzed. A simulation example illustrates the design procedure and compares the Laguerre self-tuner to a tra***ional PID controller
ieeexplore.ieee.org/iel3/3920/11352/00531247.pdf
[3] Multivariable feedwater control design for a steam generator
Younkins, T.D.; Chow, J.H.
Control Systems Magazine, IEEE
Volume 8, Issue 2, Apr 1988 Page(s):77 - 80
Digital Object Identifier 10.1109/37.1878
Summary:A multivariable feedwater control design for drum water-level regulation in a heat-recovery steam generator is presented. The control design is based on a projective output feedback scheme and is used to coordinate the tandem-connected feedwater valves of a low-pressure and a high-pressure drum. One of the design objectives is to minimize the blowdown from the drums during start-ups. Results demonstrating the control performance and the improvement over a tra***ional single-loop feedwater control design are shown
ieeexplore.ieee.org/iel1/37/114/00001878.pdf?arnumber=1878

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Controller design for direct torque controlled space vector modulated (DTC-SVM) induction motor drives
Zelechowski, M.; Kazmierkowski, M.P.; Blaabjerg, F.
Industrial Electronics, 2005. ISIE 2005. Proceedings of the IEEE International Symposium on
Volume 3, Issue , 20-23 June 2005 Page(s): 951 - 956 vol. 3
Digital Object Identifier 10.1109/ISIE.2005.1529052
Summary: In this paper two different methods of PI controllers for direct torque controlled-space vector modulated induction motor drives have been studied. The first one is simple method based only on symmetric optimum criterion. The second approach takes into account the full model of induction motor including rotor voltage equation and uses root locus method. Some simulated and experimental oscillograms that illustrate properties of the presented controller design methods are shown.

Simulation of a 6/4 switched reluctance motor based onMatlab/Simulink environment
Soares, F. Costa Branco, P.J.
Inst. Superior Tecnico, Lisbon;
This paper appears in: Aerospace and Electronic Systems, IEEE Transactions on
Publication Date: Jul 2001
Volume: 37, Issue: 3
On page(s): 989-1009
ISSN: 0018-9251
References Cited: 18
CODEN: IEARAX
INSPEC Accession Number: 7059392
Digital Object Identifier: 10.1109/7.953252
Current Version Published: 2002-08-07
Link : http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?tp=&arnumber=953252&isnumber=20611
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