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A Study On Iterative Learning control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup-Norm

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Asian Journal of control 2008年第1期4卷

作者： Kwang-Hyun Park Zeungnam Bien Division of EE Department of EECS Korea Advanced Institute of Science and Technology 373–1 Kusong-dong Yusong-gu Taejon 305–701 Korea. Zeungname Bien:received the B.S. degree in electronics engineering from Seoul National University Seoul Korea in 1969 and the M.S. and Ph.D. degrees in electrical engineering from the University of Iowa Iowa City Iowa U.S.A. in 1972 and 1975 respectively. During 1976–1977 academic years he taught as assistant professor at the Department of Electrical Engineering University of Iowa. Then Dr. Bien joined Korea Advanced Institute of Science and Technology summer 1977 and is now Professor of Control Engineering at the Department of Electrical Engineering and Computer Science KAIST. Dr. Bien was the president of the Korea Fuzzy Logic and Intelligent Systems Society during 1990–1995 and also the general chair of IFSA World Congress 1993 and for FUZZ-IEEE99 respectively. He is currently co-Editor-in-Chief for International Journal of Fuzzy Systems (IJFS) Associate Editor for IEEE Transactions on Fuzzy Systems and a regional editor for the International Journal of Intelligent Automation and Soft Computing. He has been serving as Vice President for IFSA since 1997 and is now Chief Chairman of Institute of Electronics Engineers of Korea and Director of Humanfriendly Welfare Robot System Research Center. His current research interests include intelligent control methods with emphasis on fuzzy logic systems service robotics and rehabilitation engineering and large-scale industrial control systems. Kwang-Hyun Park:received the B.S. M.S. and Ph.D. degrees in electrical engineering and computer science from KAIST Korea in 1994 19997 and 2001 respectively. He is now a researcher at Human-friendly Welfare Robot System Research Center. His research interests include learning control machine learning human-friendly interfaces and service robotics.

It has been found that some huge overshoot in the sense of sup-norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ-norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup-norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.

关键词： Iterative learning control monotone convergence learning interval sup-norm

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AUTOMATIC BRAIN TUMOR SEGMENTATION USING TISSUE DIFFISIVITY CHARACTERISTICS

AUTOMATIC BRAIN TUMOR SEGMENTATION USING TISSUE DIFFISIVITY ...

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IEEE International Symposium on Biomedical Imaging

作者： Azadeh Yazdan-Shahmorad Hesamoddin Jahanian Suresh Patel Hamid Soltanian-Zadeh Radiology Department Henry Ford Health System Medical Image Analysis Laboratory Detroit MI USA Electrical and Computer Engineering Department Wayne State University Detroit MI USA Biomedical Engineering Department University of Michigan Ann Arbor MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department Faculty of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424406715;1424406714

Water diffusion measurements have been shown to be sensitive to tissue cellular size, extra cellular volume, and membrane permeability. Therefore, diffusion tensor imaging (DTI) by MRI can be used to characterize highly cellular regions of tumors versus acellular regions, distinguishing cystic regions from solid regions. An automatic segmentation method is proposed in this paper based on a multi-phase clustering algorithm to segment the brain tumors in a feature space extracted from DTI images. The algorithm is applied on images of a total of 20 patients with 4 different types of tumors. The tumor region segmentation was 92% accurate based on the segmentation results using anatomical images and 100% accurate based on biopsy results. In general, the segmentation results obtained by the proposed method revealed a strong agreement with the biopsy results and anatomical images, providing support for the accuracy and robustness of the proposed feature space and the segmentation procedure.

关键词： Neoplasms Image segmentation Diffusion tensor imaging Clustering algorithms Biopsy Permeability measurement Volume measurement Size measurement Biomembranes Magnetic resonance imaging

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Data modeling for content-based support environment (C-BASE): Application on epilepsy data mining

Data modeling for content-based support environment (C-BASE)...

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17th IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007

作者： Siadat, Mohammad-Reza Soltanian-Zadeh, Hamid Fotouhi, Farshad Eetemadi, Ameen Elisevich, Kost Department ofComputer Science and Engineering Oakland University Rochester MI 48309 United States Radiology Image Analysis Lab. Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Proc. Center of Excellence Dept. of Elec. and Comp. Eng. Univ. of Tehran Tehran 14395-515 Iran Department of Computer Science Wayne State University Detroit MI 48202 United States Department of Neurosurgery Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)0769530192

Data Modeling is an essential first step for data preparation in any data mining procedure. Conventional entity-relational (E-R) data modeling is lossy, irreproducible, and time-consuming especially when dealing with unstructured image data associated with complex systems like the human brain. We propose a methodological framework for more objective E-R data modeling by eliminating the structured content-dependent metadata associated with the unstructured data. The proposed method is applied to epilepsy-related image data and a system called the human brain image database system (HBIDS) is developed accordingly. Supported with navigation, segmentation, data fusion, and feature extraction modules, HBIDS provides a content-based support environment (C-BASE). Such an environment potentially provides an unlimited (ad hoc) query support with a reproducible and efficient database schema. Switching between different modalities of data, while confining the feature extractors within the object(s) of interest, HBIDS yields anatomically specific query results. The price of such scheme is large storage requirements and relatively high computational cost. Examples of navigation through unstructured image data and content-based retrieval are presented in this paper. The results show the potential of HBIDS in content-based data management for decision support systems in real life medical applications. © 2007 IEEE.

关键词： Data mining

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Special Issue on Variable Structure system control — New Designs and Applications

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Asian Journal of control 2008年第4期5卷

作者： Prof. Jian-Xin Xu Prof. Leonid Fridman Department of Electrical and Computer Eng. National University of Singapore 4 Engineering Drive 3 Singapore 117576 Tel +65 6874-2566 Fax +65 6779-1103 Dr Jian-Xin Xu received his Bachelor degree from Zhejiang University China in 1982. He attended the University of Tokyo Japan where he received his Master's and Ph.D. degrees in 1986 and 1989 respectively. All his degrees are in Electrical Engineering. He worked for one year in the Hitachi research Laboratory Japan and for more than one year in Ohio State University U.S.A. as a Visiting Scholar. In 1991 he joined the National University of Singapore and is currently an associate professor in the Department of Electrical Engineering. His research interests lie in the fields of learning control variable structure control fuzzy logic control discontinuous signal processing and applications to motion control and process control problems. He is the associate editor of Asian Journal of Control member of TC on variable structure systems and sliding mode control of IEEE Control Systems Society and a senior member of IEEE. He has produced more than 90 peer-refereed journal papers near 160 technical papers in conference proceedings and authored/edited 4 books. Division de Estudios de Posgrado Facultad de Ingenieria National Autonomous University of Mexico DEP-FI UNAM Edificio “A” Circuito Exterior Ciudad Universitaria A. P. 70–256 C.P.04510 Mexico D.F. Mexico Tel +52 55 56223014 Fax +52 55 56161719 Dr. Leonid M. Fridman received his M.S in mathematics from Kuibyshev (Samara) State University Russia Ph.D. in Applied Mathematics from Institute of Control Science (Moscow) and Dr. of Science degrees in Control Science from Moscow State University of Mathematics and Electronics in 1976 1988 and 1998 respectively. In 1976–1999 Dr. Fridman was with the Department of Mathematics at the Samara State Architecture and Civil Engineering Academy Samara Russia. In 2000–2002 he was with the Department of Postgraduate Study and Investigations at the Chihuahu

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A Brief Overview of the Complex Biological and engineering Networks

A Brief Overview of the Complex Biological and Engineering N...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Jinhu Lu Derong Liu Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and System Science Chinese Academy and Sciences Beijing China Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA

Over the last few decades, complex networks have been intensively studied throughout many fields of science, especially in biological and engineering sciences. This paper briefly reviews the main advances in the complex biological and engineering networks, aiming to bridge the gap between the complex biological and engineering networks. Biologists pay more attention to the mechanisms and local dynamics of individuals, however, engineers are more interesting in the global dynamical behaviors. It is the time for the biologists and engineers to work together for better understanding the complex networks.

关键词： Biological system modeling Complex networks Mathematical model Biology Genetics Power system modeling Bridge circuits Evolution (biology) computer networks Power engineering computing

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Integrating Attribute and Status Constraint into the RBAC Model for Access control in Ubiquitous systems

Integrating Attribute and Status Constraint into the RBAC Mo...

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International Conference on Future Generation Communication and Networking (FGCN)

作者： Deqing Zou Jong Hyuk Park Tai-hoon Kim Xueguang Chen Cluster and Grid Computing Laboratory & Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computer Engineering Kyungnam University Masan Gyeongsangnam South Korea Hannam University South Korea Department of Control Science and Engineering Huazhong University of Science and Technology China

It now becomes a trend to implement the interconnections between resources as well as services in ubiquitous systems. Attribute-based authorization mechanisms, protocols and systems are gaining in popularity, such as SAML, XACML, Shibboleth, etc. However, their management efficiency could be further improved. The Role-based Access control (RBAC) mechanism is widely accepted as a general mechanism for authorization management. However, RBAC is still not flexible enough to address various application scenarios in ubiquitous systems. We propose a new architecture for access control in ubiquitous systems that impose attribute and status constraints on the RBAC model, which can significantly enhance the generality and flexibility of authorization by integrating the advantages of RBAC and attributed- based access control models. Moreover, the state mechanism proposed in this architecture captures the states of the authorization elements so as to reflect the outcomes of the authorization control. Finally, we analyze the flexibility and generality of this architecture in ubiquitous systems.

关键词： Access control Authorization Permission Grid computing Pervasive computing Access protocols Application software Markup languages computer science control system analysis

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Automatic Self-Commissioning for Secondary-Saliencies Decoupling in Sensorless-controlled AC Machines Using Structured Neural Networks

Automatic Self-Commissioning for Secondary-Saliencies Decoup...

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2007 IEEE International Symposium on Industrial Electronics (ISIE 2007), vol.6

作者： Pablo Garcia David Reigosa Fernando Briz Dejan Raca Robert D. Lorenz Department of Electrical Computer & System Engineering University of Oviedo Gijon Spain Power Control Systems MagneTek Inc. Menomonee Falls WI USA Wisconsin Electric Machines and Power Electronics Consortium (WEMPEC) Depts. of Mechanical Engineering and Electrical & Computer Engr University of Wisconsin Madison Madison WI USA

The focus of this paper is secondary-saliency decoupling in carrier signal injection-based sensorless control of AC machines using structured neural networks. Structured neural networks are utilized for automatic commissioning and decoupling of secondary saliencies including saturation-induced saliencies. Automatic commissioning process is necessary for easy implementation and for acceptance of the carrier signal injection-based sensorless control by drives industry. In comparison with classical compensation methods, such as lookup tables, this technique has advantages of reducing commissioning time and automating the process. These advantages are result of a physics-based design of structured neural networks, which is responsible for their scalability, and moderate size and complexity. In comparison with traditional neural networks, structured neural networks are simpler, physically insightful, less computationally intensive and easier to train.

关键词： AC machines Neural networks Signal processing Frequency estimation Sensorless control Position measurement Table lookup Voltage Power engineering and energy Saturation magnetization

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Grid Security Interoperation between CGSP and VEGA

Grid Security Interoperation between CGSP and VEGA

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International Conference on Future Generation Communication and Networking (FGCN)

作者： Deqing Zou Hai Jin Xueguang Chen Zongfen Han Cluster and Grid Computing Laboratory Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769530482;0769530486

Grid computing emerges as an effective technology to couple geographically distributed resources and solve large-scale computational problems in wide area networks. There are several popular grid platforms, such as UNICORE and Globus Toolkit. Many famous grid projects are constructed with these platforms, each of which manages different distributed resources. In order to aggregate resources managed by different grid platforms, it is necessary to implement the interoperation among these grid platforms. Security interoperation is one of key issues for the interoperation. CGSP (ChinaGrid Support Platform) and VEGA are two popular grid platforms in China. To achieve security interoperation between these two platforms, four mapping policies, including user-user mapping, user-agora mapping, role-user mapping, role-agora mapping, are proposed in this paper. The security interoperation process is proposed based on SAML specification and the mapping policies. We also analyze the flexibility of mapping policies and the security of the interoperation process.

关键词： Security Resource management Grid computing Authentication Large-scale systems computer networks Distributed computing Wide area networks Web services Middleware

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AN ASYMPTOTIC SECOND-ORDER SMOOTH SLIDING MODE control

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Asian Journal of control 2008年第4期5卷

作者： Yuri B. Shtessel Ilya A. Shkolnikov Mark D.J. Brown Department of Electrical and Computer Engineering University of Alabama in Huntsville Huntsville AL 35899 USA. Z/I Imaging Corporation 301 Cochran Road Suite 9 Huntsville AL 35824 USA. Principal Engineer Sikorsky Aircraft Corporation 6900 Main Street Stratford CT 06615 USA. Dr. Mark Brown received the PhD. degree in Electrical Engineering from the University of Alabama in Huntsville in 2001. He is the principal scientist supporting the development of technology for test and evaluation Prior to this Dr. Brown was the lead researcher developing the weapons control algorithms for the Comanche RAH-66 helicopter at Sikorski. He has also led the development of missile defense system technologies including research into the development of flight control algorithms at the U.S. Army Space and Missile Defense Command. Dr. Brown is currently employed by Scientific Research Corporation.

Presented is a method of smooth sliding mode control design to provide for an asymptotic second-order sliding mode on the selected sliding surface. The control law is a nonlinear dynamic feedback that in absence of unknown disturbances provides for an asymptotic second-order sliding mode. Application of the second-order disturbance observer in a combination with the proposed continuous control law practically gives the second-order sliding accuracy in presence of unknown disturbances and discrete-time control update. The piecewise constant control feedback is “smooth” in the sense that its derivative numerically taken at sampling rate does not contain high frequency components. A numerical example is presented.

关键词： Sliding mode control second order sliding mode sliding mode observer

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Robust quadratic optimal control of uncertain TS-fuzzy-model-based dynamic systems

Robust quadratic optimal control of uncertain TS-fuzzy-model...

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IEEE International Conference on systems, Man and Cybernetics

作者： Wen-Hsien Ho Jinn-Tsong Tsai Tung-Kuan Liu Jyh-Horng Chou Department of Medical Information Management Kaohsiung Medical University Taiwan Department of Computer Science National Ping Tung University of Education Taiwan Department of Mechanical and Automation Engineering National Kaohsiung First University of Science and Technology Taiwan Institute of System Information and Control National Kaohsiung First University of Science and Technology Kaohsiung Taiwan

This paper considers the design problem of the robust quadratic-optimal parallel-distributed-compensation (PDC) controllers for the Takagi-Sugeno (TS) fuzzy-model- based control systems with both elemental parametric uncertainties and norm-bounded approximation error. An integrative method, which complementarily fuses the robust stabilizability condition, the orthogonal-functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA), is presented in this paper to design the robust quadratic-optimal PDC controllers, in which the robust stabilizability condition is proposed in terms of linear matrix inequalities (LMIs).

关键词： Robust control Optimal control Nonlinear control systems control systems Uncertainty Approximation error Fuzzy control Fuzzy systems Algorithm design and analysis Nonlinear dynamical systems

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