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On Measures of Non-Integrability of Pfaffian Systems

IFAC Proceedings Volumes 1996年第1期29卷 2132-2137页

作者： Andrzej Banaszuk John Hauser Willem M. Sluis Richard M. Murray Department of Mathematics University of California Davis CA 95616-8633 Department of Electrical and Computer Engineering University of Colorado Boulder CO 80309-0425 Control and Dynamical Systems 104-44 California Institute of Technology Pasadena CA 91125 Division of Engineering and Applied Science California Institute of Technology Pasadena CA 91125

Many problems in nonlinear control theory (like, for instance, feedback linearization problem) leed to examination of integrability of a Pfaffian system. In a generic case a Pfaffian system is not integrable. Therefore, how to approximate non-integrable Pfafian systems by integrable ones and how this approximation can applied in practice appears to be a natural and important problem. In the present paper we establish some measures of non-integrability of Pfaffian system of arbitrary dimension and discuss their relation to approximations of non-integrable Pfaffian systems by integrable ones. Our work is motivated by expected applications to approximate feedback linearization of multi-input nonlinear systems.

关键词： Nonlinear systems differential geometry differential forms Pfaffian systems feedback linearization

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Learning augmented recursive estimation for uncertain nonlinear dynamical systems

Learning augmented recursive estimation for uncertain nonlin...

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IEEE International Symposium on Intelligent control (ISIC)

作者： S.C. Draper R.S. Mangoubi W.L. Baker Department of Electrical Engineering and Computer Science M.I.T. Cambridge MA USA Control and Dynamical Systems Division C. S. Draper Laboratories Inc. Cambridge MA USA Division of Engineering and Applied Sciences Harvard University Cambridge MA USA

This paper describes a learning augmented recursive estimation approach for nonlinear dynamical systems having unmodeled nonlinearities. Utilizing a passive spatially-localized learning system, an approximation of the unknown nonlinearity is synthesized online, based on state and parameter estimates from a nonlinear recursive estimator (an adaptive form of the extended Kalman filter). The learned model of the nonlinearity is used, in turn, to improve the performance of the recursive estimator. We demonstrate the approach on a second-order, mass-spring-damper system, where the spring stiffness is a nonlinear function of position. Simulation results indicate that, relative to more traditional adaptive estimation schemes, markedly improved estimation performance can be achieved.

关键词： Recursive estimation Nonlinear dynamical systems State estimation Learning systems Function approximation Filters Parameter estimation Springs Adaptive estimation Uncertainty

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A METHOD FOR ALGEBRAIC ANALYSIS OF THE TLM ALGORITHM

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 1995年第1期8卷 61-71页

作者： WITWIT, ARM WILKINSON, AJ PULKO, SH Department of Electronic Engineering The University of Hull Hull HU6 7RX U.K. Abdul Mehdi Witwit was born in Babylon in 1965. He graduated in Electronic Engineering from the Univeristy of Hull in 1990. He has recently submitted his Ph.D. thesis on the topic of meshing in TLM diffusion problems. Anthony James Wilkinson graduated from the niversity of Hull with a B.Sc. in Electronic Engineering in 1982 and a Ph.D. in adaptive control in 1987. He is currently a lecturer in the Department of Electronic Engineering where his research interests include TLM algorithms and computer control of magnetostrictive actuation. Susan Pulko obtained a B.Sc. in physics together with an ARCS from Imperial College (London) in 1977. This was followed by a Ph.D. from the University of Nottingham in 1981. Her current research interests centre on the TLM algorithm and on its application to a range of physical processes especially as applied to manufacturing. Current work involves development of the algorithm itself and TLM applications in the glass and ceramic industries.

An analogy is described between the TLM algorithm and discrete state-space control theory. The analogy is used to derive the characteristic equations corresponding to parameterized model structures. Characteristic equations corresponding to several widely used node structures are derived by this means and found to be consistent with the observed behaviour of corresponding TLM models. An example is given of the use of the analogy in the predictive mode.

关键词： Algorithms

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Steady‐state security evaluation of electrical power systems by means of artificial neural network

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European Transactions on Electrical Power 1995年第2期5卷 91-97页

作者： Chiodo, E. Menniti, D. Testa, A. Picardi, C. Elio Chiodo (1959) received the degree in Electronics Engineering in 1985 and the Ph.D. degree in Computational Statistics both from the University of Naplefltaly. He is a Researcher at the Department of Electrical Engineering of the University of Naples and a member of the Italian Statistical Society. His areas of interest include probabilistic methods applied to electric power systems analysis. (University of Naples Fedrrico 11. Electrical Engineering Dept.via Claudio 21 1-80125 Naplefltaly T +3981/7683226 Fax+3981/2396897) Daniele Menniti (1958) received the degree in Electrical Engineering from the University of Calabria. Cosenzataly and the Ph.D. degree in Electrical Engineering from the University of NapleslItaly in 1984 and 1989 respectively. He is a researcher at the Electronic. Computer and Systems Science Department of the University of Calabria. Italy. Hiscurrent research interests concern electric power system analysis real-time control and automation. (University of Calabria Electronic Computer and Systems Science Dep. Arcavacataji Rende (CS). 1-87036 CosenzdItaly T +39984/494707. Fax +39984/4947 13) Alfredo Testa (1950) received the degree in Electrical Engineering from the University of Naples/Italy in 1975. He is an Associate Professor in Electrical Power Systems at the Department of Electrical Engineering of the University of Naples. He is engaged in researches on electrical power systems reliability and harmonic analysis. (University of Naples Federico 11. Electrical Engineering Dep. via Claudio '2 1 1-80 I25 NapleslItaly T + 39 8 I/7 68 3'2 11. Fax+3981/2396897) Ciro Picardi (1949) received the degree in Electronics Engineering from the University of Naples/Italy in 1975. He is currently Associate Professor in Process Control at the Department of Electronic Computer and System Science of the University of Calabria. Italy. His current research interests are in the area of electrical drives robotics neural networks and fuzzy control. (University of Calabria Electronic. Compu

An artificial‐neural‐network (ANN) application for steady‐state security evaluation of electrical power systems is presented. Such application is based upon a combined use of a multilayer back‐propagation neural network and of an opportune electrical system model, previously proposed by some of the authors. In the paper, the definition of steady‐state security and the problems arising from its on‐line evaluation are briefly recalled. Then, the ANN utilized is described with particular reference to the solutions adopted by the authors. Afterwards, some remarks on the system model utilized are reported. Finally, numerical applications on the AEP‐14 bus system are presented and the results obtained with different ANN configurations are analyzed. Copyright © 1995 John Wiley & Sons, Ltd.

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Interactive analysis of multi-spectral images using a Hilbert curve

Interactive analysis of multi-spectral images using a Hilber...

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International Conference on Pattern Recognition

作者： S.-I. Kamata M. Niimi E. Kawaguchi Department of Computer Engineering Kyushu Institute of Technology Kitakyushu Japan Computer Science and Control Engineering Course Nagasaki Institute of Applied Science Japan

There have been many new developments in interactive analysis for multi-spectral images in the research of remote sensing. In general, the methods used are linear transformations such as principal component analysis. In this paper, the authors present a new interactive method for classifying multi-spectral images using a Hilbert curve which is a one-to-one mapping and preserves the neighborhood as much as possible. This method is based on a hierarchical histogram expression with different resolutions for the mapped one-dimensional data. The classification on this expression can be performed easily instead of using N-dimensional data directly. In order to realize the real time response from the system, the authors make use of data tables storing the addresses and the occurrences of data, etc. Here the address is defined by using the coordinates in N-dimensional space, and is made use of dealing with a part of mapping which can not preserve the neighborhood. In the experiments using LANDSAT image data, it is confirmed that the user can get the real time response from the system after once making the data tables.

关键词： Image analysis Multispectral imaging Remote sensing Real time systems Satellites Principal component analysis Histograms computer science Ear Displays

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A multi-temporal classification of multi-spectral images using a neural network

A multi-temporal classification of multi-spectral images usi...

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International Conference on Pattern Recognition

作者： S.-I. Kamata M. Niimi E. Kawaguchi Department of Computer Engineering Kyushu Institute of Technology Japan Computer Science and Control Engineering Course Nagasaki Institute of Applied Science Nagasaki Japan

The classification of remotely sensed multi-spectral data using classical statistical methods has been worked on for several decades. There have been many new developments in neural network (NN) research, and many new applications have been studied. It is well known that NN approaches have the ability to classify without assuming a distribution. The authors previously proposed an NN model to combine the spectral and spatial information of LANDSAT TM images. In this paper, the authors apply the NN approach with a normalization method to classify multi-temporal LANDSAT TM images in order to investigate the robustness of their approach. From the authors' experiments, they confirm that their approach is more effective for the classification of multi-temporal data than the original NN approach and maximum likelihood approach.

关键词： Multispectral imaging Neural networks Satellites Remote sensing Learning systems Pixel Signal processing computer science Statistical analysis Lakes

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Magnetic Bearing control Systems and Adaptive Forced Balancing

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IEEE control Systems 1994年第2期14卷 4-13页

作者： Shafai, B. Beale, S. LaRocca, P. Cusson, E. Department of Electrical and Computer Engineering Northeastern University Boston MA 02115 United States Brooks Automation Lowell MA 01851 United States Circuit Design and Applied Control Division MS 29 The Charles Stark Draper Laboratory Inc. Cambridge MA 02139 555 Technology Square United States

Active magnetic bearing (AMB) actuators support rotors without friction but require feedback control for stabilization and performance. We address the application of modern control techniques such as LQG/LTR, H/spl infin/, and QFT to AMB systems. We also introduce a novel method called adaptive forced balancing (AFB) which solves the problem of synchronous vibration caused by mass unbalance. Simulation and experimental results are included to show the performance of AFB as applied to single-end AMB suspensions (SISO systems). Finally, AFB with frequency tracking and its generalization for double-end AMB suspensions (MIMO systems) are briefly explored. © 1994 IEEE

关键词： Magnetic levitation Force control control systems Adaptive systems Programmable control Adaptive control Suspensions Actuators Friction Feedback control

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Robust synthesis of time-delay systems

Robust synthesis of time-delay systems

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IEEE Conference on Decision and control

作者： V.L. Kharitonov Minyue Fu Department Applied Mathematics and Control Theory Saint Petersburg State University Russia Department Electrical and Computer Engineering University of Newcastle NSW Australia

This paper considers the problem of robust stabilization for a class of time-delay systems which involve affine parametric perturbations. We first provide a result for testing the robust stability of such a system, an... 详细信息

关键词： Robustness Robust stability Polynomials control system synthesis Transfer functions Mathematics control theory Australia System testing Sufficient conditions

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A mathematical model for boundary input systems

A mathematical model for boundary input systems

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IEEE Conference on Decision and control

作者： H. Inaba H. Hinata Department of Information Science Tokyo Denki University Saitama Japan Computer Science & Control Engineering Course Nagasaki Institute of Applied Science Nagasaki Japan

This paper studies a mathematical model of general boundary input systems using the notion of fractional power of positive operators, and various properties of such systems are presented in the framework of semigroup approach. In particular, it is shown that every general boundary input system can be transformed into an equivalent distributed input system, and it is indicated that the equivalent system may be used to obtain various characterizations of the original general boundary input system.< >

关键词： Mathematical model Power system modeling State-space methods Feedback Hilbert space computer science control engineering Null space Kernel Solvents

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Target Detection and Localization from Bearing-Only and Bearing/range Measurements

Target Detection and Localization from Bearing-Only and Bear...

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IEEE Regional Conference on Aerospace control Systems

作者： L.G. Weiss S.C.A. Thomopoulos Applied Research Laboratory Pennsylvania State University PA USA Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University PA USA

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