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A Recursive Estimation Algorithm For Identification Of Dynamic Systems
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Book Synopsis A Recursive Estimation Algorithm for Identification of Dynamic Systems by : Toney R. Perkins
Download or read book A Recursive Estimation Algorithm for Identification of Dynamic Systems written by Toney R. Perkins and published by . This book was released on 1974 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: The report deals with the identification of unknown parameters in dynamic systems. In modeling a physical system, the problem of identifying the dynamics of a system are often encountered. The developed algorithm provides a tool to model all or parts of a dynamic system using input-output data sets from a real system. The methodology and techniques of this algorithm are based upon linear recursive estimation theory. The theoretical foundation and the pragmatics of using the ensemble data to estimate the unknown parameters are discussed at length in the development of the algorithm. As an application of the algorithm, experimental data from a man-in-the-loop simulation is used to estimate the parameters of a single axis model of the gunner. The tracking response of the gunner model compare favorably with data obtained from the simulation. (Modified author abstract).
Book Synopsis Recursive Estimation and Time-Series Analysis by : Peter C. Young
Download or read book Recursive Estimation and Time-Series Analysis written by Peter C. Young and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has grown out of a set of lecture notes prepared originally for a NATO Summer School on "The Theory and Practice of Systems ModelLing and Identification" held between the 17th and 28th July, 1972 at the Ecole Nationale Superieure de L'Aeronautique et de L'Espace. Since this time I have given similar lecture courses in the Control Division of the Engineering Department, University of Cambridge; Department of Mechanical Engineering, University of Western Australia; the University of Ghent, Belgium (during the time I held the IBM Visiting Chair in Simulation for the month of January, 1980), the Australian National University, and the Agricultural University, Wageningen, the Netherlands. As a result, I am grateful to all the reci pients of these lecture courses for their help in refining the book to its present form; it is still far from perfect but I hope that it will help the student to become acquainted with the interesting and practically useful concept of recursive estimation. Furthermore, I hope it will stimulate the reader to further study the theoretical aspects of the subject, which are not dealt with in detail in the present text. The book is primarily intended to provide an introductory set of lecture notes on the subject of recursive estimation to undergraduate/Masters students. However, the book can also be considered as a "theoretical background" handbook for use with the CAPTAIN Computer Package.
Book Synopsis Identification of Dynamic Systems by : Rolf Isermann
Download or read book Identification of Dynamic Systems written by Rolf Isermann and published by Springer Science & Business Media. This book was released on 2010-11-22 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
Book Synopsis Recursive Estimation and Time-Series Analysis by : Peter C. Young
Download or read book Recursive Estimation and Time-Series Analysis written by Peter C. Young and published by Springer Science & Business Media. This book was released on 2011-08-04 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the MatlabTM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in MatlabTM and its other toolboxes. The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject; or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.
Book Synopsis Modelling and Parameter Estimation of Dynamic Systems by : J.R. Raol
Download or read book Modelling and Parameter Estimation of Dynamic Systems written by J.R. Raol and published by IET. This book was released on 2004-08-13 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation.
Book Synopsis Recursive Identification and Parameter Estimation by : Han-Fu Chen
Download or read book Recursive Identification and Parameter Estimation written by Han-Fu Chen and published by CRC Press. This book was released on 2014-06-23 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation problems arising from diverse areas. Supplying a systematic description of recursive estimation methods, it provides rigorous theoretical analysis of recursive solutions to problems of stochastic systems. Presenting the material and proposed algorithms in a manner that makes it easy to understand, the book provides readers with the modeling and identification skills required for successful theoretical research and effective applications.
Book Synopsis Theory and Practice of Recursive Identification by : Lennart Ljung
Download or read book Theory and Practice of Recursive Identification written by Lennart Ljung and published by MIT Press (MA). This book was released on 1985 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and systematic framework for developing, describing, and analyzing such recursive algorithms.
Book Synopsis Numerical Solution of Two Point Boundary Value Problems by : Herbert B. Keller
Download or read book Numerical Solution of Two Point Boundary Value Problems written by Herbert B. Keller and published by SIAM. This book was released on 1976-01-01 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lectures on a unified theory of and practical procedures for the numerical solution of very general classes of linear and nonlinear two point boundary-value problems.
Book Synopsis Optimal Estimation of Dynamic Systems by : John L. Crassidis
Download or read book Optimal Estimation of Dynamic Systems written by John L. Crassidis and published by CRC Press. This book was released on 2004-04-27 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation. Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals receiv
Book Synopsis Identification of Continuous-Time Systems by : Allamaraju Subrahmanyam
Download or read book Identification of Continuous-Time Systems written by Allamaraju Subrahmanyam and published by CRC Press. This book was released on 2019-12-06 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.
Book Synopsis Identification and System Parameter Estimation 1982 by : G. A. Bekey
Download or read book Identification and System Parameter Estimation 1982 written by G. A. Bekey and published by Elsevier. This book was released on 2016-06-06 with total page 869 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identification and System Parameter Estimation 1982 covers the proceedings of the Sixth International Federation of Automatic Control (IFAC) Symposium. The book also serves as a tribute to Dr. Naum S. Rajbman. The text covers issues concerning identification and estimation, such as increasing interrelationships between identification/estimation and other aspects of system theory, including control theory, signal processing, experimental design, numerical mathematics, pattern recognition, and information theory. The book also provides coverage regarding the application and problems faced by several engineering and scientific fields that use identification and estimation, such as biological systems, traffic control, geophysics, aeronautics, robotics, economics, and power systems. Researchers from all scientific fields will find this book a great reference material, since it presents topics that concern various disciplines.
Book Synopsis Topics in Identification and Distributed Parameter Systems by : Erhard Bühler
Download or read book Topics in Identification and Distributed Parameter Systems written by Erhard Bühler and published by Springer-Verlag. This book was released on 2013-07-02 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Identification of Dynamic Systems by : Richard E. Maine
Download or read book Identification of Dynamic Systems written by Richard E. Maine and published by . This book was released on 1985 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Identification of Continuous Systems by : Heinz Unbehauen
Download or read book Identification of Continuous Systems written by Heinz Unbehauen and published by . This book was released on 1987 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing together important advances in the field of continuous system identification, this book deals with both parametric and nonparametric methods. It pays special attention to the problem of retaining continuous model parameters in the estimation equations, to which all the existing techniques used in estimating discrete models may be applied. It is aimed at both the academic researcher and the control engineer in industry. The techniques covered range from certain simple numerical or graphical methods applicable to some of the frequently encountered model forms, to attractive recursive algorithms for continuous model identification suitable for real time implementation. These include the recent methods based on orthogonal functions such as those of Walsh and Poisson moment functionals. Some techniques based on stable model adaptation principles are also presented and illustrated.
Book Synopsis New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment with Application to Frequency Estimation and System Identification by : Wing-Yi Lau
Download or read book New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment with Application to Frequency Estimation and System Identification written by Wing-Yi Lau and published by . This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment With Application to Frequency Estimation and System Identification" by Wing-yi, Lau, 劉穎兒, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of the Thesis Entitled New Recursive Parameter Estimation Algorithms in Impulsive Noise Environment with Application to Frequency Estimation and System Identification submitted by Wing-Yi LAU for the degree of Master of Philosophy at The University of Hong Kong in August 2006 Least-squares (LS) parameter estimation algorithms are very useful in applications such as frequency estimation and system identification. In order to support online applications with a much lower arithmetic complexity, new QR-decomposition-(QRD)-based recursive algorithms for estimating the frequency components of multiple sinusoids based on the linear prediction (LP) approach and identifying the system under colored noise are proposed in this study. Furthermore, since the LS-based algorithms are sensitive to impulsive noise, new QRD- based recursive algorithms with M-estimation are introduced so that the robustness of the proposed algorithms can be improved and the impulsive noise can be de-emphasized and removed effectively. Simulation results show that the proposed algorithms give better performance with lower arithmetic complexity than the conventional LS algorithms. Besides parameter estimation, this thesis presents a new Kalman filter-based power spectral density (PSD) estimation algorithm for nonstationary pressure signals. The pressure signals are modeled as an autoregressive (AR) process and a stochastically perturbed difference equation constraint model is used to describe the dynamics of the AR coefficients. The proposed algorithm uses variable numbers of measurements to estimate the coefficients instead of fixed number of measurements in the conventional Kalman filter. In addition, the number of the measurements of the proposed algorithm is adaptively chosen by the intersection of confidence intervals (ICI) rule. Simulation results show that the proposed algorithm achieves a better time-frequency resolution and better tracking performance than the conventional Kalman filter-based algorithm which only updates the fixed number of measurements for each estimation. The above algorithms are proposed for linear models. For nonlinear models, this thesis proposes a new recursive parameter estimation algorithm for the nonlinear adaptive function coefficients autoregressive (AFAR) models. The AFAR model is a generalization of the familiar linear AR model and it is suitable for modeling nonlinear correlation of a time series governed by unknown nonlinearities. The nonlinearities are estimated using local polynomial regression (LPR), which gives a better bias-variance tradeoff than traditional polynomial approximations. Experimental results show that the model parameters can be estimated accurately using the proposed method. Moreover, using the close relationship between a simplified AFAR model and the nonlinear Wiener system, a new recursive algorithm for identifying the nonlinear Wiener system is proposed. Another new recursive algorithm for identifying the nonlinear Wiener-Hammerstein system (WHS) model is also proposed using the relationship between the AFAR model and the WHS model. DOI: 10.5353/th_b3759586 Subjects: Signal processing - Statistical methods Parameter estimation Algorithms
Book Synopsis The Fractional Calculus Theory and Applications of Differentiation and Integration to Arbitrary Order by :
Download or read book The Fractional Calculus Theory and Applications of Differentiation and Integration to Arbitrary Order written by and published by Elsevier. This book was released on 1974-09-05 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; andmethods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory.As a result, the book represents a blend of new methods in general computational analysis,and specific, but also generic, techniques for study of systems theory ant its particularbranches, such as optimal filtering and information compression. - Best operator approximation,- Non-Lagrange interpolation,- Generic Karhunen-Loeve transform- Generalised low-rank matrix approximation- Optimal data compression- Optimal nonlinear filtering
Book Synopsis Discrete Linear Control Systems by : V.N. Fomin
Download or read book Discrete Linear Control Systems written by V.N. Fomin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: One service mathematics has rendered the 'Bt mm ... - si j'avait su comment en revenir, human race. It has put common sense back je n'y serais point alIe.' Jules Verne where it belongs. on the topmost shelf next to the dusty canister labelled 'discarded non The series is divergent; therefore we may be sense'. Eric T. Bell able to do something with it. O. Heavisidc Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
