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Author :
Publisher :
ISBN 13 :
Total Pages : 6 pages
Book Rating : 4.:/5 (916 download)
Download or read book Maximum-likelihood parameter estimation for general non-linear dynamic systems written by and published by . This book was released on 1987 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : W. J. H. Stortelder
Publisher :
ISBN 13 :
Total Pages : 196 pages
Book Rating : 4.F/5 ( download)
Download or read book Parameter Estimation in Nonlinear Dynamic Systems written by W. J. H. Stortelder and published by . This book was released on 1998 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Walter Johannes Henricus Stortelder
Publisher :
ISBN 13 : 9789074795913
Total Pages : 175 pages
Book Rating : 4.7/5 (959 download)
Download or read book Parameter estimation in nonlinear dynamical systems written by Walter Johannes Henricus Stortelder and published by . This book was released on 1998 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jeremy Blackwell
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (227 download)
Download or read book A Maximum Likelihood Parameter Estimation Program for General Non-linear Systems (U) written by Jeremy Blackwell and published by . This book was released on 1987 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: A computer program has been developed for the Maximum Likelihood estimation of parameters in general non-linear systems. Sensitivity matrix elements are calculated numerically, overcoming the need for explicit sensitivity equations. Parameters such as break points and time shifts are successfully determined using both simulated and actual test data. Keywords: Non linear systems, Time lag, Drop tests, Parameter estimation, Maximum likelihood, Landing gear.
Author : J Blackwell
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (946 download)
Download or read book A Maximum Likelihood Parameter Estimation Progam for General Non-linear Systems written by J Blackwell and published by . This book was released on 1988 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : L. D. Attaway
Publisher :
ISBN 13 :
Total Pages : 88 pages
Book Rating : 4.:/5 (731 download)
Download or read book Maximum-likelihood Prediction and Estimation for Nonlinear Dynamic Systems written by L. D. Attaway and published by . This book was released on 1968 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method is given for determining the system state using noise-corrupted observations of a non-linear dynamic invector process, with a numerical application to radar observation of a reentry body. The study examined the feasibility of numerically solving the vector-differential equations satisfied by the maximum-likelihood estimator. The maximum-likelihood estimate is that initial condition which minimizes a certain functional on itself, on the observation, and on the a priori statistics.
Author : Dan Simon
Publisher : John Wiley & Sons
ISBN 13 : 0470045337
Total Pages : 554 pages
Book Rating : 4.4/5 (7 download)
Download or read book Optimal State Estimation written by Dan Simon and published by John Wiley & Sons. This book was released on 2006-06-19 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.
Author : Sherif Rushdy
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (144 download)
Download or read book Maximum Likelihood Estimation of a Nonlinear System Dynamic Market Growth Model written by Sherif Rushdy and published by . This book was released on 1981 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent efforts to determine the proper role of formal statistical estimation in modeling "System Dynamics" models show that the parameter estimates derived from Ordinary and Generalized Least Squares (OLS and GLS) are highly sensitive to errors in data measurement, and likely to prove misleading if used as a basis for selection of parameter values or structural analysis. Using the framework developed in this previous work, - where a nonlinear feedback model generates synthetic data, which is then used to estimate model parameters and thus provide a basis for the evaluation of an estimation technique, - this thesis reviews previous results with OLS and investigates alternative estimation techniques. A review of both econometric and engineering techniques, together with some preliminary experimental results revealed that no econometric estimation technique proved capable of meeting the requirements of the estimation of parameters in a nonlinear dynamic feedback model in the presence of measurement noise. The only promising method, the Filtering Form of the Maximum Likelihood algorithm, was found in the engineering literature where it is being used in a growing number of applications. A general FORTRAN program was developed to implement this algorithm and was tried out on three small-scale linear and nonlinear models. The method was found to be capable of drastically improving upon the Least Squares estimates, if sufficient Knowledge about the noise statistics (which present identifiability problems if they are all to be estimated) was available. However, experimentation on Forrester's "Market-Growth" model, while still modest in size compared to many System Dynamics models (nine equations and fifteen parameters to estimate), revealed the many limitations (in particular in convergence and cost) of this algorithm, that preclude its use in socio-economic applications. In the light of the above results, alternative methods of model validation, and in particular a more formal use of sensitivity testing, are suggested for further research.
Author : Ravindra Jategaonkar
Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (18 download)
Download or read book Maximum Likelihood Parameter Estimation from Flight Test Data for General Non-linear Systems written by Ravindra Jategaonkar and published by . This book was released on 1983 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John L. Crassidis
Publisher : CRC Press
ISBN 13 : 0203509129
Total Pages : 606 pages
Book Rating : 4.2/5 (35 download)
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
Author : J.R. Raol
Publisher : IET
ISBN 13 : 0863413633
Total Pages : 405 pages
Book Rating : 4.8/5 (634 download)
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.
Author : C. Giese
Publisher :
ISBN 13 :
Total Pages : 32 pages
Book Rating : 4.:/5 (498 download)
Download or read book Estimation of Nonlinear System States and Parameters by Regression Methods written by C. Giese and published by . This book was released on 1964 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern theories of optimal control are generally based on an assumption that a precise quantitative mathematical model exists for a dynamic system which is to be controlled or observed. In fact, such models are often lacking and must be inferred from experimental response data. When basic physical theory is sufficient to permit the object involved to be described by a differential equation with certain free parameters, the determination of a quantitative model becomes a problem in statistical estimation. This report formulates nonlinear dynamic system state and parameter estimation as a regression problem. An attempt is made to treat least squares regression, maximum likelihood estimation, and Bayes estimation from a unifying point of view. Experimental results relating to the nonlinear pendulum equation and to the ballistic vehicle atmospheric re-entry equation are included. These results show that it is possible to construct general algorithms for the automatic determination of parameter vectors by a digital computer. (Author).
Author : Wei Dai
Publisher :
ISBN 13 :
Total Pages : 180 pages
Book Rating : 4.:/5 (115 download)
Download or read book Parameter Estimation for Nonlinear Dynamic Systems with Significant Uncertainties written by Wei Dai and published by . This book was released on 2014 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hadiseh Karimi
Publisher :
ISBN 13 :
Total Pages : 458 pages
Book Rating : 4.:/5 (871 download)
Download or read book Parameter Estimation Techniques for Nonlinear Dynamic Models with Limited Data, Process Disturbances and Modeling Errors written by Hadiseh Karimi and published by . This book was released on 2013 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis appropriate statistical methods to overcome two types of problems that occur during parameter estimation in chemical engineering systems are studied. The first problem is having too many parameters to estimate from limited available data, assuming that the model structure is correct, while the second problem involves estimating unmeasured disturbances, assuming that enough data are available for parameter estimation. In the first part of this thesis, a model is developed to predict rates of undesirable reactions during the finishing stage of nylon 66 production. This model has too many parameters to estimate (56 unknown parameters) and not having enough data to reliably estimating all of the parameters. Statistical techniques are used to determine that 43 of 56 parameters should be estimated. The proposed model matches the data well. In the second part of this thesis, techniques are proposed for estimating parameters in Stochastic Differential Equations (SDEs). SDEs are fundamental dynamic models that take into account process disturbances and model mismatch. Three new approximate maximum likelihood methods are developed for estimating parameters in SDE models. First, an Approximate Expectation Maximization (AEM) algorithm is developed for estimating model parameters and process disturbance intensities when measurement noise variance is known. Then, a Fully-Laplace Approximation Expectation Maximization (FLAEM) algorithm is proposed for simultaneous estimation of model parameters, process disturbance intensities and measurement noise variances in nonlinear SDEs. Finally, a Laplace Approximation Maximum Likelihood Estimation (LAMLE) algorithm is developed for estimating measurement noise variances along with model parameters and disturbance intensities in nonlinear SDEs. The effectiveness of the proposed algorithms is compared with a maximum-likelihood based method. For the CSTR examples studied, the proposed algorithms provide more accurate estimates for the parameters. Additionally, it is shown that the performance of LAMLE is superior to the performance of FLAEM. SDE models and associated parameter estimates obtained using the proposed techniques will help engineers who implement on-line state estimation and process monitoring schemes.
Author : Rolf Isermann
Publisher : Springer
ISBN 13 : 9783540871552
Total Pages : 705 pages
Book Rating : 4.8/5 (715 download)
Download or read book Identification of Dynamic Systems written by Rolf Isermann and published by Springer. This book was released on 2011-04-08 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.
Author : Matej Gašperin
Publisher :
ISBN 13 :
Total Pages : 162 pages
Book Rating : 4.:/5 (78 download)
Download or read book Parameter Estimation of Nonlinear Dynamic Systems written by Matej Gašperin and published by . This book was released on 2011 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher : Academic Press
ISBN 13 : 0080956351
Total Pages : 606 pages
Book Rating : 4.0/5 (89 download)
Download or read book System Identification Advances and Case Studies written by and published by Academic Press. This book was released on 1977-02-21 with total page 606 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
