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Modelling and Parameter Estimation of Dynamic Systems

Modelling and Parameter Estimation of Dynamic Systems
Author: J.R. Raol
Publisher: IET
Total Pages: 405
Release: 2004-08-13
Genre: Mathematics
ISBN: 0863413633

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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.


Identification of Dynamic Systems

Identification of Dynamic Systems
Author: Rolf Isermann
Publisher: Springer Science & Business Media
Total Pages: 705
Release: 2010-11-22
Genre: Technology & Engineering
ISBN: 3540788794

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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.


Dynamic Systems Models

Dynamic Systems Models
Author: Josif A. Boguslavskiy
Publisher: Springer
Total Pages: 201
Release: 2016-03-22
Genre: Science
ISBN: 3319040367

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This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamics or biological sequence analysis. The technical material is illustrated by the use of worked examples and methods for training the algorithms are included. Dynamic Systems Models provides researchers in aerospatial engineering, bioinformatics and financial mathematics (as well as computer scientists interested in any of these fields) with a reliable and effective numerical method for nonlinear estimation and solving boundary problems when carrying out control design. It will also be of interest to academic researchers studying inverse problems and their solution.


Mathematical and Computational Modeling and Simulation

Mathematical and Computational Modeling and Simulation
Author: Dietmar P.F. Möller
Publisher: Springer Science & Business Media
Total Pages: 438
Release: 2012-12-06
Genre: Mathematics
ISBN: 3642187099

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This introduction and textbook familiarizes engineers with the use of mathematical and computational modeling and simulation in a way that develops their understanding of the solution characteristics of a broad class of real-world problems. The relevant basic and advanced methodologies are explained in detail, with special emphasis on ill-defined problems. Some fifteen simulation systems are presented on the language and the logical level. Moreover, the reader also can accumulate an experiential overview by studying the wide variety of case studies spanning much of science and engineering. The latter are briefly described within the book but their full versions as well as some simulation software demos are available on the Web. The book can be used for courses on various levels as well as for self-study. Advanced sections are identified and can be skipped in a first reading or in undergraduate courses.


Modeling, Identification and Simulation of Dynamical Systems

Modeling, Identification and Simulation of Dynamical Systems
Author: P. P. J. van den Bosch
Publisher: CRC Press
Total Pages: 212
Release: 2020-12-17
Genre: Mathematics
ISBN: 0429605927

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This book gives an in-depth introduction to the areas of modeling, identification, simulation, and optimization. These scientific topics play an increasingly dominant part in many engineering areas such as electrotechnology, mechanical engineering, aerospace, and physics. This book represents a unique and concise treatment of the mutual interactions among these topics. Techniques for solving general nonlinear optimization problems as they arise in identification and many synthesis and design methods are detailed. The main points in deriving mathematical models via prior knowledge concerning the physics describing a system are emphasized. Several chapters discuss the identification of black-box models. Simulation is introduced as a numerical tool for calculating time responses of almost any mathematical model. The last chapter covers optimization, a generally applicable tool for formulating and solving many engineering problems.


Measurement Data Modeling and Parameter Estimation

Measurement Data Modeling and Parameter Estimation
Author: Zhengming Wang
Publisher: CRC Press
Total Pages: 540
Release: 2016-04-19
Genre: Computers
ISBN: 1439853797

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This book discusses the theories, methods, and application techniques of the measurement data mathematical modeling and parameter estimation. It seeks to build a bridge between mathematical theory and engineering practice in the measurement data processing field so theoretical researchers and technical engineers can communicate. It is organized with abundant materials, such as illustrations, tables, examples, and exercises. The authors create examples to apply mathematical theory innovatively to measurement and control engineering. Not only does this reference provide theoretical knowledge, it provides information on first hand experiences.


Applied Parameter Estimation for Chemical Engineers

Applied Parameter Estimation for Chemical Engineers
Author: Peter Englezos
Publisher: CRC Press
Total Pages: 462
Release: 2000-10-12
Genre: Science
ISBN: 9780203904695

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This book determines adjustable parameters in mathematical models that describe steady state or dynamic systems, presenting the most important optimization methods used for parameter estimation. It focuses on the Gauss-Newton method and its modifications for systems and processes represented by algebraic or differential equation models.