Modeling Identification And Simulation Of Dynamical Systems

Author : P. P. J. van den Bosch,A. C. van der Klauw
Publisher : CRC Press
Page : 212 pages
File Size : 43,5 Mb
Release : 2020-12-17
Category : Mathematics
ISBN : 9780429605925

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Modeling, Identification and Simulation of Dynamical Systems by P. P. J. van den Bosch,A. C. van der Klauw Pdf

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.

Author : Paul P. J. Bosch
Publisher : Unknown
Page : 195 pages
File Size : 53,5 Mb
Release : 1994
Category : TECHNOLOGY
ISBN : 0138746877

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Modeling, Identification, and Simulation of Dynamical Systems by Paul P. J. Bosch Pdf

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.

Author : P. P. J. van den Bosch,A. C. van der Klauw
Publisher : CRC Press
Page : 206 pages
File Size : 43,6 Mb
Release : 2020-12-17
Category : Mathematics
ISBN : 9780429611445

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Modeling, Identification and Simulation of Dynamical Systems by P. P. J. van den Bosch,A. C. van der Klauw Pdf

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.

Author : Lennart Ljung,Torkel Glad
Publisher : Prentice Hall
Page : 0 pages
File Size : 52,9 Mb
Release : 1994
Category : Computer simulation
ISBN : 0135970970

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Modeling of Dynamic Systems by Lennart Ljung,Torkel Glad Pdf

Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. MARKET: For practicing engineers who are faced with problems of modeling.

Author : Patricia Melin,Oscar Castillo
Publisher : CRC Press
Page : 262 pages
File Size : 43,9 Mb
Release : 2001-10-25
Category : Mathematics
ISBN : 9781420024524

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Modelling, Simulation and Control of Non-linear Dynamical Systems by Patricia Melin,Oscar Castillo Pdf

These authors use soft computing techniques and fractal theory in this new approach to mathematical modeling, simulation and control of complexion-linear dynamical systems. First, a new fuzzy-fractal approach to automated mathematical modeling of non-linear dynamical systems is presented. It is illustrated with examples on the PROLOG programming la

Author : Lennart Ljung,Torkel Glad
Publisher : Unknown
Page : 402 pages
File Size : 50,6 Mb
Release : 2016
Category : Electronic
ISBN : 9144116888

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Modeling & Identification of Dynamic Systems by Lennart Ljung,Torkel Glad Pdf

Author : Steven L. Brunton,J. Nathan Kutz
Publisher : Cambridge University Press
Page : 615 pages
File Size : 40,7 Mb
Release : 2022-05-05
Category : Computers
ISBN : 9781009098489

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Data-Driven Science and Engineering by Steven L. Brunton,J. Nathan Kutz Pdf

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Author : Craig A. Kluever
Publisher : John Wiley & Sons
Page : 480 pages
File Size : 52,8 Mb
Release : 2020-06-23
Category : Technology & Engineering
ISBN : 9781119723479

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Dynamic Systems by Craig A. Kluever Pdf

The simulation of complex, integrated engineering systems is a core tool in industry which has been greatly enhanced by the MATLAB® and Simulink® software programs. The second edition of Dynamic Systems: Modeling, Simulation, and Control teaches engineering students how to leverage powerful simulation environments to analyze complex systems. Designed for introductory courses in dynamic systems and control, this textbook emphasizes practical applications through numerous case studies—derived from top-level engineering from the AMSE Journal of Dynamic Systems. Comprehensive yet concise chapters introduce fundamental concepts while demonstrating physical engineering applications. Aligning with current industry practice, the text covers essential topics such as analysis, design, and control of physical engineering systems, often composed of interacting mechanical, electrical, and fluid subsystem components. Major topics include mathematical modeling, system-response analysis, and feedback control systems. A wide variety of end-of-chapter problems—including conceptual problems, MATLAB® problems, and Engineering Application problems—help students understand and perform numerical simulations for integrated systems.

Author : Yuri Tiumentsev,Mikhail Egorchev
Publisher : Academic Press
Page : 332 pages
File Size : 50,6 Mb
Release : 2019-05-17
Category : Science
ISBN : 9780128154304

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Neural Network Modeling and Identification of Dynamical Systems by Yuri Tiumentsev,Mikhail Egorchev Pdf

Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft. Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and training Offers application examples of dynamic neural network technologies, primarily related to aircraft Provides an overview of recent achievements and future needs in this area

Author : Edward Layer,Krzysztof Tomczyk
Publisher : Springer Science & Business Media
Page : 165 pages
File Size : 52,6 Mb
Release : 2009-12-30
Category : Technology & Engineering
ISBN : 9783642045882

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Measurements, Modelling and Simulation of Dynamic Systems by Edward Layer,Krzysztof Tomczyk Pdf

The development and use of models of various objects is becoming a more common practice in recent days. This is due to the ease with which models can be developed and examined through the use of computers and appropriate software. Of those two, the former - high-speed computers - are easily accessible nowadays, and the latter - existing programs - are being updated almost continuously, and at the same time new powerful software is being developed. Usually a model represents correlations between some processes and their interactions, with better or worse quality of representation. It details and characterizes a part of the real world taking into account a structure of phenomena, as well as quantitative and qualitative relations. There are a great variety of models. Modelling is carried out in many diverse fields. All types of natural phenomena in the area of biology, ecology and medicine are possible subjects for modelling. Models stand for and represent technical objects in physics, chemistry, engineering, social events and behaviours in sociology, financial matters, investments and stock markets in economy, strategy and tactics, defence, security and safety in military fields. There is one common point for all models. We expect them to fulfil the validity of prediction. It means that through the analysis of models it is possible to predict phenomena, which may occur in a fragment of the real world represented by a given model. We also expect to be able to predict future reactions to signals from the outside world.

Author : Juš Kocijan
Publisher : Springer
Page : 267 pages
File Size : 42,8 Mb
Release : 2015-11-21
Category : Technology & Engineering
ISBN : 9783319210216

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Modelling and Control of Dynamic Systems Using Gaussian Process Models by Juš Kocijan Pdf

This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.

Author : J.R. Raol,G. Girija,J. Singh
Publisher : IET
Page : 405 pages
File Size : 44,8 Mb
Release : 2004-08-13
Category : Mathematics
ISBN : 9780863413636

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Modelling and Parameter Estimation of Dynamic Systems by J.R. Raol,G. Girija,J. Singh Pdf

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 : Peter S.C. Heuberger,Paul M.J. van den Hof,Bo Wahlberg
Publisher : Springer Science & Business Media
Page : 432 pages
File Size : 44,6 Mb
Release : 2005-06-30
Category : Technology & Engineering
ISBN : 185233956X

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Modelling and Identification with Rational Orthogonal Basis Functions by Peter S.C. Heuberger,Paul M.J. van den Hof,Bo Wahlberg Pdf

Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science. A model is always only an approximation of a real phenomenon so that having an approximation theory which allows for the analysis of model quality is a substantial concern. The use of rational orthogonal basis functions to represent dynamical systems and stochastic signals can provide such a theory and underpin advanced analysis and efficient modelling. It also has the potential to extend beyond these areas to deal with many problems in circuit theory, telecommunications, systems, control theory and signal processing. Modelling and Identification with Rational Orthogonal Basis Functions affords a self-contained description of the development of the field over the last 15 years, furnishing researchers and practising engineers working with dynamical systems and stochastic processes with a standard reference work.

Author : Robert L. Woods,Kent L. Lawrence
Publisher : Pearson
Page : 552 pages
File Size : 54,7 Mb
Release : 1997
Category : Mathematics
ISBN : UOM:39015045643064

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Modeling and Simulation of Dynamic Systems by Robert L. Woods,Kent L. Lawrence Pdf

Introduction to modeling and simulation - Models for dynamic systems and systems similarity - Modeling of engineering systems - Mechanical systems - Electrical systems - Fluid systems - Thermal systems - Mixed discipline systems - System dynamic response analysis - Frequency response - Time response and digital simulation - Engineering applications - System design and selection of components.

Author : Rolf Isermann,Marco Münchhof
Publisher : Springer
Page : 0 pages
File Size : 46,5 Mb
Release : 2014-11-23
Category : Technology & Engineering
ISBN : 3642422675

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Identification of Dynamic Systems by Rolf Isermann,Marco Münchhof Pdf

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.