Structural Identification and Estimation of a Linear Dynamic Model

Structural Identification and Estimation of a Linear Dynamic Model PDF Author: Julian Graham Morris
Publisher:
ISBN: 9780642908780
Category : Estimation theory
Languages : en
Pages : 54

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Book Description

Structural Identification and Estimation of a Linear Dynamic Model

Structural Identification and Estimation of a Linear Dynamic Model PDF Author: Julian Graham Morris
Publisher:
ISBN: 9780642908780
Category : Estimation theory
Languages : en
Pages : 54

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Book Description


Identification of Dynamic Systems

Identification of Dynamic Systems PDF Author: Rolf Isermann
Publisher: Springer Science & Business Media
ISBN: 3540788794
Category : Technology & Engineering
Languages : en
Pages : 705

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Book Description
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.

Nonlinear system identification. 2. Nonlinear system structure identification

Nonlinear system identification. 2. Nonlinear system structure identification PDF Author: Robert Haber
Publisher: Springer Science & Business Media
ISBN: 9780792358572
Category : Computers
Languages : en
Pages : 428

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Book Description
This is the second part of a two-volume handbook presenting a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes such as modelling, parameter estimation, structure search, nonlinearity and model validity tests.

Time Domain Identification of Linear Dynamic Structural Systems Using Total Least Squares

Time Domain Identification of Linear Dynamic Structural Systems Using Total Least Squares PDF Author: James Kirwan Pinkelman
Publisher:
ISBN:
Category :
Languages : en
Pages : 412

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Book Description


Modeling, Identification and Simulation of Dynamical Systems

Modeling, Identification and Simulation of Dynamical Systems PDF Author: P. P. J. van den Bosch
Publisher: CRC Press
ISBN: 0429605927
Category : Mathematics
Languages : en
Pages : 212

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Book Description
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.

Dynamic Modeling, Simulation and Control of Energy Generation

Dynamic Modeling, Simulation and Control of Energy Generation PDF Author: Ranjan Vepa
Publisher: Springer Science & Business Media
ISBN: 1447154002
Category : Technology & Engineering
Languages : en
Pages : 384

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Book Description
This book addresses the core issues involved in the dynamic modeling, simulation and control of a selection of energy systems such as gas turbines, wind turbines, fuel cells and batteries. The principles of modeling and control could be applied to other non-convention methods of energy generation such as solar energy and wave energy. A central feature of Dynamic Modeling, Simulation and Control of Energy Generation is that it brings together diverse topics in thermodynamics, fluid mechanics, heat transfer, electro-chemistry, electrical networks and electrical machines and focuses on their applications in the field of energy generation, its control and regulation. This book will help the reader understand the methods of modelling energy systems for controller design application as well as gain a basic understanding of the processes involved in the design of control systems and regulators. It will also be a useful guide to simulation of the dynamics of energy systems and for implementing monitoring systems based on the estimation of internal system variables from measurements of observable system variables. Dynamic Modeling, Simulation and Control of Energy Generation will serve as a useful aid to designers of hybrid power generating systems involving advanced technology systems such as floating or offshore wind turbines and fuel cells. The book introduces case studies of the practical control laws for a variety of energy generation systems based on nonlinear dynamic models without relying on linearization. Also the book introduces the reader to the use nonlinear model based estimation techniques and their application to energy systems.

Modelling and Parameter Estimation of Dynamic Systems

Modelling and Parameter Estimation of Dynamic Systems PDF Author: J.R. Raol
Publisher: IET
ISBN: 0863413633
Category : Mathematics
Languages : en
Pages : 405

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Book Description
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.

Modelling and Identification of Dynamic Systems

Modelling and Identification of Dynamic Systems PDF Author: N.K. Sinha
Publisher: Springer
ISBN: 0442281625
Category : Computers
Languages : en
Pages : 334

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Book Description


From Data to Model

From Data to Model PDF Author: Jan C. Willems
Publisher: Springer Science & Business Media
ISBN: 3642750079
Category : Business & Economics
Languages : en
Pages : 254

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Book Description
The problem of obtaining dynamical models directly from an observed time-series occurs in many fields of application. There are a number of possible approaches to this problem. In this volume a number of such points of view are exposed: the statistical time series approach, a theory of guaranted performance, and finally a deterministic approximation approach. This volume is an out-growth of a number of get-togethers sponsered by the Systems and Decision Sciences group of the International Institute of Applied Systems Analysis (IIASA) in Laxenburg, Austria. The hospitality and support of this organization is gratefully acknowledged. Jan Willems Groningen, the Netherlands May 1989 TABLE OF CONTENTS Linear System Identification- A Survey page 1 M. Deistler A Tutorial on Hankel-Norm Approximation 26 K. Glover A Deterministic Approach to Approximate Modelling 49 C. Heij and J. C. Willems Identification - a Theory of Guaranteed Estimates 135 A. B. Kurzhanski Statistical Aspects of Model Selection 215 R. Shibata Index 241 Addresses of Authors 246 LINEAR SYSTEM IDENTIFICATION· A SURVEY M. DEISTLER Abstract In this paper we give an introductory survey on the theory of identification of (in general MIMO) linear systems from (discrete) time series data. The main parts are: Structure theory for linear systems, asymptotic properties of maximum likelihood type estimators, estimation of the dynamic specification by methods based on information criteria and finally, extensions and alternative approaches such as identification of unstable systems and errors-in-variables. Keywords Linear systems, parametrization, maximum likelihood estimation, information criteria, errors-in-variables.

Analytical Methods for Dynamic Modelers

Analytical Methods for Dynamic Modelers PDF Author: Hazhir Rahmandad
Publisher: MIT Press
ISBN: 0262331438
Category : Business & Economics
Languages : en
Pages : 443

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Book Description
A user-friendly introduction to some of the most useful analytical tools for model building, estimation, and analysis, presenting key methods and examples. Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling. Bringing together tools and methodologies from fields as diverse as computational statistics, econometrics, and operations research in a single text, the book can be used for graduate-level courses and as a reference for dynamic modelers who want to expand their methodological toolbox. The focus is on quantitative techniques for use by dynamic modelers during model construction and analysis, and the material presented is accessible to readers with a background in college-level calculus and statistics. Each chapter describes a key method, presenting an introduction that emphasizes the basic intuition behind each method, tutorial style examples, references to key literature, and exercises. The chapter authors are all experts in the tools and methods they present. The book covers estimation of model parameters using quantitative data; understanding the links between model structure and its behavior; and decision support and optimization. An online appendix offers computer code for applications, models, and solutions to exercises. Contributors Wenyi An, Edward G. Anderson Jr., Yaman Barlas, Nishesh Chalise, Robert Eberlein, Hamed Ghoddusi, Winfried Grassmann, Peter S. Hovmand, Mohammad S. Jalali, Nitin Joglekar, David Keith, Juxin Liu, Erling Moxnes, Rogelio Oliva, Nathaniel D. Osgood, Hazhir Rahmandad, Raymond Spiteri, John Sterman, Jeroen Struben, Burcu Tan, Karen Yee, Gönenç Yücel