Appropriate for courses in System Identification. This book is a comprehensive and coherent description of the theory, methodology and practice of System Identification--the science of building mathematical models of dynamic systems by observing input/output data. It puts the user in focus, giving the necessary background to understand theoretical ...
Presenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems, this books shows that non-parametric regression can be successfully applied to system identification, and it highlights the achievements in doing so. With emphasis on Hammerstein, Wiener systems, and their ...
Identification in control theory is the process of obtaining a model of the object or process being controlled. It is used extensively in the area of robust control for the purpose of finding applicable models and, once identified, then validated or tested. Written by two of the leading researchers, this is the first book to cover this rapidly ...
This book presents new approaches to the construction of fuzzy models for model-based control. New model structures and identification algorithms are described for the effective use of heterogeneous information in the form of numerical data, qualitative knowledge, and first principle models. The main methods and techniques are illustrated through ...
A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable ...
This text covers recent results in the analysis, identification and control of systems described by Volterra models. Topics covered include:- qualitative behavior of finite Volterra models compared and contrasted with other nonlinear model classes- structural restrictions and extensions to Volterra model class - least squares and stochastic ...
The absence of training signals from many kinds of transmission necessitates the widespread use of blind equalization and system identification. There have been many algorithms developed for these purposes, working with one- or two-dimensional signals and with single-input single-output or multiple-input multiple-output, real or complex systems. ...
In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to ...
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 ...
As a byproduct of historical development, there are different, unrelated systems of nomenclature for 'inorganic chemistry', 'organic chemistry', 'polymer chemistry', 'natural products chemistry', etc. With each new discovery in the laboratory, as well as each new theoretical proposal for a chemical, the lines that traditionally have separated ...
Focuses on robust control, currently a very important topic in control research and engineering. The interest in this area is motivated by the need to achieve greater accuracy and predictability in modern control systems, as are found in aircraft and rocket navigation systems, for example.
Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited. The ...
This volume contains the results of the workshop on "Parameter Identification and Inverse Problems in Hydrology, Geology and Ecology", held in Karlsruhe, Germany, and represents a selection of contributions from the various groups of participants. The reviewed, invited and contributed articles are grouped according to the broad headings of ...
This book intends to provide users of identification software with the fundamental insight needed to carry out the interactive design of models of physical objects. The text begins with the fundamental conditions for setting up correct identification problems, continues by highlighting the roles of the validation and falsification of models, and ...
This comprehensive book describes procedures to identify and analyze the properties of many types of nonlinear systems from random data measured at the input and output points of physical systems. Improvements are offered in applying older techniques, and problems that traditionally have been difficult to analyze are solved by new, simpler ...
This book offers a tutorial view of recent trends in the science of modelling, adaptation, and learning. The most important modern approaches to identification, namely the stochastic, behavioral, subspace, and frequency domain approaches, are discussed thoroughly. On adaptation, tuning the parameters of a linear model is presented as a cure for ...
Filtering and system identification are powerful techniques for building models of complex systems. This book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing ...
System identification is the process of developing or improving a mathematical representation of a physical system using experimental data. Over the past decade, several system identification techniques have been developed within different disciplines. This text/reference brings together the significant advances over the past decade into a single ...
This valuable volume offers a systematic approach to flight vehicle system identification and covers exhaustively the time-domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, ...
The presentation of a coherent methodology for the estimation of the parameters of mathematical models from experimental data is examined in this volume. Topics covered include: the choice of the structure of the mathematical model; the choice of a performance criterion to compare models; the optimization of this performance criterion, the ...
This book gives a global picture of the current state of identification, from the reasons for mathematical modelling, through the theoretical underpinning, to details of a wide range of well-tried identification algorithms and their application. The limitations of present techniques and the practical constraints on their use are explored and ...
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