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Applied Control Systems Design

Applied Control Systems Design
Kataloginformation
Feldname Details
Vorliegende Sprache eng
Hinweise auf parallele Ausgaben 392096501 Buchausg. u.d.T.: ‡Mahmoud, Magdi S., 1948 - : Applied control systems design
ISBN 978-1-4471-2878-6
Name Mahmoud, Magdi S.
Xia, Yuanqing
ANZEIGE DER KETTE Xia, Yuanqing
T I T E L Applied Control Systems Design
Verlagsort London
Verlag Springer London
Erscheinungsjahr 2012
2012
Umfang Online-Ressource (XXI, 560p. 363 illus., 216 illus. in color, digital)
Reihe SpringerLink. Bücher
Notiz / Fußnoten Description based upon print version of record
Weiterer Inhalt Applied Control Systems Design; Preface; Acknowledgements; Contents; List of Notations; Chapter 1: Introduction; 1.1 Overview; 1.2 Modern Automation Structure; 1.3 Systems Identification; 1.4 Control Design; 1.5 Outline of the Book; 1.5.1 Methodology; 1.5.2 Chapter Organization; References; Chapter 2: Some Industrial Systems; 2.1 Introduction; 2.2 Steam Generation Unit; 2.2.1 System Dynamics; 2.3 Small-Power Wind Turbine; 2.3.1 Wind Turbine Basics; 2.4 Unmanned Surface Marine Vehicle; 2.4.1 Dynamic Model; 2.5 Industrial Evaporation Unit; 2.5.1 Mathematical Models. 2.5.2 Multistage Evaporator System2.6 Distillation Tower; 2.6.1 A Particular Tower; 2.7 Falling Film Evaporator; 2.7.1 A Single Effect Evaporator; 2.8 Vapor Compression Cycle Systems; 2.8.1 A Typical System; 2.9 Flutter of an Aircraft F-18; 2.9.1 Flutter Input and Output Data; 2.10 A Hydraulic Pumping System; 2.10.1 Hydraulic Process and the Data; 2.10.2 Static Behavior; 2.11 Notes and References; References; Chapter 3: System Identification Methods; 3.1 Introduction; 3.2 Parameter Estimation Approach; Model Validation; 3.2.1 Estimation Algorithms; 3.2.2 Gradient Algorithm. 3.2.3 Least Squares Algorithm3.2.4 Choice of the Adaptation Gain; Choice of the Initial Adaptation Gain F(0); 3.3 Transfer-Function Methods; 3.3.1 Prediction Error Method (PEM); 3.4 Subspace Identification Method; 3.4.1 State Space Models; 3.4.2 Block Hankel Matrices and State Sequences; 3.4.3 Model Matrices; 3.4.4 Orthogonal Projections; 3.4.5 Oblique Projections; 3.4.6 Deterministic Subspace Identification; Calculation of a State Sequence; Computing the System Matrices; 3.4.7 Stochastic Subspace Identification; Calculation of a State Sequence; Computing the System Matrices. 3.4.8 Combined Deterministic-Stochastic AlgorithmCalculation of a State Sequence; Computing the System Matrices; 3.4.9 Variations; 3.5 Output-Error Parametric Model Identification; 3.5.1 Introduction; 3.5.2 Problems in Estimating Parameters; 3.5.3 Identification Example 3.1; 3.5.4 Parameterizing a MIMO Model; 3.5.5 Identification Example 3.2; 3.5.6 Identification Example 3.3; 3.5.7 Identification Example 3.4; 3.5.8 The Output Normal Form; 3.5.9 Identification Example 3.5; 3.5.10 The Tridiagonal Form; 3.5.11 The Output-Error Cost Function; 3.5.12 Identification Example 3.6. 3.5.13 Numerical Parameter Estimation3.5.14 The Gauss-Newton Method; 3.5.15 Identification Example 3.7; 3.5.16 Regularization in the Gauss-Newton Method; 3.5.17 The Steepest Descent Method; 3.5.18 Gradient Projection; 3.5.19 Analyzing the Accuracy of the Estimates; 3.5.20 Dealing with Colored Measurement Noise; 3.5.21 Identification Example 3.8; 3.5.22 Weighted Least Squares; 3.5.23 Prediction-Error Methods; 3.6 Prediction-Error Parametric Model Estimation; 3.6.1 Introduction; 3.6.2 Prediction-Error Methods; 3.6.3 Parameterizing an Innovation State-Space Model. 3.6.4 The Prediction-Error Cost Function
Titelhinweis Buchausg. u.d.T.: ‡Mahmoud, Magdi S., 1948 - : Applied control systems design
ISBN ISBN 978-1-4471-2879-3
Klassifikation 54.83
TJFM
TEC004000
*93-02
62M20
62F99
62J05
62P30
93B30
93B51
93C40
93C95
93E12
93E20
629.8
TJ212-225
Kurzbeschreibung Yuanqing Xia
2. Kurzbeschreibung Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers' assimilation of the material discussed is assisted by the provision of problems and examples. Most of these exercises use MATLAB® to make computation and visualization more straightforward. Applied Control System Design will be of interest to academic researchers for its comparison of different systems models and their response to different control methods and will assist graduate students in learning the practical necessities of advanced control system design. The consistent reference to real systems coupled with self-learning tools will assist control practitioners who wish to keep up to date with the latest control design ideas.
1. Schlagwortkette Regelungstechnik
ANZEIGE DER KETTE Regelungstechnik
SWB-Titel-Idn 365267457
Signatur Springer E-Book
Bemerkungen Elektronischer Volltext - Campuslizenz
Elektronische Adresse $uhttp://dx.doi.org/10.1007/978-1-4471-2879-3
Internetseite / Link Volltext
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