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Linear Feedback Control: Analysis and Design with MATLAB [Mīkstie vāki]

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  • Formāts: Paperback / softback, 366 pages, height x width x depth: 229x152x17 mm, weight: 641 g, Illustrations
  • Sērija : Advances in Design and Control No. 14
  • Izdošanas datums: 30-Nov-2007
  • Izdevniecība: Society for Industrial & Applied Mathematics,U.S.
  • ISBN-10: 0898716381
  • ISBN-13: 9780898716382
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  • Mīkstie vāki
  • Cena: 140,55 €
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Linear Feedback Control: Analysis and Design with MATLABPalielināt
  • Formāts: Paperback / softback, 366 pages, height x width x depth: 229x152x17 mm, weight: 641 g, Illustrations
  • Sērija : Advances in Design and Control No. 14
  • Izdošanas datums: 30-Nov-2007
  • Izdevniecība: Society for Industrial & Applied Mathematics,U.S.
  • ISBN-10: 0898716381
  • ISBN-13: 9780898716382
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780898716382.html
Keywords:
Discusses analysis and design techniques for linear feedback control systems using MATLAB® software. By reducing the mathematics, increasing MATLAB working examples, and inserting short scripts and plots within the text, the authors have created a resource suitable for almost any type of user. For beginners, the book provides an efficient entrance into the field; for readers who have already had a first course in control, the text helps bridge the gap between control theory and the use of MATLAB for control systems; for practicing engineers, it serves as a handy reference.

The book begins with a summary of the properties of linear systems and addresses modeling and model reduction issues. In the subsequent chapters on analysis, the authors introduce time domain, complex plane, and frequency domain techniques. Their coverage of design includes discussions on model-based controller designs, PID controllers, and robust control designs. A unique aspect of the book is its inclusion of a chapter on fractional-order controllers, which are useful in control engineering practice.

Especially useful for self-study, Linear Feedback Control uses the MATLAB companion package CtrlLAB, which allows readers to learn quickly while simply clicking through options with a mouse. Each chapter ends with a set of problems to help readers strengthen their understanding of the material. All example scripts within the book, as well as the CtrlLAB package, are freely downloadable from MATLAB Central.
Preface xi
Introduction to Feedback Control
1(10)
Introduction
1(2)
Historical Background
3(1)
Structure of the Book
4(2)
A Survival Guide to MATLAB
6(5)
A Brief Overview of MATLAB
6(1)
Standard MATLAB Statements and Functions
6(1)
Graphics Facilities in MATLAB
7(1)
On-Line Help Facilities in MATLAB
7(1)
MATLAB Toolboxes
8(1)
Problems
9(2)
Mathematical Models of Feedback Control Systems
11(40)
A Physical Modeling Example
11(1)
The Laplace Transformation
12(2)
Transfer Function Models
14(3)
Transfer Functions of Control Systems
14(1)
MATLAB Representations of Transfer Functions
14(2)
Transfer Function Matrices for Multivariable Systems
16(1)
Transfer Functions of Discrete-Time Systems
16(1)
Other Mathematical Model Representations
17(3)
State Space Modeling
17(2)
Zero-Pole-Gain Description
19(1)
Modeling of Interconnected Block Diagrams
20(4)
Series Connection
20(1)
Parallel Connection
20(1)
Feedback Connection
21(1)
More Complicated Connections
22(2)
Conversion Between Different Model Objects
24(11)
Conversion to Transfer Functions
25(1)
Conversion to Zero-Pole-Gain Models
26(1)
State Space Realizations
27(7)
Conversion Between Continuous and Discrete-Time Models
34(1)
An Introduction to System Identification
35(16)
Identification of Discrete-Time Systems
35(5)
Order Selection
40(1)
Generation of Identification Signals
41(3)
Identification of Multivariable Systems
44(1)
Problems
45(6)
Analysis of Linear Control Systems
51(60)
Properties of Linear Control Systems
52(14)
Stability Analysis
52(3)
Controllability and Observability Analysis
55(4)
Kalman Decomposition of Linear Systems
59(3)
Time Moments and Markov Parameters
62(2)
Norm Measures of Signals and Systems
64(2)
Time Domain Analysis of Linear Systems
66(4)
Analytical Solutions to Continuous Time Responses
66(3)
Analytical Solutions to Discrete-Time Responses
69(1)
Numerical Simulation of Linear Systems
70(8)
Step Responses of Linear Systems
70(5)
Impulse Responses of Linear Systems
75(1)
Time Responses to Arbitrary Inputs
76(2)
Root Locus of Linear Systems
78(6)
Frequency Domain Analysis of Linear Systems
84(8)
Frequency Domain Graphs with MATLAB
84(3)
Stability Analysis Using Frequency Domain Methods
87(1)
Gain and Phase Margins of a System
88(2)
Variations of Conventional Nyquist Plots
90(2)
Introduction to Model Reduction Techniques
92(19)
Pade Approximations and Routh Approximations
92(4)
Pade Approximations to Delay Terms
96(2)
Suboptimal Reduction Techniques for Systems with Delays
98(3)
State Space Model Reduction
101(3)
Problems
104(7)
Simulation Analysis of Nonlinear Systems
111(28)
An Introduction to Simulink
111(7)
Commonly Used Simulink Blocks
112(3)
Simulink Modeling
115(1)
Simulation Algorithms and Control Parameters
116(2)
Modeling of Nonlinear Systems by Examples
118(8)
Nonlinear Elements Modeling
126(5)
Modeling of Piecewise Linear Nonlinearities
126(3)
Limit Cycles of Nonlinear Systems
129(2)
Linearization of Nonlinear Models
131(8)
Problems
135(4)
Model-Based Controller Design
139(42)
Cascade Lead-Lag Compensator Design
140(11)
Introduction to Lead-Lag Synthesis
140(6)
Lead-Lag Synthesis by Phase Margin Assignment
146(5)
Linear Quadratic Optimal Control
151(14)
Linear Quadratic Optimal Control Strategies
151(1)
Linear Quadratic Regulator Problems
152(3)
Linear Quadratic Control for Discrete-Time Systems
155(1)
Selection of Weighting Matrices
156(3)
Observers and Observer Design
159(3)
State Feedback and Observer-Based Controllers
162(3)
Pole Placement Design
165(6)
The Bass-Gura Algorithm
166(1)
Ackermann's Algorithm
166(1)
Numerically Robust Pole Placement Algorithm
167(2)
Observer Design Using the Pole Placement Technique
169(1)
Observer-Based Controller Design Using the Pole Placement Technique
169(2)
Decoupling Control of Multivariable Systems
171(4)
Decoupling Control with State Feedback
171(1)
Pole Placement of Decoupling Systems with State Feedback
172(3)
SISOTool: An Interactive Controller Design Tool
175(6)
Problems
177(4)
PID Controller Design
181(54)
Introduction
182(3)
The PID Action
182(2)
PID Control with Derivative in the Feedback Loop
184(1)
Ziegler-Nichols Tuning Formula
185(12)
Empirical Ziegler-Nichols Tuning Formula
185(4)
Derivative Action in the Feedback Path
189(2)
Methods for First-Order Plus Dead Time Model Fitting
191(3)
A Modified Ziegler-Nichols Formula
194(3)
Other PID Controller Tuning Formulae
197(13)
Chien-Hrones-Reswick PID Tuning Algorithm
197(1)
Cohen-Coon Tuning Algorithm
198(2)
Refined Ziegler-Nichols Tuning
200(3)
The Wang-Juang-Chan Tuning Formula
203(1)
Optimum PID Controller Design
203(7)
PID Controller Tuning Algorithms for Other Types of Plants
210(3)
PD and PID Parameter Setting for IPDT Models
210(1)
PD and PID Parameters for FOIPDT Models
211(2)
PID Parameter Settings for Unstable FOPDT Models
213(1)
PID_Tuner: A PID Controller Design Program for FOPDT Models
213(3)
Optimal Controller Design
216(9)
Solutions to Optimization Problems with MATLAB
216(2)
Optimal Controller Design
218(3)
A MATLAB/Simulink-Based Optimal Controller Designer and Its Applications
221(4)
More Topics on PID Control
225(10)
Integral Windup and Anti-Windup PID Controllers
225(2)
Automatic Tuning of PID Controllers
227(3)
Control Strategy Selection
230(1)
Problems
231(4)
Robust Control Systems Design
235(48)
Linear Quadratic Gaussian Control
236(11)
LQG Problem
236(1)
LQG Problem Solutions Using MATLAB
236(5)
LQG Control with Loop Transfer Recovery
241(6)
General Descriptions of the Robust Control Problems
247(6)
Small Gain Theorem
247(1)
Unstructured Uncertainties
248(1)
Robust Control Problems
249(1)
Model Representation Under MATLAB
250(1)
Dealing with Poles on the Imaginary Axis
251(2)
H∞ Controller Design
253(18)
Augmentations of the Model with Weighting Functions
253(2)
Model Augmentation with Weighting Function Under MATLAB
255(1)
Weighted Sensitivity Problems: A Simple Case
256(5)
H∞ Controller Design: The General Case
261(6)
Optimal H∞ Controller Design
267(4)
Optimal H2 Controller Design
271(2)
The Effects of Weighting Functions in H∞ Control
273(10)
Problems
281(2)
Fractional-Order Controller: An Introduction
283(24)
Fractional-Order Calculus and Its Computations
284(3)
Definitions of Fractional-Order Calculus
285(1)
Properties of Fractional-Order Differentiations
286(1)
Frequency and Time Domain Analysis of Fractional-Order Linear Systems
287(5)
Fractional-Order Transfer Function Modeling
287(1)
Interconnections of Fractional-Order Blocks
288(1)
Frequency Domain Analysis of Linear Fractional-Order Systems
289(1)
Time Domain Analysis of Fractional-Order Systems
290(2)
Filter Approximation to Fractional-Order Differentiations
292(6)
Oustaloup's Recursive Filter
292(2)
A Refined Oustaloup Filter
294(2)
Simulink-Based Fractional-Order Nonlinear Differential Equation Solutions
296(2)
Model Reduction Techniques for Fractional-Order Systems
298(2)
Controller Design Studies for Fractional-Order Systems
300(7)
Problems
304(3)
Appendix CtrILAB: A Feedback Control System Analysis and Design Tool
307(30)
Introduction
307(2)
What is CtrlLAB?
307(1)
Installation and Requirements
308(1)
Execution of CtrlLAB
308(1)
Model Entry and Model Conversion
309(2)
Transfer Function Entry
309(1)
Entering Other Model Representations
309(1)
A More Complicated Model Entry
310(1)
Model Transformation and Reduction
311(5)
Model Display
311(3)
State Space Realizations
314(1)
Model Reduction
314(2)
Feedback Control System Analysis
316(6)
Frequency Domain Analysis
316(2)
Time Domain Analysis
318(3)
System Properties Analysis
321(1)
Controller Design Examples
322(5)
Model-Based Controller Designs
322(1)
Design of PID Controllers
322(3)
Robust Controller Design
325(2)
Graphical Interface-Based Tools
327(10)
A Matrix Processor
327(4)
A Graphical Curve Processor
331(3)
Problems
334(3)
Bibliography 337(8)
Index of MATLAB Functions 345(4)
Index 349
Dingyü Xue is a Professor of Control Engineering on the Faculty of Information Sciences and Engineering at Northeastern University in Shenyang, China. YangQuan Chen is an Assistant Professor in the Electrical and Computer Engineering Department and the Director of the Center for Self-Organizing and Intelligent Systems at Utah State University. Derek P. Atherton is Professor Emeritus at the University of Sussex.