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Control System Design An Introduction to State-Space Methods

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ISBN-10: 0486442780

ISBN-13: 9780486442785

Edition: 2005

Authors: Bernard Friedland

List price: $34.95
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Description:

Introduction to state-space methods covers feedback control; state-space representation of dynamic systems and dynamics of linear systems; frequency-domain analysis; controllability and observability; and shaping the dynamic response. Additional subjects encompass linear observers; compensator design by the separation principle; linear, quadratic optimum control; random processes; and Kalman filters. 1986 edition.
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Book details

List price: $34.95
Copyright year: 2005
Publisher: Dover Publications, Incorporated
Publication date: 3/24/2005
Binding: Paperback
Pages: 528
Size: 6.57" wide x 9.21" long x 1.02" tall
Weight: 1.540
Language: English

Preface
Feedback Control
The Mechanism of Feedback
Feedback Control Engineering
Control Theory Background
Scope and Organization of This Book
Notes
References
State-Space Representation of Dynamic Systems
Mathematical Models
Physical Notion of System State
Block-Diagram Representations
Lagrange's Equations
Rigid Body Dynamics
Aerodynamics
Chemical and Energy Processes
Problems
Notes
References
Dynamics of Linear Systems
Differential Equations Revisited
Solution of Linear Differential Equations in State-Space Form
Interpretation and Properties of the State-Transition Matrix
Solution by the Laplace Transform: The Resolvent
Input-Output Relations: Transfer Functions
Transformation of State Variables
State-Space Representation of Transfer Functions: Canonical Forms
Problems
Notes
References
Frequency-Domain Analysis
Status of Frequency-Domain Methods
Frequency-Domain Characterization of Dynamic Behavior
Block-Diagram Algebra
Stability
Routh-Hurwitz Stability Algorithms
Graphical Methods
Steady State Responses: System Type
Dynamic Response: Bandwidth
Robustness and Stability (Gain and Phase) Margins
Multivariable Systems: Nyquist Diagram and Singular Values
Problems
Notes
References
Controllability and Observability
Introduction
Where Do Uncontrollable or Unobservable Systems Arise?
Definitions and Conditions for Controllability and Observability
Algebraic Conditions for Controllability and Observability
Disturbances and Tracking Systems: Exogenous Variables
Problems
Notes
References
Shaping the Dynamic Response
Introduction
Design of Regulators for Single-Input, Single-Output Systems
Multiple-Input Systems
Disturbances and Tracking Systems: Exogenous Variables
Where Should the Closed-Loop Poles Be Placed?
Problems
Notes
References
Linear Observers
The Need for Observers
Structure and Properties of Observers
Pole-Placement for Single-Output Systems
Disturbances and Tracking Systems: Exogenous Variables
Reduced-Order Observers
Problems
Notes
References
Compensator Design by the Separation Principle
The Separation Principle
Compensators Designed Using Full-Order Observers
Reduced-Order Observers
Robustness: Effects of Modeling Errors
Disturbances and Tracking Systems: Exogenous Variables
Selecting Observer Dynamics: Robust Observers
Summary of Design Process
Problems
Notes
References
Linear, Quadratic Optimum Control
Why Optimum Control?
Formulation of the Optimum Control Problem
Quadratic Integrals and Matrix Differential Equations
The Optimum Gain Matrix
The Steady State Solution
Disturbances and Reference Inputs: Exogenous Variables
General Performance Integral
Weighting of Performance at Terminal Time
Problems
Notes
References
Random Processes
Introduction
Conceptual Models for Random Processes
Statistical Characteristics of Random Processes
Power Spectral Density Function
White Noise and Linear System Response
Spectral Factorization
Systems with State-Space Representation
The Wiener Process and Other Integrals of Stationary Processes
Problems
Notes
References
Kalman Filters: Optimum Observers
Background
The Kalman Filter is an Observer
Kalman Filter Gain and Variance Equations
Steady State Kalman Filter
The "Innovations" Process
Reduced-Order Filters and Correlated Noise
Stochastic Control: The Separation Theorem
Choosing Noise for Robust Control
Problems
Notes
References
Matrix Algebra and Analysis
Bibliography
Index of Applications
Index