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9780471266372

Feedback Control of Computing Systems

by ; ; ;
  • ISBN13:

    9780471266372

  • ISBN10:

    047126637X

  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2004-08-24
  • Publisher: Wiley-IEEE Press
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Supplemental Materials

What is included with this book?

Summary

This is the first practical treatment of the design and application of feedback control of computing systems. MATLAB files for the solution of problems and case studies accompany the text throughout. The book discusses information technology examples, such as maximizing the efficiency of Lotus Notes.This book results from the authors' research into the use of control theory to model and control computing systems. This has important implications to the way engineers and researchers approach different resource management problems. This guide is well suited for professionals and researchers in information technology and computer science.

Author Biography

JOSEPH L. HELLERSTEIN, YIXIN DIAO, and SUJAY PAREKH are researchers at the IBM Thomas J. Watson Research Center in Hawthorne, New York. They are also adjunct professors at Columbia University, where they are using this book to teach a class on feedback control to computer science students. <BR> DAWN M. TILBURY is Associate Professor of Mechanical Engineering at the University of Michigan.

Table of Contents

PREFACE xv
PART I BACKGROUND 1(28)
1 Introduction and Overview
3(240)
1.1 The Nature of Feedback Control
3(3)
1.2 Control Objectives
6(1)
1.3 Properties of Feedback Control Systems
7(3)
1.4 Open-Loop versus Closed-Loop Control
10(1)
1.5 Summary of Applications of Control Theory to Computing Systems
11(2)
1.6 Computer Examples of Feedback Control Systems
13(11)
1.6.1 IBM Lotus Domino Server
13(2)
1.6.2 Queueing Systems
15(1)
1.6.3 Apache HTTP Server
16(3)
1.6.4 Random Early Detection of Router Overloads
19(1)
1.6.5 Load Balancing
20(1)
1.6.6 Streaming Media
21(1)
1.6.7 Caching with Differentiated Service
22(2)
1.7 Challenges in Applying Control Theory to Computing Systems
24(2)
1.8 Summary
26(1)
1.9 Exercises
27(2)
PART II SYSTEM MODELING 29(214)
2 Model Construction
31(34)
2.1 Basics of Queueing Theory
31(4)
2.2 Modeling Dynamic Behavior
35(7)
2.2.1 Model Variables
35(1)
2.2.2 Signals
35(3)
2.2.3 Linear, Time-Invariant Difference Equations
38(2)
2.2.4 Nonlinearities
40(2)
2.3 First-Principles Models
42(2)
2.4 Black-Box Models
44(12)
2.4.1 Model Scope
45(2)
2.4.2 Experimental Design
47(2)
2.4.3 Parameter Estimation
49(4)
2.4.4 Model Evaluation
53(3)
2.5 Summary
56(1)
2.6 Extended Examples
56(3)
2.6.1 IBM Lotus Domino Server
56(1)
2.6.2 Apache HTTP Server
57(1)
2.6.3 M/M/1/K Comparisons
58(1)
2.7 Parameter Estimation Using MATLAB
59(3)
2.8 Exercises
62(3)
3 Z-Transforms and Transfer Functions
65(46)
3.1 Z-Transform Basics
65(16)
3.1.1 Z-Transform Definition
66(2)
3.1.2 Z-Transforms of Common Signals
68(3)
3.1.3 Properties of Z-Transforms
71(3)
3.1.4 Inverse Z-Transforms
74(1)
3.1.5 Using Z-Transforms to Solve Difference Equations
75(6)
3.2 Characteristics Inferred from Z-Transforms
81(8)
3.2.1 Review of Complex Variables
81(2)
3.2.2 Poles and Zeros of a Z-Transform
83(3)
3.2.3 Steady-State Analysis
86(2)
3.2.4 Time Domain versus Z-Domain
88(1)
3.3 Transfer Functions
89(13)
3.3.1 Stability
92(3)
3.3.2 Steady-State Gain
95(1)
3.3.3 System Order
96(1)
3.3.4 Dominant Poles and Model Simplification
96(4)
3.3.5 Simulating Transfer Functions
100(2)
3.4 Summary
102(1)
3.5 Extended Examples
103(2)
3.5.1 M/M/1/K from System Identification
103(1)
3.5.2 IBM Lotus Domino Server: Sensor Delay
103(1)
3.5.3 Apache HTTP Server: Combining Control Inputs
104(1)
3.6 Z-Transforms and MATLAB
105(2)
3.7 Exercises
107(4)
4 System Modeling with Block Diagrams
111(18)
4.1 Block Diagrams Basics
111(20)
4.2 Transforming Block Diagrams
115(1)
4.2.1 Special Aggregations of Blocks
115(1)
4.3 Transfer Functions for Control Analysis
116(3)
4.4 Block Diagram Restructuring
119(1)
4.5 Summary
120(1)
4.6 Extended Examples
121(1)
4.6.1 IBM Lotus Domino Server
121(2)
4.6.2 Apache HTTP Server with Control Loops
123(1)
4.6.3 Streaming
124(2)
4.7 Composing Transfer Functions in MATLAB
126(2)
4.8 Exercises
128(1)
5 First-Order Systems
129(1)
5.1 First-Order Model
129(1)
5.2 System Response
131(34)
5.2.1 Steady-State and Transient Responses
131(2)
5.2.2 Input Signal Model
133(1)
5.2.3 Time-Domain Solution
133(2)
5.3 Initial Condition Response
135(1)
5.4 Impulse Response
136(5)
5.5 Step Response
141(1)
5.5.1 Numerical Example
141(1)
5.5.2 Time-Domain Solution
141(2)
5.5.3 Steady-State Response
143(1)
5.5.4 Transient Response
144(3)
5.6 Transient Response to Other Signals
147(1)
5.6.1 Ramp Response
147(3)
5.6.2 Frequency Response
150(2)
5.7 Effect of Stochastics
152(2)
5.8 Summary
154(2)
5.9 Extended Examples
156(1)
5.9.1 Estimating Operating Region of the Apache HTTP Server
156(1)
5.9.2 IBM Lotus Domino Server with a Disturbance
157(2)
5.9.3 Feedback Control of the IBM Lotus Domino Server
159(2)
5.10 Analyzing Transient Response with MATLAB
161(1)
5.11 Exercises
162(3)
6 Higher-Order Systems
165(36)
6.1 Motivation and Definitions
165(3)
6.2 Real Poles
168(11)
6.2.1 Initial Condition Response
168(3)
6.2.2 Impulse Response
171(3)
6.2.3 Step Response
174(2)
6.2.4 Other Signals
176(1)
6.2.5 Effect of Zeros
177(2)
6.3 Complex Poles
179(7)
6.3.1 Second-Order System
179(2)
6.3.2 Impulse Response
181(4)
6.3.3 Step Response 183 6.4 Summary
185(1)
6.5 Extended Examples
186(10)
6.5.1 Apache HTTP Server with a Filter
186(3)
6.5.2 Apache HTTP Server with a Filter and Controller
189(2)
6.5.3 IBM Lotus Domino Server with a Filter and Controller
191(1)
6.5.4 M/M/1/K with a Filter and Controller
192(4)
6.6 Analyzing Transient Response with MATLAB
196(1)
6.7 Exercises
197(4)
7 State-Space Models
201(1)
7.1 State Variables
201(1)
7.2 State-Space Models
204(1)
7.3 Solving Difference Equations in State Space
207(1)
7.4 Converting Between Transfer Function Models and State-Space Models
211(1)
7.5 Analysis of State-Space Models
216(29)
7.5.1 Stability Analysis of State-Space Models
216(2)
7.5.2 Steady-State Analysis of State-Space Models
218(2)
7.5.3 Transient Analysis of State-Space Models
220(1)
7.6 Special Considerations in State-Space Models
221(1)
7.6.1 Equivalence of State Variables
221(1)
7.6.2 Controllability
222(3)
7.6.3 Observability
225(3)
7.7 Summary
228(1)
7.8 Extended Examples
229(1)
7.8.1 MIMO System Identification of the Apache HTTP Server
229(5)
7.8.2 State-Space Model of the IBM Lotus Domino Server with Sensor Delay
234(3)
7.9 Constructing State-Space Models in MATLAB
237(2)
7.10 Exercises
239(4)
PART III CONTROL ANALYSIS AND DESIGN 243(154)
8 Proportional Control
245(48)
8.1 Control Laws and Controller Operation
245(7)
8.2 Desirable Properties of Controllers
252(2)
8.3 Framework for Analyzing Proportional Control
254(7)
8.3.1 Closed-Loop Transfer Functions
255(2)
8.3.2 Stability
257(1)
8.3.3 Accuracy
258(2)
8.3.4 Settling Time
260(1)
8.3.5 Maximum Overshoot
260(1)
8.4 P-Control: Robustness, Delays, and Filters
261(10)
8.4.1 First-Order Target System
261(5)
8.4.2 Measurement Delay
266(2)
8.4.3 Moving-Average Filter
268(3)
8.5 Design of Proportional Controllers
271(4)
8.6 Summary
275(1)
8.7 Extended Examples
276(10)
8.7.1 IBM Lotus Domino Server with a Moving-Average Filter
276(2)
8.7.2 Apache with Precompensation
278(4)
8.7.3 Apache with Disturbance Rejection
282(1)
8.7.4 Effect of Operating Region on M/M/1/K Control
282(4)
8.8 Designing P-Controllers in MATLAB
286(3)
8.9 Exercises
289(4)
9 PID Controllers
293(44)
9.1 Integral Control
293(8)
9.1.1 Steady-State Error with Integral Control
294(2)
9.1.2 Transient Response with Integral Control
296(5)
9.2 Proportional-Integral Control
301(14)
9.2.1 Steady-State Error with PI Control
303(1)
9.2.2 PI Control Design by Pole Placement
303(4)
9.2.3 PI Control Design Using Root Locus
307(2)
9.2.4 PI Control Design Using Empirical Methods
309(6)
9.3 Proportional-Derivative Control
315(5)
9.4 PID Control
320(4)
9.5 Summary
324(1)
9.6 Extended Examples
325(7)
9.6.1 PI Control of the Apache HTTP Server Using Empirical Methods
325(2)
9.6.2 Designing a PI Controller for the Apache HTTP Server Using Pole Placement Design
327(1)
9.6.3 IBM Lotus Domino Server with a Sensor Delay
328(2)
9.6.4 Caching with Feedback Control
330(2)
9.7 Designing PI Controllers in MATLAB
332(1)
9.8 Exercises
333(4)
10 State-Space Feedback Control
337(38)
10.1 State-Space Analysis
337(2)
10.2 State Feedback Control Systems
339(14)
10.2.1 Static State Feedback
340(2)
10.2.2 Precompensated Static State Feedback
342(4)
10.2.3 Dynamic State Feedback
346(5)
10.2.4 Comparison of Control Architectures
351(2)
10.3 Design Techniques
353(9)
10.3.1 Pole Placement Design
353(5)
10.3.2 LQR Optimal Control Design
358(4)
10.4 Summary
362(2)
10.5 Extended Examples
364(8)
10.5.1 MIMO Control of the Apache HTTP Server
364(6)
10.5.2 Effect of the LQR Design Parameters in a Dynamic State Feedback System
370(2)
10.6 Designing State-Space Controllers Using MATLAB
372(1)
10.7 Exercises
373(2)
11 Advanced Topics
375(28)
11.1 Motivating Example
376(2)
11.2 Gain Scheduling
378(3)
11.3 Self-Tuning Regulators
381(3)
11.4 Minimum-Variance Control
384(2)
11.5 Fluid Flow Analysis
386(3)
11.6 Fuzzy Control
389(4)
11.7 Summary
393(2)
11.8 Exercises
395(2)
APPENDIX A MATHEMATICAL NOTATION 397(4)
APPENDIX B ACRONYMS 401(2)
APPENDIX C KEY RESULTS 403(6)
C.1 Modeling
403(1)
C.1.1 Dominant Pole Approximation
403(1)
C.1.2 Closed-Loop Transfer Functions
403(1)
C.2 Analysis
404(1)
C.2.1 Stability
404(1)
C.2.2 Settling Time
405(1)
C.2.3 Maximum Overshoot
405(1)
C.2.4 Steady-State Gain
405(1)
C.3 Controller Design
405(4)
C.3.1 Control Laws
405(1)
C.3.2 Pole Placement Design
406(1)
C.3.3 LQR Design
407(2)
APPENDIX D ESSENTIALS OF LINEAR ALGEBRA 409(4)
D.1 Matrix Inverse, Singularity
409(1)
D.2 Matrix Minor, Determinant, and Adjoint
409(1)
D.3 Vector Spaces
410(1)
D.4 Matrix Rank
411(1)
D.5 Eigenvalues
411(2)
APPENDIX E MATLAB BASICS 413(8)
E.1 Variables and Values
413(3)
E.1.1 Vectors
414(1)
E.1.2 Matrices
415(1)
E.2 Functions
416(1)
E.3 Plotting
417(1)
E.4 M-files
418(2)
E.5 Summary of MATLAB Functions and Commands
420(1)
REFERENCES 421(6)
INDEX 427

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