Feedback Control of Computing Systems.

Other records:
Hellerstein, Joseph L.
1st ed.
Hoboken : John Wiley & Sons, Incorporated, 2004.
Wiley - IEEE Ser.
Wiley - IEEE Ser.
1 online resource (451 pages)
Feedback control systems.
Control theory.
Electronic data processing.
Electronic books.
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. DAWN M. TILBURY is Associate Professor of Mechanical Engineering at the University of Michigan.
Feedback Control of Computing Systems
1 Introduction and Overview
1.1 The Nature of Feedback Control
1.2 Control Objectives
1.3 Properties of Feedback Control Systems
1.4 Open-Loop versus Closed-Loop Control
1.5 Summary of Applications of Control Theory to Computing Systems
1.6 Computer Examples of Feedback Control Systems
1.6.1 IBM Lotus Domino Server
1.6.2 Queueing Systems
1.6.3 Apache HTTP Server
1.6.4 Random Early Detection of Router Overloads
1.6.5 Load Balancing
1.6.6 Streaming Media
1.6.7 Caching with Differentiated Service
1.7 Challenges in Applying Control Theory to Computing Systems
1.8 Summary
1.9 Exercises
2 Model Construction
2.1 Basics of Queueing Theory
2.2 Modeling Dynamic Behavior
2.2.1 Model Variables
2.2.2 Signals
2.2.3 Linear, Time-Invariant Difference Equations
2.2.4 Nonlinearities
2.3 First-Principles Models
2.4 Black-Box Models
2.4.1 Model Scope
2.4.2 Experimental Design
2.4.3 Parameter Estimation
2.4.4 Model Evaluation
2.5 Summary
2.6 Extended Examples
2.6.1 IBM Lotus Domino Server
2.6.2 Apache HTTP Server
2.6.3 M/M/1/K Comparisons
*2.7 Parameter Estimation Using MATLAB
2.8 Exercises
3 Z-Transforms and Transfer Functions
3.1 Z-Transform Basics
3.1.1 Z-Transform Definition
3.1.2 Z-Transforms of Common Signals
3.1.3 Properties of Z-Transforms
3.1.4 Inverse Z-Transforms
3.1.5 Using Z-Transforms to Solve Difference Equations
3.2 Characteristics Inferred from Z-Transforms
3.2.1 Review of Complex Variables
3.2.2 Poles and Zeros of a Z-Transform
3.2.3 Steady-State Analysis
3.2.4 Time Domain versus Z-Domain
3.3 Transfer Functions
3.3.1 Stability
3.3.2 Steady-State Gain
3.3.3 System Order.
3.3.4 Dominant Poles and Model Simplification
3.3.5 Simulating Transfer Functions
3.4 Summary
3.5 Extended Examples
3.5.1 M/M/1/K from System Identification
3.5.2 IBM Lotus Domino Server: Sensor Delay
3.5.3 Apache HTTP Server: Combining Control Inputs
*3.6 Z-Transforms and MATLAB
3.7 Exercises
4 System Modeling with Block Diagrams
4.1 Block Diagrams Basics
4.2 Transforming Block Diagrams
4.2.1 Special Aggregations of Blocks
4.3 Transfer Functions for Control Analysis
4.4 Block Diagram Restructuring
4.5 Summary
4.6 Extended Examples
4.6.1 IBM Lotus Domino Server
4.6.2 Apache HTTP Server with Control Loops
4.6.3 Streaming
*4.7 Composing Transfer Functions in MATLAB
4.8 Exercises
5 First-Order Systems
5.1 First-Order Model
5.2 System Response
5.2.1 Steady-State and Transient Responses
5.2.2 Input Signal Model
5.2.3 Time-Domain Solution
5.3 Initial Condition Response
5.4 Impulse Response
5.5 Step Response
5.5.1 Numerical Example
5.5.2 Time-Domain Solution
5.5.3 Steady-State Response
5.5.4 Transient Response
5.6 Transient Response to Other Signals
5.6.1 Ramp Response
5.6.2 Frequency Response
5.7 Effect of Stochastics
5.8 Summary
5.9 Extended Examples
5.9.1 Estimating Operating Region of the Apache HTTP Server
5.9.2 IBM Lotus Domino Server with a Disturbance
5.9.3 Feedback Control of the IBM Lotus Domino Server
*5.10 Analyzing Transient Response with MATLAB
5.11 Exercises
6 Higher-Order Systems
6.1 Motivation and Definitions
6.2 Real Poles
6.2.1 Initial Condition Response
6.2.2 Impulse Response
6.2.3 Step Response
6.2.4 Other Signals
6.2.5 Effect of Zeros
6.3 Complex Poles
6.3.1 Second-Order System
6.3.2 Impulse Response
6.3.3 Step Response
6.4 Summary
6.5 Extended Examples.
6.5.1 Apache HTTP Server with a Filter
6.5.2 Apache HTTP Server with a Filter and Controller
6.5.3 IBM Lotus Domino Server with a Filter and Controller
6.5.4 M/M/1/K with a Filter and Controller
*6.6 Analyzing Transient Response with MATLAB
6.7 Exercises
7 State-Space Models
7.1 State Variables
7.2 State-Space Models
7.3 Solving Difference Equations in State Space
7.4 Converting Between Transfer Function Models and State-Space Models
7.5 Analysis of State-Space Models
7.5.1 Stability Analysis of State-Space Models
7.5.2 Steady-State Analysis of State-Space Models
7.5.3 Transient Analysis of State-Space Models
7.6 Special Considerations in State-Space Models
7.6.1 Equivalence of State Variables
7.6.2 Controllability
7.6.3 Observability
7.7 Summary
7.8 Extended Examples
7.8.1 MIMO System Identification of the Apache HTTP Server
7.8.2 State-Space Model of the IBM Lotus Domino Server with Sensor Delay
*7.9 Constructing State-Space Models in MATLAB
7.10 Exercises
8 Proportional Control
8.1 Control Laws and Controller Operation
8.2 Desirable Properties of Controllers
8.3 Framework for Analyzing Proportional Control
8.3.1 Closed-Loop Transfer Functions
8.3.2 Stability
8.3.3 Accuracy
8.3.4 Settling Time
8.3.5 Maximum Overshoot
8.4 P-Control: Robustness, Delays, and Filters
8.4.1 First-Order Target System
8.4.2 Measurement Delay
8.4.3 Moving-Average Filter
8.5 Design of Proportional Controllers
8.6 Summary
8.7 Extended Examples
8.7.1 IBM Lotus Domino Server with a Moving-Average Filter
8.7.2 Apache with Precompensation
8.7.3 Apache with Disturbance Rejection
8.7.4 Effect of Operating Region on M/M/1/K Control
*8.8 Designing P-Controllers in MATLAB
8.9 Exercises
9 PID Controllers.
9.1 Integral Control
9.1.1 Steady-State Error with Integral Control
9.1.2 Transient Response with Integral Control
9.2 Proportional-Integral Control
9.2.1 Steady-State Error with PI Control
9.2.2 PI Control Design by Pole Placement
9.2.3 PI Control Design Using Root Locus
9.2.4 PI Control Design Using Empirical Methods
9.3 Proportional-Derivative Control
9.4 PID Control
9.5 Summary
9.6 Extended Examples
9.6.1 PI Control of the Apache HTTP Server Using Empirical Methods
9.6.2 Designing a PI Controller for the Apache HTTP Server Using Pole Placement Design
9.6.3 IBM Lotus Domino Server with a Sensor Delay
9.6.4 Caching with Feedback Control
*9.7 Designing PI Controllers in MATLAB
9.8 Exercises
10 State-Space Feedback Control
10.1 State-Space Analysis
10.2 State Feedback Control Systems
10.2.1 Static State Feedback
10.2.2 Precompensated Static State Feedback
10.2.3 Dynamic State Feedback
10.2.4 Comparison of Control Architectures
10.3 Design Techniques
10.3.1 Pole Placement Design
10.3.2 LQR Optimal Control Design
10.4 Summary
10.5 Extended Examples
10.5.1 MIMO Control of the Apache HTTP Server
10.5.2 Effect of the LQR Design Parameters in a Dynamic State Feedback System
*10.6 Designing State-Space Controllers Using MATLAB
10.7 Exercises
11 Advanced Topics
11.1 Motivating Example
11.2 Gain Scheduling
11.3 Self-Tuning Regulators
11.4 Minimum-Variance Control
11.5 Fluid Flow Analysis
11.6 Fuzzy Control
11.7 Summary
11.8 Exercises
C.1 Modeling
C.1.1 Dominant Pole Approximation
C.1.2 Closed-Loop Transfer Functions
C.2 Analysis
C.2.1 Stability
C.2.2 Settling Time
C.2.3 Maximum Overshoot
C.2.4 Steady-State Gain.
C.3 Controller Design
C.3.1 Control Laws
C.3.2 Pole Placement Design
C.3.3 LQR Design
D.1 Matrix Inverse, Singularity
D.2 Matrix Minor, Determinant, and Adjoint
D.3 Vector Spaces
D.4 Matrix Rank
D.5 Eigenvalues
E.1 Variables and Values
E.1.1 Vectors
E.1.2 Matrices
E.2 Functions
E.3 Plotting
E.4 M-files
E.5 Summary of MATLAB Functions and Commands
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2021. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Diao, Yixin.
Parekh, Sujay.
Tilbury, Dawn M.
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Print version: Hellerstein, Joseph L. Feedback Control of Computing Systems
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