book

Feedback Control for Computer Systems

by Philipp K. Janert

October 2013

Intermediate to advanced

330 pages

7h 46m

English

O'Reilly Media, Inc.

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What Is Feedback?Why This Book?How to Read This BookConventions Used in This BookUsing Code ExamplesSafari® Books OnlineHow to Contact UsAcknowledgments
A Hands-On ExampleHoping for the BestEstablishing ControlAdding It UpSummaryCode to Play With
Systems and SignalsTracking Error and Corrective ActionStability, Performance, Accuracy The SetpointUncertainty and Change Feedback and FeedforwardFeedback and Enterprise SystemsCode to Play With
Lags and Delays Forced Response and Free Response Transient Response and Steady-State ResponseDynamics in the Physical World and in the Virtual World Dynamics and MemoryThe Importance of Lags and Delays for Feedback Loops Avoiding DelaysTheory and PracticeCode to Play With
Block DiagramsOn/Off ControlProportional Control Why Proportional Control Is Not EnoughIntegral Control Integral Control Changes the Dynamics Integral Control Can Generate a Constant OffsetDerivative Control Problems with Derivative ControlThe Three-Term or PID ControllerCode to Play With
Control Input and Output Directionality of the Input/Output RelationExamples Thermal Control 1: HeatingSituationInputOutputCommentary Item CacheSituationInputOutputCommentary Server ScalingSituationInputOutputCommentary Controlling Supply and Demand by Dynamic PricingSituationInputOutputCommentary Thermal Control 2: CoolingSituationInputOutputCommentaryCriteria for Selecting Control Signals For Control Inputs For Control OutputsA Note on Multidimensional Systems
The Feedback IdeaIterationProcess KnowledgeAvoiding InstabilityThe SetpointControl, Not Optimization
Frequency RepresentationThe Transfer FunctionBlock-Diagram AlgebraPID ControllersPoles of the Transfer FunctionProcess Models

Static Input/Output Relation: The Process Characteristic Practical ConsiderationsDynamic Response to a Step Input: The Process Reaction Curve Practical AspectsProcess Models Self-Regulating Process Accumulating Process Self-Regulating Process with Oscillation Non-Minimum Phase SystemOther Methods of System Identification
Tuning ObjectivesGeneral Effect of Changes to Controller ParametersZiegler–Nichols TuningSemi-Analytical Tuning Methods Practical AspectsA Closer Look at Controller Tuning Formulas
Actuator Saturation and Integrator Windup Preventing Integrator Windup Setpoint Changes and Integrator PreloadingSmoothing the Derivative TermChoosing a Sampling IntervalVariants of the PID Controller Incremental Form Error Feedback Versus Output Feedback The General Linear Digital ControllerNonlinear Controllers Error-Square and Gap Controllers Simulating Floating-Point Output Categorical Output
Changing Operating Conditions: Gain Scheduling Gain Scheduling for Mildly Nonlinear SystemsLarge Disturbances: FeedforwardFast and Slow Dynamics: Nested or “Cascade” ControlSystems Involving Delays: The Smith Predictor
The Case StudiesModeling Time Control Time Simulation TimeThe Simulation Framework Components Plants and Systems Controllers Actuators and Filters Convenience Functions for Standard Loops Generating Graphical Output
Defining Components Cache Misses as Manufacturing DefectsMeasuring System CharacteristicsController TuningSimulation Code
The SituationMeasuring System CharacteristicsEstablishing ControlImproving PerformanceVariations Cumulative Goal Gain Scheduling Integrator Preloading Weekend EffectsSimulation Code
The SituationMeasuring and TuningReaching 100 Percent With a Nonstandard ControllerDealing with LatencySimulation Code
On the Nature of Queues and BuffersThe ArchitectureSetup and TuningDerivative Control to the RescueController AlternativesSimulation Code
The SituationThe ModelTuning and CommissioningClosed-Loop PerformanceSimulation Code
The SituationProblem AnalysisArchitecture Alternatives A Nontraditional Loop Arrangement A Traditional Loop with LogarithmsResultsSimulation Code
Simple Controllers, Simple LoopsMeasuring and TuningStaying in ControlDealing with Noise
Differential EquationsLaplace Transforms Properties of the Laplace TransformUsing the Laplace Transform to Solve Differential Equations A Worked ExampleThe Transfer Function Worked Example: Step Response Worked Example: Ramp Input The Harmonic OscillatorWhat If the Differential Equation Is Not Known?
Composite SystemsThe Feedback Equation An Alternative Derivation of the Feedback EquationBlock-Diagram AlgebraLimitations and Importance of Transfer Function Methods
The Transfer Function of the PID ControllerThe Canonical Form of the PID ControllerThe General ControllerProportional Droop Revisited A Worked Example
Structure of a Transfer FunctionEffect of Poles and Zeros Special Cases and Additional DetailsComplex conjugate polesMultiple polesPoles on the imaginary axisPole/zero cancellationsPole Positions and Response Patterns Dominant Poles Pole PlacementWhat to Do About Delays
Construction of Root Locus DiagramsRoot Locus or “Evans” RulesAngle and Magnitude CriteriaPractical IssuesExamples Simple Lag with a P Controller Simple Lag with a PI Controller
Frequency Response Frequency Response in the Physical World Frequency Response for Transfer Functions A Worked ExampleThe Bode PlotA Criterion for Marginal StabilityOther Graphical Techniques
Discrete-Time Modeling and the z-TransformState-Space MethodsRobust ControlOptimal ControlMathematical Control Theory
Basic PlottingPlot RangesInline TransformationsPlotting Simulation ResultsSummary
Basic OperationsPolar CoordinatesThe Complex Exponential
Recommended ReadingAdditional ReferencesMathematical Prerequisites

Content preview from Feedback Control for Computer Systems

Chapter 1. Why Feedback? An Invitation

Workflow, order processing, ad delivery, supply chain management—enterprise systems are often built to maintain the flow of certain items through various processing steps. For instance, at a well-known online retailer, one of our systems was responsible for managing the flow of packages through the facilities. Our primary control mechanism was the number of pending orders we would release to the warehouses at any one time. Over time, these orders would turn into shipments and be ready to be loaded onto trucks. The big problem was to throttle the flow of pending orders just right so that the warehouses were never idle, but without overflowing them (quite literally) either.

Later I encountered exactly the same problem, but in an entirely different context, at a large publisher of Internet display ads. In this case, the flow consisted of ad impressions.^[1] Again, the primary “knob” that we could adjust was the number of ads released to the web servers, but the constraint was a different one. Overflowing the servers was not a concern, but it was essential to achieve an even delivery of ads from various campaigns over the course of the month. Because the intensity of web traffic changes from hour to hour and from day to day, we were constantly struggling to accomplish this goal.

As these two examples demonstrate, maintaining an even flow of items or work units, while neither overwhelming nor starving downstream processing steps, is a common objective ...