ESE406/505-MEAM513: Lecture 1 Introduction to Feedback and Control

Ali Jadbabaie

January 11, 2005

Goals:Give an overview of the course; describe course structure, administration Define feedback/control systems and learn how to recognize main featuresDescribe what control systems do and the primary principles of control

Reading (available on course web page): Astrom and Murray, Analysis and Design of Feedback Systems, Ch 1“For the Spy in the Sky, New Eyes”, NY Times, June 2002.

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Course AdministrationAnnouncements :

•First class is on Tuesday January 13th 2004 in Towne 313 from 12:00-1:30pm.

Course Description: This course is an introduction to analysis and design of feedback control systems, including classical control theory in the time and frequency domain. Modeling of physical, biological and information systems using linear and nonlinear differential equations. Stability and performance of interconnected systems, including use of block diagrams, Bode plots, Nyquist criterion, and Design of feedback controllers. Suggested pre-requisites: Basic course on ordinary differential equations and linear algebra. For Systems Engineering Students: knowledge of ESE 210 (SYS 200) material.For EE students: Knowledge of signals and systems (ESE 325)Instructor:

•Ali Jadbabaie , jadbabai@seas.upenn.edu ,Office hours : Wednesdays 2:00-4:00pm, 365 GRW Moore bldg.

Lectures: T- TR 12:00-1:30pm, Towne 313. Textbook:

•Feedback Control of Dynamic Systems, by Franklin, Powell and Emami Naieni, 4th Edition, Prentice Hall, 2002. Other References:

•Modern Control Engineering, 4th Edition, by K. Ogata, Prentice Hall, 2001 •Modern Control Systems, 9th Edition, by Dorf and Bishop, Prentice Hall, 2001. •Automatic Control Systems, by B. Kuo, Prentice Hall, 1995.

Course Notes and Links Reading material for the class will be posted on blackboardRequired reading sources

•R. M. Murray (ed), Control in an Information Rich World: Report of the Panel on Future Directions in Control, Dynamics, and Systems, SIAM, 2002. Available online at http://www.cds.caltech.edu/~murray/cdspanel/ •K. J. Åström and Richard M. Murray, Analysis and Design of Feedback Systems, Preprint, 2004. Online access on blackboard•J. Doyle, B. Francis, and A. Tannenbaum, Feedback Control Theory, McMillan, 1992. Online access on blackboard

•Grading : Homeworks : 20% Midterm I: 35% Midterm II : 45% •Teaching assistants: Nima Moshtagh , Ali Ahmadzadeh

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Controls Course Sequence

ESE406/505-MEAM513 – Introduction to the principles and tools of control and feedbackSummarize key concepts, w/ examples of fundamental principles at work Introduce MATLAB-based tools for modeling, simulation, and analysis Introduction to control designProvide knowledge to work with control engineers in a team setting

ESE500 – Linear Systems TheoryDetailed description of state space concepts.Rigorous analysis and synthesis of time invariant and time varying

systems.

ESE 617/MEAM 613- Nonlinear Systems

• Tools and algorithms for analysis and design of nonlinear control systems

SpringFall

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What is Feedback?

Miriam Webster: the return to the input of a part of the

output of a machine, system, or process (as for producing changes in an electronic circuit that improve performance or in an automatic control device that provide self-corrective action) [1920]

Feedback = mutual interconnection of two (or more) systemsSystem 1 affects system 2System 2 affects system 1Cause and effect is tricky; systems

are mutually dependent

Feedback is ubiquitous in natural and engineered systems

Terminology

System 2

System 1

System 2System 1

System 2System 1

ClosedLoop

OpenLoop

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What do these two have in common?

Tornado Boeing 777

• Highly nonlinear, complicated dynamics!• Both are capable of transporting goods and people over long distances

BUT

• One is controlled, and the other is not.• Control is “the hidden technology that you meet every day”• It heavily relies on the notion of “feedback”

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Example #1: Flyball Governor

“Flyball” Governor (1788) Regulate speed of steam engine Reduce effects of variations in load

(disturbance rejection) Major advance of industrial revolution

Balls fly out as speed increases,

Valve closes,slowing engine

http://www.heeg.de/~roland/SteamEngine.htmlBoulton-Watt steam engine

Flyballgovernor

Steamengine

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Other Examples of Feedback

Biological SystemsPhysiological regulation (homeostasis)Bio-molecular regulatory networks

Environmental SystemsMicrobial ecosystemsGlobal carbon cycle

Financial SystemsMarkets and exchangesSupply and service chains

ESE

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Control = Sensing + Computation + Actuation

SenseVehicle Speed

ComputeControl “Law”

ActuateGas Pedal

In Feedback “Loop”

GoalsStability: system maintains desired operating point (hold steady speed)Performance: system responds rapidly to changes (accelerate to 65 mph)Robustness: system tolerates perturbations in dynamics (mass, drag, etc)

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A modern Feedback Control System

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Two Main Principles of Control

Robustness to Uncertainty through FeedbackFeedback allows high performance in the

presence of uncertaintyExample: repeatable performance of

amplifiers with 5X component variationKey idea: accurate sensing to compare

actual to desired, correction through computation and actuation

Design of Dynamics through FeedbackFeedback allows the dynamics of a

system to be modifiedExample: stability augmentation for highly

agile, unstable aircraftKey idea: interconnection gives closed

loop that modifies natural behaviorX-29 experimental aircraft

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Example #2: Cruise Control

engine hill

engine des( )

mv bv u u

u k v v

Control System++-

disturbance

reference

Stability/performanceSteady state velocity approaches

desired velocity as k Smooth response; no overshoot or

oscillations

Disturbance rejectionEffect of disturbances (hills)

approaches zero as k RobustnessResults don’t depend on the specific

values of b, m, or k for k sufficiently large

ss des hill

1kv v u

b k b k

time

velocity

vdes

1 ask

0 ask

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Example #3: Insect Flight

More information: M. D. Dickinson, Solving the mystery of

insect flight, Scientific American, June 2001.

ACTUATION

two wings(di-ptera)

specialized“power”muscles

SENSING

neuralsuperposition

eyes

hind winggyroscopes(halteres)

COMPUTATION

~500,000 neurons

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EXAMPLE # 4: Coordinated Control of Manned and Unmanned Systems

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Other Examples

Cruise control

Electronic ignition

Temperature control

Electronic fuel injection

Anti-lock brakes

Electronic transmission

Electric power steering (PAS)

Air bags

Active suspension

EGR control

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Brakes

Airbags

Seatbelts

MirrorsWipers

Headlights

Steering

GPS Radio

ShiftingTraction control

Anti-skid

Electronic ignition

Electronic fuel injectionTemperature control

Cruise control

Bumpers Fenders

Suspension (control)

Seats

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essential: 230   nonessential: 2373   unknown: 1804   total: 4407

http://www.shigen.nig.ac.jp/ecoli/pec

Gene networks?

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essential: 230   nonessential: 2373  

Are these “redundant?”

No!

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Regulatory feedback

Cartoon of E. Coli metabolism

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Regulatory feedback

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Decision

SensingActuation

Signaling

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Organized complexity

Simple behavior

Robust and adaptive

Evolvable

Enormous “hidden” complexity

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Segway: The human Transporter

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Modern Engineering Applications of Control

Flight Control SystemsModern commercial and military

aircraft are “fly by wire”Autoland systems, unmanned

aerial vehicles (UAVs) are already in place

RoboticsHigh accuracy positioning for

flexible manufacturingRemote environments: space, sea,

non-invasive surgery, etc.

Chemical Process ControlRegulation of flow rates,

temperature, concentrations, etc.Long time scales, but only crude

models of process

Communications and NetworksAmplifiers and repeatersCongestion control of the InternetPower management for wireless

communications

AutomotiveEngine control, transmission

control, cruise control, climate control, etc

Luxury sedans: 12 control devices in 1976, 42 in 1988, 67 in 1991

AND MANY MORE...

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The Internet: Largest feedback system built by man

IP

Web FTP Mail News Video Audio ping napster

Applications

TCP SCTP UDP ICMP

Transport protocols

Ethernet 802.11 SatelliteOpticalPower lines BluetoothATM

Link technologies

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The Internet hourglass

IP

Web FTP Mail News Video Audio ping napster

Applications

TCP

Ethernet 802.11 SatelliteOpticalPower lines BluetoothATM

Link technologies

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The Internet hourglass

IP

Web FTP Mail News Video Audio ping napster

Applications

TCP

Ethernet 802.11 SatelliteOpticalPower lines BluetoothATM

Link technologies

IP under everything

IP oneverything

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Network protocols.

HTTP

TCP

IP

Files

packetspacketspacketspacketspacketspackets

Sources

Links

Files

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Protocol stack

Applications

TCP

IP

Hardware

Modules

packetspacketspacketspacketspacketsIP packets

Files

packetspacketspacketspacketspacketsTCP packets

packetspacketspacketspacketspacketsLayer 2 packets

packetspacketspacketspacketspacketsBits

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Animation of the protocols

HTTP

TCP

Files Files

packetspacketspacketspacketspacketsTCP packets

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Animation of the protocols

HTTP

TCP

IP

Files

packetspacketspacketspacketspacketspackets

Files

packetspacketspacketspacketspacketsTCP packets packetspacketspacketspacketspacketsTCP packets

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Animation of the protocols

HTTP

TCP

IP

Files Files

packetspacketspacketspacketspacketsTCP packets packetspacketspacketspacketspacketsTCP packets

packetspacketspacketspacketspacketsIP packetspacketspacketspacketspacketspacketsIP packets

Sources

LinkspacketspacketspacketspacketspacketsLayer 2 packets

packetspacketspacketspacketspacketsBits

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IP IPIP IP IP

TCP

Application

TCP

Application

TCP

Application

RoutingProvisioning

Ver

tica

l dec

ompo

siti

onP

roto

col S

tack

Each layer can evolve independently provided:

1. Follow the rules2. Everyone else does

“good enough” with their layer

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IP IPIP IP IP

TCP

Application

TCP

Application

TCP

Application

RoutingProvisioning

Horizontal decompositionEach level is decentralized and asynchronous

January 11, 2005 35

IP IPIP IP IP

TCP

Application

TCP

Application

TCP

Application

RoutingProvisioningHorizontal decomposition

Ver

tica

l dec

ompo

siti

on• Entirely different from the telephone system, although the parts are essentially identical (VLSI, copper, and fiber)• The Internet is much more like biology and relies on feedback regulation at every level.• Only recently has a coherent theory of the Internet started to emerge and pay off.

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Internet

Link

IP

TCP

Application

Simplify

DeviceBoard

Computer

OperatingSystem

IP

TCP

Application

Interface

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Sources

Links

January 11, 2005 38

Hosts

Routers

packets

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Hosts

Routers

packets

Hidden from the user

Files

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Hosts

Routers

packets

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Hosts

Routers

packets

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Control Tools

Modeling Input/output representations for subsystems +

interconnection rulesSystem identification theory and algorithms Theory and algorithms for reduced order modeling

+ model reduction

AnalysisStability of feedback systems, including

robustness “margins”Performance of input/output systems (disturbance

rejection, robustness)

SynthesisConstructive tools for design of feedback systemsConstructive tools for signal processing and

estimation (Kalman filters)

MATLAB Toolboxes SIMULINK Control System Neural Network Data Acquisition Optimization Fuzzy Logic Robust Control Instrument Control Signal Processing LMI Control Statistics Model Predictive Control System Identification µ-Analysis and

Synthesis 

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Magic of Feedback

• Feedback is used to regulate the value of a quantity in a system to a desired level, by measuring the error, i.e., difference between the desired value and the sensed value.

•Sometimes the decision is based on the instantaneous value of error, and sometimes is based on the history of the error, and/or predictions on the future value of the error. Some times we use all three.

•The performance of a feedback system is measured based on the response to a “step” change in the reference, or in tracking a sinusoid.

• Feedback regulation will work even when the “components” are uncertain.

• The down side of using feedback is that It can cause instability It makes the design more complicated

• The main components of a feedback loop are sensing, decision/computation, and actuation.• We will use theory of differential equations, linear algebra and complex variables to analyze feedback systems.

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Overview of the Course

Wk Tue/Thur

1 Introduction to Feedback and Control

2-3 System Modeling/Analysis, Review of ODEs, and Laplace Transform

4-5 Stability and Performance

6-7 Tests for stability

8-9 Root locus analysis. Design for time domain specs.

10-11

Frequency Domain Design: Bode plot.

12-14

Loop Analysis of Feedback Systems. Nyquist criterion

15 Fundamental Limits on Performance

16 Uncertainty Analysis and Robustness

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Summary: Introduction to Feedback and Control

Sense

Compute

Actuate

Control =

Sensing + Computation +Actuation

Feedback PrinciplesRobustness to UncertaintyDesign of Dynamics

Many examples of feedback and control in natural & engineered systems:

BIO

BIOESE

ESE

CS

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Summary

Feedback control is Every where you just have to look for it

January 11, 2005 47

Welcome to

ESE406/505- MEAM513

Control Systems

Instructor: Ali Jadbabaie

jadbabai@seas.upenn.edu

Course website:

on Blackboard