Download - Introduction to Feedback and Control
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 , [email protected] ,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
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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
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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
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Welcome to
ESE406/505- MEAM513
Control Systems
Instructor: Ali Jadbabaie
Course website:
on Blackboard