introduction tointelligent control part 1keffe006/workshop/ece4951-lecture1.pdf · introduction...
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Introduction to Intelligent Control
Part 1
ECE 4951 - Spring 2010
Prof. Marian S. StachowiczLaboratory for Intelligent Systems
ECE Department, University of Minnesota Duluth
January 19 - 21, 2010
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Instructors
• INSTRUCTORS: Prof. Marian S. Stachowicz,
• MWAH 273, phone: 218- 726-6531,
• http://www.d.umn.edu/ece/lis
• TIME/LOCATION: Lectures (first three weeks)
• T, Th, 8:00 – 8:50, MWAH 191
• F 16:00 – 16:50, MWAH 175
•• Laboratories (first three weeks)
• F 14:00 – 15:50, MWAH 293, • F 14:00 – 15:50, MWAH 293,
• 8 hours per week, MWAH 293 (next 10 weeks)
•• OFFICE HOURS: 14:00 - 15:30, T, Th, MWAH 273
••• CONSULTANT: Prof. Christopher Carroll
• MWAH 252, phone: 218 - 726-7530,
•• OFFICE HOURS: TBA, MWAH 252
•
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REFERENCES
• 1. M.S. Stachowicz and L. Beall , Fuzzy Logic Package for Mathematica, Version 5.2, Wolfram Research, Inc., 2003
• 2. R.C. Dorf and R.H. Bishop, Modern Control Systems, 11th Edition, Prentice Hall, 2008, 11th Edition, Prentice Hall, 2008,
• 3. Kasuo Tanaka, An Introduction to Fuzzy Logic for Practical Applications, Springer, 1997
• 4. J. Yen and R. Langari, Fuzzy Logic, Prentice Hall, Inc., 1999
• 5. K.M. Passino and S. Yurkovich, Fuzzy Control, Addison Wesley Longman, Inc., 1998
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• 6. D. J. Pack, Steven F. Barrett, The 68HC12 Microcontroller: The theory and Applications, Prentice Hall, 2008
• 7. F. M. Cady, Software and Hardware Engineering, Oxford University Press, Inc.,2008
• 8. H.R. Everett, Sensors for Mobile Robots, A K Peters, 1995• 8. H.R. Everett, Sensors for Mobile Robots, A K Peters, 1995• 9. ECE 4899-4999, ECE 4951 – ECE Senior Design Project
Handbook, ECE Dep. 2009
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References for reading
1. R.C. Dorf and R.H. Bishop, Modern Control Systems,
10th Edition, Prentice Hall, 2008,Chapter 1.1 - 1.10
2. J.J. DiStefano, A. R. Stubberud, I. J. Williams, Feeedbackand Control Systems, Schaum's Outline Series, McGraw-Hill, Inc., 1990Chapters 1, 2
Control Systems
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Control
• The word control is usually taken to mean :
- regulate,
- direct,- direct,
- command.
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Control system
• A control system is an interconnection of
components forming a system configuration that
will provide a desired system response.will provide a desired system response.
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The Input – Output relationship represent the Cause – Effect relationship
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Input
• The input is the stimulus, excitation or
command applied to a control system.
• Typically from external energy source,
usually in order to produce a specified
response from the control system.
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Output
• The output is the actual response obtained
from a control system.
• It may or may not be equal to specified
response implied by the input.
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Two Types of Control Systems
• Open Loop
– No feedback
– Difficult to control
output with accuracy
• Closed Loop
– Must have feedback
– Must have sensor on output
– Almost always negative output with accuracy – Almost always negative
feedback
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Open-loop control
An open-loop control system utilizes an actuating
device to control the process directly without using
feedback.
A common example of an open-loop control system
is an electric toaster in the kitchen.
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Closed-loop control
A closed-loop control system uses a measurement
of the output and feedback of this signal to
compare it with the desired output.compare it with the desired output.
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Manual control system
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Goal: Regulate the level of fluid by adjusting the output valve.
The input is a reference level of fluid and is memorized by operator.The power amplifier is the operator.The sensor is visual.Operator compares the actual level with the desired level and opens or closes the valve ( actuator).
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The level of fluid in a tank control.
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Terms and concepts
• Automation - The control of a process by automatic means.
• Closed-loop feedback control system -A system that uses a measurement of the output and A system that uses a measurement of the output and compares it with the desired output.
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Design-The process of conceiving or inventing the forms, parts, and details of a system to achieve a specified purpose.
Feedback signal - A measure of the output of the Feedback signal - A measure of the output of the system used for feedback to control the system.
Multivariable control system - A system with more than one input variable or more than one output variable.
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Negative feedback -The output signal is fed back so that it subtracts from the input signal.
Open-loop control system - A system that utilizes a Open-loop control system - A system that utilizes a device to control the process without using feedback.
Optimization -The adjustment of the parameters to achieve the most favorable or advantageous design.
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Positive feedback -The output signal is fed back so that it adds to the input signal.
Process -The device, plant, or system under control.
Productivity -The ratio of physical output to physical input of an industrial process.
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Robot - Programmable computers integrated with a
manipulator.
Synthesis - The combining of separate elements or Synthesis - The combining of separate elements or
devices to form a coherent whole.
System - An interconnection of elements and devices
for a desired purpose.
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The Control System Design Process
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• Design is the process of conceiving or inventing
the forms, parts, and details of a system to
achieve a specified purpose.
Engineering design
achieve a specified purpose.
• It is the central task of the engineer.
• It is a complex process in which both creativity and analysis play major role.
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• Complexity, trade-off, gaps, and risk are inherent in designing new systems and devices.
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Trade-off
The result of making a judgment about how
to compromise between conflicting criteria.to compromise between conflicting criteria.
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Goals
Twin goals of understanding and controlling are
complementary because effective systems
control requires that the systems be control requires that the systems be
understood and modeled.
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Control engineering
Control engineering is based on the foundations
of feedback theory and linear system analysis,
and it integrates the concepts of network theory
and communication theory.and communication theory.
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Given a process, how to design a feedback
control system?
Three steps:
• Modeling. Obtain mathematical description of the systems.
• Analysis. Analyze the properties of the system.
• Design. Given a plant, design a controller based on performance specifications.
The course spans each of these steps in that sequence.
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The basis for analysis of a system is the
foundation provided by linear system theory,
which assumes a cause-effect relationship for
the components of a system.the components of a system.
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Design 1
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Design 2
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Design 3
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The design of control systems is a specific example of engineering design.
The goal of control engineering design is to obtain the configuration, specifications, and
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obtain the configuration, specifications, and identification of the key parameters of a proposed system to meet an actual need.
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The design process consists of seven main building blocks, which are arrange into three groups:
1.Establishment of goals and variables to be controlled, and definition of specifications
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controlled, and definition of specifications against which to measure performance.
1.System definition and modeling.
1.Control system design and integrated system simulation and analysis
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Design examples
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Rotating disk speed control
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Step 1. Control goal
• Design a system that will held a rotating disk
at a constant speed. Ensure that the actual speed at a constant speed. Ensure that the actual speed
of rotation is within a specified percentage of
desired speed.
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Step 2. Variable to be controlled
• Speed of rotation disc
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Step 3. Control design specification
• Design a system that will ensure that
the actual speed of rotation is within a the actual speed of rotation is within a
specified percentage of desired speed.
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Step 4. Preliminary system configuration
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Step 4 Preliminary system configuration
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With precision components, we could expect
to reduce the error of the feedback system toto reduce the error of the feedback system to
one-hundredth of error of the open-loop system.
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Insulin delivery system
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Step 1. Control goal
• Design a system to regulate the blood sugar
concentration of a diabetic by controlled concentration of a diabetic by controlled
dispensing of insulin.
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The blood glucose and insulin concentrations for a healthy person.
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Step 2. Variable to be controlled
• Blood glucose concentration
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Step 3. Control design specification
• Provide a blood glucose level for the diabetic
that closely approximates the glucose level of
a healthy person.a healthy person.
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Step 4 Preliminary system configurations
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E 4.1 Tracking the sun
H(s) = 1
Gc(s) = 1
H(s) = 1
N(s) = 0
G(s) = 100/(ττττ s + 1)
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P 4.17 A robot gripper control
Km = 30
Rf = 1 ohmRf = 1 ohm
Kf = Ki = 1
J = 0.1,
b = 1
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AP 4.1 Tank level regulator
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Performance Indices
Elevator
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Simplified description of a control system
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Elevator input and output
When the fourth floor button is pressed on the firs t floor, the elevator rises to the fourth floor with a speed and floor level accuracy designed for passenger comfort. 57Intelligent Control
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Push of the fourth-floor button is an input that
represent a desired output, shown as a step function.
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Transient response
Passenger comfort and passenger patience are dependent upon the transient response. If this response is too fast, passenger comfort is sacrificed; if too slow, passenger patience is sacrificed.
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Steady-state error
Passenger safety and convenience would besacrificed if the elevator is not properly level.
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Performance Indices
• A performance index is a quantitative
measure of the performance of a system and
is chosen so that emphasis is given to the is chosen so that emphasis is given to the
important system specifications.
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Response of the system
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ISE - Integral of Square of Error
I = e2(t)T
∫ dtI1 = e (t)0
∫ dt
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The Integral Squared Error
T
∫I1 = e2(t)0
T
∫ dt
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IAE - Integral of the Absolute Magnitude of the
Error
I = e(t)T
∫ dtI2 = e(t)0
∫ dt
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ITAE - Integral of Time Multiplied by Absolute
Error
I = t e(t)T
∫ dtI3 = t e(t)0
∫ dt
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ITSE - Integral of Time Multiplied by Squared
Error
I = te2(t)T
∫ dtI4 = te (t)0
∫ dt
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General form of the performance integral
I = f [e(t),r(t),c((t),t]T
∫ dtI = f [e(t),r(t),c((t),t]0
∫ dt
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Section 5.9
∫=T
dtteISE0
2 )( ∫=T
dtteIAE0
|)(|
∫=T
dttetITAE0
|)(| ∫=T
dttteITSE0
2 )(0 0
∫=T
dtttytrtefI0
)),(),(),((
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Performance criteria
T(s) = 1
s2 + 2ζs +1
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Optimum system
• A control system is optimum when the elected
performance index is minimized.
• The optimum value of the parameters depends
directly upon the definition of optimum, that is,
the performance index.
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Open-loop and closed-loop systems
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Thank you.
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