R.C. Dorf and R.H. Bishop, Modern Control Systems,. 11th Edition, Prentice ...
and Control Systems, Schaum's Outline Series, McGraw-Hill,. Inc., 1990.
Chapters ...
ECE 4951 - Spring 2010
Introduction to Intelligent Control Part 1 Prof. Marian S. Stachowicz Laboratory for Intelligent Systems ECE Department, University of Minnesota Duluth
January 19 - 21, 2010
Instructors • • • • • • • • • • • • • • • • • • • • •
INSTRUCTORS:
TIME/LOCATION:
Prof. Marian S. Stachowicz, MWAH 273, phone: 218- 726-6531,
[email protected] http://www.d.umn.edu/ece/lis 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, 8 hours per week, MWAH 293 (next 10 weeks)
OFFICE HOURS:
CONSULTANT:
OFFICE HOURS:
14:00 - 15:30, T, Th, MWAH 273
Prof. Christopher Carroll MWAH 252, phone: 218 - 726-7530,
[email protected] 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, • 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 Intelligent Control
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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 • 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, Feeedback and Control Systems, Schaum's Outline Series, McGraw-Hill, Inc., 1990 Chapters 1, 2
Control Systems
Control • The word control is usually taken to mean : - regulate, - 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.
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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 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.
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Manual control system
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). Intelligent Control
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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 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 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. Intelligent Control
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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 device to control the process without using feedback. Optimization -The adjustment of the parameters to achieve the most favorable or advantageous design. Intelligent Control
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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 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
Engineering design • Design is the process of conceiving or inventing the forms, parts, and details of a system to 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.
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Goals Twin goals of understanding and controlling are complementary because effective systems 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.
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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. Intelligent Control
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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.
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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 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 against which to measure performance. 1.System definition and modeling. 1.Control system design and integrated system simulation and analysis Intelligent Control
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Design examples
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 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 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 to one-hundredth of error of the open-loop system.
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Insulin delivery system
Step 1. Control goal
• Design a system to regulate the blood sugar concentration of a diabetic by controlled dispensing of insulin.
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The blood glucose and insulin concentrations for a healthy person. Intelligent Control
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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.
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Step 4 Preliminary system configurations
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E 4.1 Tracking the sun
Gc(s) = 1 H(s) = 1
N(s) = 0 G(s) = 100/(ττ s + 1)
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P 4.17 A robot gripper control
Km = 30 Rf = 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 first floor, the elevator rises to the fourth floor with a speed and floor level accuracy designed for Intelligent Control passenger comfort.
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Push of the fourth-floor button is an input that represent a desired output, shown as a step function. Intelligent Control
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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. Intelligent Control
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Steady-state error
Passenger safety and convenience would be sacrificed if the elevator is not properly level. Intelligent Control
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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 important system specifications.
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Response of the system
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ISE - Integral of Square of Error
I1 =
T
∫ e (t)dt 2
0
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The Integral Squared Error
I1 =
T
∫ e (t)dt 2
0
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IAE - Integral of the Absolute Magnitude of the Error
I2 =
T
∫ e(t) dt 0
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ITAE - Integral of Time Multiplied by Absolute Error
I3 =
T
∫ t e(t) dt 0
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ITSE - Integral of Time Multiplied by Squared Error
I4 =
T
∫ te (t)dt 2
0
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General form of the performance integral
I=
T
∫
f [e(t),r(t),c((t),t]dt
0
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Section 5.9 T
ISE = ∫ e (t )dt 2
0
T
IAE = ∫ | e(t ) | dt 0
T
T
ITAE = ∫ t | e(t ) | dt
ITSE = ∫ te 2 (t )dt 0
0
T
I = ∫ f (e(t ), r (t ), y(t ), t )dt 0
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Performance criteria 1 T(s) = 2 s + 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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