# Lecture 1 - Rowan University

Electronics - Devices

Nov 15, 2013 (4 years and 8 months ago)

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Mathematical Models

SYSTEMS AND CONTROL I
ECE 09.321

09/04/07

Lecture 1

ROWAN UNIVERSITY

College of Engineering

Prof. John Colton

DEPARTMENT OF ELECTRICAL & COMPUTER ENGINEERING

Fall 2007
-

Semester One

2

Welcome to Systems and Control I

Course Learning Objectives

Develop mathematical tools for analysis and design of modern
feedback control systems

Apply these tools to many types of closed loop feedback control
systems, evaluating the beneficial effects that feedback provides

state and transient performance of these systems

Evaluate the beneficial implications of feedback on system
performance, including sensitivity to parameter variation,
tracking, and disturbance rejection

Develop the design criteria and tools for optimizing closed loop
system performance and ensuring system stability

Develop tools for frequency response analysis and design of
feedback control systems.

Use MATLAB for assignments and lab projects to supplement
direct calculations

3

Systems and Control I Topics

Historical Perspective

Mathematical models and tools: differential equations of
physical systems, Laplace transforms, convolution integral
and impulse response, transfer functions, block diagram
manipulation, and signal flow graphs

Closed loop system performance: sensitivity reduction,
disturbance rejection, transient performance and steady
-
state error, use of s
-
plane for analysis and design, cost of
feedback, design criteria and tools, frequency response
methods

Stability of feedback control systems: stability concepts,
Routh
-
Hurwitz Stability Criterion, root locus design methods,
Bode diagrams, phase and gain margin, Nyquist stability
criterion

Design of feedback control systems

4

Lectures M/W 9:50 AM
-
10:40 AM Rowan 102

Laboratories T 3:15 PM
-
6:00 PM Rowan 239

Course Website:
users.rowan.edu/~colton/fall07/systems/index.html

Required Text:
Modern Control Systems
, Dorf and Bishop,

11
th

Edition 2007, ISBN: 0132270285

Chapters 1/2)

Problem Sets: see website (issued each Wednesday, due 9:50 AM

the next Monday

show all work for any credit,
no

credit for

late problem sets)

Labs: see website (labs conducted Tuesday, reports due 12:15 PM
the next Tuesday

lab report format,
no

credit for late lab reports

Course announcements: made regularly in class

Email: check regularly (daily)

Course Potpourri

5

Learning Evaluation

6 Quizzes 30%

Final Exam 40%

Assignments and labs 30%

Problem Sets and Class participation (15%)

Lab Reports, participation, homework (15%)

6

Introduction to Control Systems

Historical perspective

Introduction to Feedback Control Systems

Closed loop system examples

7

Historical Perspective

13.7B BC

Big Bang

13.4B

Stars and galaxies form

5B

Birth of our sun

3.8B

Early life begins

700M

First animals

200M

Mammals evolve

65M

Dinosaurs extinct

600K

Homo sapiens evolve

8

Feedback Control Systems emerge rather recently

1600

Drebbel Temperature regulator

1781

Pressure regulator for steam boilers

1765

Polzunov water level float regulator

9

Closed loop example: Polzunov’s Water
level float regulator

10

Feedback Control Systems emerge rather recently

1600

Drebbel Temperature regulator

1681

Pressure regulator for steam boilers

1765

Polzunov water level float regulator

1769 James Watt’s Steam Engine and Governor

11

Closed loop example: James Watt’s flyball
governor

12

Feedback Control Systems emerge rather recently

1600

Drebbel Temperature regulator

1681

Pressure regulator for steam boilers

1765

Polzunov water level float regulator

1769 James Watt’s Steam Engine and Governor

1868 James Clerk Maxwell formulates a mathematical model for

governor control of a steam engine

1927

Harold Black discovers and patents the feedback amplifier

1927 Hendrik Bode analyzes feedback amplifiers

1932

Nyquist develops methods for analyzing feedback amplifier

stability

13

Open loop and closed loop control systems

Open Loop System

14

Open loop and closed loop control
system models

Open Loop System

Closed Loop System

15

Example: Feedback Control Amplifiers

16

Feedback Control Systems emerge rather recently

1600

Drebbel Temperature regulator

1681

Pressure regulator for steam boilers

1765

Polzunov water level float regulator

1769 James Watt’s Steam Engine and Governor

1868 James Clerk Maxwell formulates a mathematical model for

governor control of a steam engine

1927

Harold Black discovers and patents the feedback amplifier

1927 Hendrik Bode analyzes feedback amplifiers

1932

Nyquist develops methods for analyzing feedback amplifier

stability

1940s Norbert Wiener leads gun positioning effort; feedback control

engineering becomes an engineering discipline

1950s Increased use of Laplace transform, s
-
plane, root locus

1960s Sputnik, highly accurate control systems for space vehicles,

robotics, and missiles

1980s Routine use of digital computers as control elements

1990s Feedback control in automobiles, automation, planetary

exploration

17

Example: Feedback in everyday life

18

Quotable Quotes

“Take warning! Alternating currents are
dangerous! They are fit only for powering the
electric chair. The only similarity between an AC
and a DC lighting system is that they both start
from the same coal pile.”

Thomas Edison

Pamphlet of 1887

“Heavier than air flying machines are impossible”

Lord Kelvin

Royal Society 1895

“There is no likelihood man can ever tap the
power of the atom”

Robert Milliken Nobel Laureate Physics 1923

19

Multivariable Control System Model

20

Multivariable Control System

21

Robotics

A robot is a programmable computer integrated with a machine

22

Example: Disk Drive

23

Example: Automatic Parking Control

24

Feedback Control: Benefits and cost

Benefits:

Cost:

25

Feedback Control: Benefits and cost

Benefits:

Cost:

Reduction of sensitivity to process parameters

Disturbance rejection

More precise control of process at lower cost

Performance and robustness not otherwise achievable

26

Feedback Control: Benefits and cost

Benefits:

Cost:

More mathematical sophistication

Large loop gain to provide substantial closed loop gain

Stabilizing closed loop system

-
state response

Reduction of sensitivity to process parameters

Disturbance rejection

More precise control of process at lower cost

Performance and robustness not otherwise achievable

27

Homework for next week

See website for Problem Set 1

Due Monday 09/10
8 AM

Show
all work

for any credit

See website for Lab Assignment 1