ME-314 Introduction to Control Engineering is a course taught to Mechanical Engineering senior undergrads. The course is taught by Dr. Bilal Siddiqui at DHA Suffa University. This lecture is introduction to the field.

1. ME-314 Control Engineering
Dr. Bilal A. Siddiqui
Mechanical Engineering
DHA Suffa University
and Brian Douglas

2. About the Course
• This course teaches the basics of system modeling
and control system design
– Basic Concepts
– Mathematical modeling of physical systems
– System response to common inputs
– Stability concepts
– Control systems design
• Root locus design
• Frequency response design
• State space design
and Brian Douglas

3. Books and References
• Katsuhiko Ogata-Modern Control Engineering-Prentice Hall (2001)
• Farid Golnaraghi, Benjamin C. Kuo-Automatic Control Systems-Wiley
(2009)
• Norman S. Nise-Control Systems Engineering, 6th Edition-John Wiley
(2010)
• Richard C. Dorf, Robert H. Bishop - Modern Control Systems-PRENTICE
HALL (2010)
• Fracis Raven – Automatic Control Engineering – McGraw Hill (1961)
• Brian Douglas - The Fundamentals of Control Theory – Online (current)
• Brian Douglas lectures of control systems
https://www.youtube.com/user/ControlLecture
and Brian Douglas

4. Introduction
System – Interconnected parts that form a larger more complex whole. It does
“something”: basically we want to control that something.
Control System – Another system (interconnected components) which is
designed to change the behavior or performance of the system we want to
“control”.
It is confusing to refer to both “the system” and “control system”, so we
generally call “the system” as “plant” or “process”
and Brian Douglas

5. Introduction
Multivariable Control System
Open-Loop Control Systems
utilize a controller or control
actuator to obtain the desired
response.
Closed-Loop Control
Systems utilizes feedback to
compare the actual output to
the desired output response.

6. The Control Problem
• Any system has at least three parts: Inputs,
Outputs, the system itself. The problem is one
of these three is unknown.
– System Identification:
– Simulation Problem
– Control System Design

7. Nomenclature of Control Systems

8. Disturbances
• Sometimes, uncontrolled inputs (called disturbances)
also affect the plant/process.
• There is no way to correct output in open loop
• Control system is ‘robust’ if it can mitigate them

9. Noise
• All sensors are also affected by measurement noise
(remember ME-313 Meas. & Instr).
• Output in this case is not disturbed in the open loop
• Control system is ‘robust’ if it can mitigate noise
sensor noise

10. Plant / Model Mismatch
• We can seldom mathematically model systems accurately
• This means the plant will behave differently from
predictions based on its “model”
• Controller applies inputs based on the plant model
model
model

11. Advantages of Feedback
• There is no need to use feedback (close loop) control and we can use open
loop control, if
– The model is perfectly accurate
– There is no measurement noise
– There is no disturbance
• But none of the above is possible practically.
• Therefore, feedback is the only available mechanism to achieve desired
performance.
• Closed-loop systems have greater accuracy than open-loop systems.
• Less sensitive to noise, disturbances, & changes in environment.
• Transient response and steady-state error can be controlled more
conveniently and with greater flexibility
• Some plants/processes are unstable or not stable to the degree we want
• Control systems can make unstable systems stable

12. Disadvantages
• Sometimes, the plant itself may be stable, but an aggressive
control system can make it unstable.
• Closed-loop systems are more complex and expensive than
open-loop systems.
– Modern digital control systems contain a lot of subsystems:
microcontrollers, analog-digital converters, actuators etc.
– Sensors and actuators can be very expensive
• Therefore,
– Must consider the trade-off between simplicity and low cost of an
open-loop system vs accuracy and higher cost of a closed-loop system
– Control system must be carefully tuned
• Plant degrades over time, so control system needs to be
recalibrated periodically.

13. System Response
• Take the example of a building elevator (Nise)
– 4th
floor button is pressed on the 1st
floor
– Elevator rises with a speed and floor-leveling
accuracy designed for passenger comfort.
– Push of 4th
-floor button is an input that represents
our desired output
Norman S. Nise-Control Systems Engineering, 6th Edition-John Wiley (2010)

14. Transient and Steady State
Response
• Two major measures of performance are
– transient response
– steady-state error
• 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.
• Steady-state error : passenger
safety and convenience would be sacrificed if the elevator did
not properly level.
Norman S. Nise-Control Systems Engineering, 6th Edition-John Wiley (2010)

15. Stability
• Transient and steady response
are useless if the plant is
unstable
• Two types of stability: static
and dynamic
• Static: tendency to come back
to equilibrium point
• Dynamic: each oscillation has
smaller amplitude than
previous
• Control systems must be
designed to be stable.

16. Control System Design Cycle (Dorf)

17. Case Study: Antenna Position Control
• Extraterrestrial life is being searched with help
of huge antennas. We want to make a control
system which automatically points the antenna
in the direction (azimuth) we want. (Nise)

18. Layout of Antenna Azimuth
Control
• Azimuth angle can be
measured by a simple n-turn
potentiometer (how?)
• Another potentiometer can be
used to give the desired angle
(how?)
• Gearbox can be used to
amplify the torque (how?)
• Differential amplifier can be
used as a comparator.
• Motor is used as actuator.
• Where is the controller?

19. Schematic of Antenna Azimuth
Control

20. Block Diagram of Antenna
Azimuth Control

21. Response of Antenna Azimuth
Control System
• Look at affect of controller (power amplifier)
gain

22. Another Look at the Design
Process

23. History (Dorf)
Watt’s Flyball Governor
(18th
century)
Greece (BC) – Float regulator mechanism
Holland (16th
Century)– Temperature regulator
Heron of Greece’s water
clock (3rd
century BC)

24. History
Water-level float regulator

25. History
18th Century James Watt’s centrifugal governor for the speed control of a steam
engine.
1920s Minorsky worked on automatic controllers for steering ships.
1930s Nyquist developed a method for analyzing the stability of controlled systems
1940s Frequency response methods made it possible to design linear closed-loop
control systems
1950s Root-locus method due to Evans was fully developed
1960s State space methods, optimal control, adaptive control and
1980s Learning controls are begun to investigated and developed.
Present and on-going research fields. Recent application of modern control theory
includes such non-engineering systems such as biological, biomedical, economic and
socio-economic systems
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26. (a) Automobile steering
control system.
(b) The driver uses the
difference between the
actual and the desired
direction of travel
to generate a controlled
adjustment of the
steering wheel.
(c) Typical direction-
of-travel response.
Examples of Modern Control Systems

27. Examples of Modern Control Systems

28. Examples of Modern Control Systems

29. Examples of Modern Control Systems

30. Examples of Modern Control Systems

31. Examples of Modern Control Systems

32. The Future of Control Systems

33. The Future of Control Systems

34. Design Example

35. Design Example

36. Design Example

37. Design Example

40. Design Example

41. Design Example

42. Sequential Design Example

44. Sequential Design Example