1. Introduction and Terminologies
Control Systems
Introduction and Terminologies
Abdul Qadir Ansari, Ph.D.
Course website:

2. Text Books Control Systems Engineering, (6th Edition)
By: Norman S. Nise.
Modern Control Systems, (12th Edition)
By: Richard C. Dorf and Robert H. Bishop.
Schaum’s Outline of Feedback and Control Systems, (2nd Edition)
By: Joseph J. Distefano, Allen R. Stubberud, and Ivan J. Willaims.

3. Reference Books Modern Control Engineering, (5th Edition)
By: Katsuhiko Ogata.
2. Basic Feedback Controls in Biomedicine.
By: Charles S. Lessard.
3. Feedback Control of Dynamic Systems, (6th Edition)
By: Gene Franklin, J.D. Powell, and Abbas Emami-Naeini
Feedback Systems: An Introduction for Scientists and Engineers, by Karl J.
Åström and Richard M. Murray.
Physiological Control Systems: Analysis, Simulation and Estimation, by: Michael C. K. Khoo.

4. Marks Distribution Theory Total Marks = 100 Sessional Marks = 20
Attendance = 10 marks
Class Tests/Quizzes = 10 marks
Mid-Semester Examination : 20 Marks
Final Examination : 60 Marks

5. Learning behaviors OBE based Learning Evaluation
Student Centric Learning: You have also to be source of information.
Presentations in class (voluntarily)
Semester Project
Working in groups
Individual Learning
Evaluation
2-3 Class Quiz (can be surprise)
Home assignments.
Mid Semester Examination
Final Examination

6. Expectations from Students
Active participation.
Help each other in reviewing notes, and solving complex problems.
Promptly report/share problems/issues, including typos on slides, or misspoken words from instructor.

7. Course Outline Classical Control Modern Control System Modelling
Transfer Function
Block Diagrams
Signal Flow Graphs
System Analysis
Time Domain Analysis (Test Signals)
Frequency Domain Analysis
Bode Plots
Nyquist Plots
Nichol’s Chart
Modern Control
State Space Modelling
Eigen value Analysis
Observability and Controllability
Solution of State Equations (state Transition Matrix)
State Space to Transfer Function
Transfer Function to State Space

8. Course Outline Open loop and close loop control systems.
Block diagrams models and reduction techniques.
Signal flow graphs.
Mathematical modeling of electrical and mechanical systems.
Transient and steady state response of linear control systems.
State-space representation and analysis.
Eigen values and Eigen vectors.
Closed-loop system stability analysis using the Routh-Hurwitz criteria.
Stability, performance analysis, and control system design using the Root Locus techniques.
Bode diagrams.
Nyquist stability criterion.
Gain and Phase margins.

9. Prerequisites For Classical Control Theory Differential Equations
Laplace Transform
Basic Physics
For Modern Control theory
Linear Algebra
Matrices

10. Course Objectives
On completion of this module, students will be able to do the following ;
Define the basic terminologies used in controls systems.
Explain advantages and drawbacks of open-loop and closed loop control systems.
Obtain models of linear control systems in ordinary differential equation, transfer function, state space, or block diagram form.
Obtain overall transfer function of a linear control system using either block diagram algebra, or signal flow graphs.
Simplify complex control system models using block diagram and signal flow graphs reduction techniques.
Explain the relationship between system output response and transfer function characteristics or pole/zero locations.
Determine the stability of a closed-loop control systems using the Routh-Hurwitz criteria.
Analyze the closed loop stability and performance of control systems based on open-loop transfer functions using the Root Locus technique and Nyquist stability criterion techniques.
Compute and analyze the frequency response of control systems using Bode diagrams.

11. What is Control System?
A system Controlling the operation of another system.
A system that can regulate itself and another system.
A control System is a device, or set of devices to manage, command, direct or regulate the behaviour of other device(s) or system(s).

12. Definitions
System – An interconnection of elements and devices for a desired purpose.
Control System – An interconnection of components forming a system configuration that will provide a desired response.
Process – The device, plant, or system under control. The input and output relationship represents the cause-and-effect relationship of the process.
Process
Output
Input

13. Definitions
Controlled Variable– It is the quantity or condition that is measured and Controlled. Normally controlled variable is the output of the control system.
Manipulated Variable– It is the quantity of the condition that is varied by the controller so as to affect the value of controlled variable.
Control – Control means measuring the value of controlled variable of the system and applying the manipulated variable to the system to correct or limit the deviation of the measured value from a desired value.

14. Definitions
Controller
Output Or
Controlled Variable
Input or
Set point
reference
Process
Manipulated Variable
Disturbances– A disturbance is a signal that tends to adversely affect the value of the system. It is an unwanted input of the system.
If a disturbance is generated within the system, it is called internal disturbance. While an external disturbance is generated outside the system.

15. Types of Control System
Natural Control System
Universe
Human Body
Manmade Control System
Vehicles
Aeroplanes, …

16. Types of Control System
Manual Control Systems
Room Temperature regulation Via Electric Fan
Water Level Control
Automatic Control System
Room Temperature regulation Via A.C
Human Body Temperature Control
The hypothalamus works with other parts of the body's temperature-regulating system.
Blood Glucose Control in Body

17. Types of Control System
Open-Loop Control Systems utilize a controller or control actuator to obtain the desired response.
Output has no effect on the control action. No feedback – no correction of disturbances
In other words output is neither measured nor fed back.
Controller
Output
Input
Process
Examples:- Washing Machine, Toaster, Electric Fan

21. Types of Control System
Since in open loop control systems reference input is not compared with measured output, for each reference input there is fixed operating condition.
Therefore, the accuracy of the system depends on calibration.
The performance of open loop system is severely affected by the presence of disturbances, or variation in operating/ environmental conditions.

22. Types of Control System
Closed-Loop Control Systems utilizes feedback to compare the actual output to the desired output response.
Controller
Output
Input
Process
Comparator
Measurement
Examples:- Refrigerator, Iron

23. Types of Control System
Multivariable Control System
Controller
Outputs
Temp
Process
Comparator
Measurements
Humidity
Pressure

24. Types of Control System
Feedback Control System
A system that maintains a prescribed relationship between the output and some reference input by comparing them and using the difference (i.e. error) as a means of control is called a feedback control system.
Feedback can be positive or negative.
Controller
Output
Input
Process
Feedback - +
error

25. Types of Control System
Servo System
A Servo System (or servomechanism) is a feedback control system
Servo means slave/serving and mechanism means command; thus servo mechanism systems are slave to command systems.
Usually, the output is some mechanical position, velocity or acceleration.
Antenna Positioning System

26. Types of Control System
Linear vs. Nonlinear Control System
A Control System in which output varies linearly with the input is called a linear control system.
y(t)
u(t)
Process

27. Types of Control System
Linear vs. Nonlinear Control System
When the input and output has nonlinear relationship the system is said to be nonlinear.
Linear control System Does not exist in practice.
Linear control systems are idealized models fabricated by the analyst purely for the simplicity of analysis and design.
When the magnitude of signals in a control system are limited to range in which system components exhibit linear characteristics the system is essentially linear.

28. Temperature
Valve Position °C
% Open 0%
100%
500°C
25%

29. Types of Control System
Time invariant vs. Time variant
When the characteristics of the system do not depend upon time itself then the system is said to time invariant control system.
Time varying control system is a system in which one or more parameters vary with time.

30. Types of Control System
Lumped parameter vs. Distributed Parameter
Control system that can be described by ordinary differential equations are lumped-parameter control systems (dependent variables of interest are a function of time alone)
Whereas the distributed parameter control systems are described by partial differential equations (dependent variables are functions of time and one or more spatial variables.

31. Types of Control System
Continuous Data vs. Discrete Data System
In continuous data control system all system variables are function of a continuous time t.
A discrete time control system involves one or more variables that are known only at discrete time intervals.
x(t) t
X[n] n

32. Types of Control System
Deterministic vs. Stochastic Control System
A control System is deterministic if the response to input is predictable and repeatable.
If not, the control system is a stochastic control system.
y(t) t
x(t)
z(t) t

33. Adaptive Control System
Types of Control System
Adaptive Control System
The dynamic characteristics of most control systems are not constant for several reasons.
The effect of small changes on the system parameters is mitigated in a feedback control system.
An adaptive control system is required when the changes in the system parameters are significant.

34. Learning Control System
Types of Control System
Learning Control System
A control system that can learn from the environment it is operating is called a learning control system.

35. Types of Control System
Control Systems
Natural
Man-made
Manual
Automatic
Open-loop
Closed-loop
Non-linear
linear
Time variant
Time invariant

36. Manipulated Variable- water inflow
Controller
Command Signal- preset height H̅
Controlled Variable- water level in the tank
Objective is to control the height of water level in tank thus water level is controlled variable of this system
Pre-set height of water is command signal
Water out flows are disturbances
Manipulated variable is water in flow
Controller is floating ball and lever constitute controller
Disturbance

37. Floating ball +linkage
Water source + valve
Water Tank
Preset Height H̅
Controlled variable
-Actual Height H
Manipulated variable
Control variable
Disturbance Signal

38. - Manipulated variable Control variable Controlled variable
-Actual Height H
Preset Height H̅
Water source + valve (Actuator)
Water Tank (Plant)
Floating ball +linkage (Controller) + -
Disturbance Signal
Set Point Regulator System

39. Examples of Modern Control Systems
(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.

44. Control Logic i.e. in Brian of Driver
Car Driving Control System
Wind , Road Traffic
Direction of Highway
Heading
Control Logic i.e. in Brian of Driver
Actuator i.e. Hands
Vehicle
Speed Limits
Actuator i.e. Feet
Speed
Error Detector i.e. Eyes of Driver
There are two output variables. MIMO system, Multivariable
Regulator Control System, Tracking System, Command Following System

46. BASIC Feedback Structurew m A D GA GP + y yr - b H
A: Reference Input Elements Block
D : Control Logic Block
GA : Actuator Block
GP : Plant
H:Feedback Block
m: Manipulated Signal
w: Disturbance Variable
y: Controlled Variable
yr: Command Signal
r: Reference Signal
b: Feedback Signal
e︢ : Actuating Error Signal
u: Control Signal

47. The Design Process

48. 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 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

49. Examples of Control Systems
Water-level float regulator

50. Examples of Control Systems

51. Examples of Control Systems

52. Examples of Control Systems

53. Examples of Modern Control Systems
Aerospace engineers develop control systems for a vehicle's orientation (altitude) about its center of mass. The control systems include actuators, which exert forces in various directions, and generate rotational forces or moments about the aerodynamic center of the aircraft, and thus rotate the aircraft in pitch, roll, or yaw.

54. Examples of Control Systems

55. Examples of Control Systems

56. Examples of Control Systems

57. Examples of Modern Control Systems

58. Examples of Modern Control Systems