Control Systems Dr. Mohammed Gulam Ahamad Lecture 1: Introduction.

Dr. Mohammed Gulam Ahamad

1. Control Systems Engineering, (6th Edition) By: Norman S. Nise.

2. Modern Control Systems, (12th Edition) By: Richard C. Dorf and Robert H. Bishop.

3. Schaum’s Outline of Feedback and Control Systems, (2nd

Edition) By: Joseph J. Distefano, Allen R. Stubberud, and Ivan J.

Willaims.

1. 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-Naeini4. Feedback Systems: An Introduction for Scientists and Engineers,

by Karl J. Åström and Richard M. Murray.5. Physiological Control Systems: Analysis, Simulation and

Estimation, by: Michael C. K. Khoo.

Theory

Total Marks = 100

Sessional Marks = 40• Home work = 10 marks

• Class Tests/Quizzes = 10 marks

Final Exam Marks = 40

• Full attendance is expected, except with prior-notified excuses in written.

• On-time arrival.• Active participation.

• Ask questions.• Answer questions from instructor or students.

• Help each other in reviewing notes, and solving complex problems.

• Promptly report/share problems/issues, including typos on slides, or misspoken words from instructor.

• Cheating is a very serious offense. It will be dealt with in the most severe manner allowable under University regulations. If caught cheating, you can expect a failing grade and initiation of a cheating case in the University system.

• 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.• Polar plots.• Nyquist stability criterion.• Gain and Phase margins.• Nichol’s chart.

PrerequisitesFor Classical Control Theory

Differential EquationsLaplace TransformBasic PhysicsOrdinary and Semi-logarithimic graph papers

For Modern Control theory above &Linear AlgebraMatrices

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.•Compute and analyze the frequency response of control systems using Bode diagrams.•Analyze the closed loop stability and performance of control systems based on open-loop transfer functions using the Polar plots and Nyquist stability criterion techniques.

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).

DefinitionsSystem – 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 OutputInput

DefinitionsControlled 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.

Definitions

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.

Controller

OutputOrControlled Variable

InputorSet pointorreference

Process

Manipulated Variable

Types of Control System

Natural Control SystemUniverseHuman Body

Manmade Control SystemVehiclesAeroplanes


Manual Control SystemsRoom Temperature regulation Via Electric FanWater Level Control

Automatic Control SystemRoom Temperature regulation Via A.CHuman Body Temperature Control

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

OutputInput Process

Examples:- Washing Machine, Toaster, Electric Fan


• 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.


Closed-Loop Control Systems utilizes feedback to compare the actual output to the desired output response.

Examples:- Refrigerator, Iron

Controller

OutputInputProcessComparator

Measurement


Multivariable Control System

Controller

OutputsTempProcessComparator

Measurements

HumidityPressure


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 OutputInput Process

Feedback

-+ error


Servo System

• A Servo System (or servomechanism) is a feedback control system in which the output is some mechanical position, velocity or acceleration.

Antenna Positioning System Modular Servo System (MS150)


Linear vs. Nonlinear Control System• A Control System in which output varies linearly with the input

is called a linear control system.

53 )()( tuty

y(t)u(t) Process

12 )()( tuty

0 2 4 6 8 105

10

15

20

25

30

35y=3*u(t)+5

u(t)

y(t)

0 2 4 6 8 10-20

-15

-10

-5

0

5

y(t)

u(t)

y=-2*u(t)+1


Linear vs. Nonlinear Control System

• When the input and output has nonlinear relationship the system is said to be nonlinear.

0 0.02 0.04 0.06 0.080

0.1

0.2

0.3

0.4

Adhesion Characteristics of Road

Creep

Adh

esio

n C

oeff

icie

nt



• 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.

0 0.02 0.04 0.06 0.080

0.1

0.2

0.3

0.4

Adhesion Characteristics of Road

Creep

Adh

esio

n C

oeff

icie

nt



• Temperature control of petroleum product in a distillation column.

Temperature

Valve Position

°C

% Open0% 100%

500°C

25%


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.

12 )()( tuty

ttuty 32 )()(


Lumped parameter vs. Distributed Parameter

• Control system that can be described by ordinary differential equations are lumped-parameter control systems.

• Whereas the distributed parameter control systems are described by partial differential equations.

kxdt

dxC

dt

xdM

2

2

2

2

21dz

xg

dz

xf

dy

xf


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


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)

t

z(t)

t


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 attenuated in a feedback control system.

An adaptive control system is required when the changes in the system parameters are significant.


Learning Control System

A control system that can learn from the environment it is operating is called a learning control system.


Control Systems

Natural Man-made

Manual Automatic

Open-loop Closed-loop

Non-linear linear

Time variantTime invariant

Non-linear linear

Time variantTime invariant

LTI C

ontrol S

ystems

LTI C

ontrol S

ystems(Linear tim

e invariant control systems)


Examples of Control SystemsWater-level float regulator

Examples of Control Systems




History18th 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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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.




Examples of Modern Control SystemsOpen-loop & Closed-loop Models of Blood Glucose Control System

Examples of Control SystemsA Model of Heart Rate Control System










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Control Systems Dr. Mohammed Gulam Ahamad Lecture 1: Introduction.

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