EES310803 EES310803 Fundamental of Control Systems Fundamental of Control Systems
Electrical Engineering Department University of Indonesia
Lecturer:
Dr. Wahidin Wahab M.Sc.
Aries Subiantoro, ST. MSc.
Introduction to Control Systems Introduction to Control Systems
Introduction to the Topic
To give an idea of the many applications of the subject
To give an insight into its history
to highlight its advantages
to demonstrates the depth and the breath of the subject
To illustrate its usefulness as a subject worth studying
Define some Simple Terms
S S ome Control System Applications ome Control System Applications
Space shuttle
Automatic
machine tools
Automatic parts delivery in a
factory
(Use ACDsee
to look at the pictures)
Control System in Nature Control System in Nature
Pancreas – regulates blood sugar
Adrenalin – automatically generated to increase heart-rate and oxygen intake in times of flight
Eyes – able to follow a moving object
Hand – able to pick up an object and
place it at a predetermined location
Some ‘Artificial’ Applications of Some ‘Artificial’ Applications of
Control Control
Modern Economics
A Model of Student Performance
Input is available study time
Output is performance/exam mark
Such a model could be used to predict time required to improve the grade
With such a scheme you could decide whether it is worth spending more effort to pass the Control
System Exam!
Control Systems Provide Power Control Systems Provide Power
Amplification Amplification
Radio telescopes can be accurately pointed at far reaches of the universe
Lift can stop at the right desired floor
Control systems allow us to move large pieces of equipment with precision
We could not perform these tasks ourselves. Motors provide the power and the control systems regulate the position and speed
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
Figure 1.8
The search for
extraterrestrial life is being carried out with
radio antennas like the one pictured here. A radio
antenna is an
example of a system with position controls.
© Peter Menzel.
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
a. system concept;
b. detailed layout;
c. schematic;
d. functional block diagram
Figure 1.9
Antenna azimuth position control system:
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
Figure 1.10
Response of a position control system showing effect of high and low controller gain on the output
response
Response of an Un-stable System.
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
a. Early elevators were controlled by hand
ropes or an elevator
operator. Here, a rope is cut to demonstrate the safety brake, an
innovation in early elevators;
b. Modern Duo-lift elevators make their way up the Grande
Arche in Paris, driven by one motor, with each car counterbalancing the other. Today, elevators are fully
automatic, using control systems to regulate
position and velocity.
Figure 1.2 Elevators
Photos courtesy of United Technologies Otis Elevator.
Control finds Applications in Control finds Applications in
Transportation Transportation
Engine regulation, active suspension systems and anti-lock braking systems in automobiles
Steering of missiles, planes, aircraft and ships at sea
For example, modern ships use a combination of
electrical, mechanical, and hydraulic components to develop rudder commands in response to desired heading commands. The rudder commands, in turn, produce a rudder angle, which steers the ship
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
Figure P1.2
Aircraft attitude definition
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
Figure P1.9
High-speed rail system showing pantograph and catenary
© 1997, ASME.
Control finds Applications in Control finds Applications in
Process Industries Process Industries
In the process industries control is used to regulate level, pressure, and temperature of chemical refinery vessels
In a steel rolling mill, the position of the rolls is
controlled according to the measured thickness
of the steel going off the finishing line
Control Applications in Process Control Applications in Process
Industries Industries
Hydrostatic Radar
Tuning Fork
Float
Capacitance Dipstick
Sight glass
Gage Glass
Weight Differential
Pressure
Ultrasonic Gap Displacer Nuclear
Ultrasonic Bubbler
Control Systems in the Home Control Systems in the Home
CD Player the position of the laser spot in relation to the microscopic pits in a Compact Disc is controllers
Video Recorders the tracking of the record and play- back heads is controlled by controlling the velocity of the tape
Central heating systems use thermostats to measure and control the temperature in the room
Washing machines use sequencing controls to provide a variety of wash cycles and temperature controls to avoid damage to delicate fabrics
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
(a)
(b)
(c)
Figure 1.4
a. Video laser disc player;
b. objective lens reading pits on a laser disc;
c. optical path for playback showing tracking mirror rotated by a control system to keep the laser beam positioned on the pits.
(c) Pioneer Electronics, Inc.
Control Systems Engineering, Fourth Edition by Norman S. Nise Copyright © 2004 by John Wiley & Sons. All rights reserved.
Figure 1.7
Computer hard disk drive, showing disks and read/write head
Courtesy of Quantum Corp.
The Hidden Technology The Hidden Technology
z “Automatic control systems are today pervasive. They appear practically everywhere in our homes, in industry, in
communication systems, in all types of vehicles and in
scientific instruments. Control systems are increasingly
becoming mission critical, a failure of the control systems will thus lead to a system failure.
In spite of this automatic control is not very much talked about. It is therefore appropriate to label the technology the hidden
technology”
K.J. Astrom
Historical Development of Control Historical Development of Control
Systems Systems
Ancient Greece (ca. 3000 BC): water clocks, automatic oil lamps; special effects in temples
17th Century: Cornelis Drebbel – temperature control for an egg incubator
18th Century: James Watt – Flyball governor for steam engine
Late 19th Century to mid 20th Century:
Development of classical control theory
1960’s: present “modern control theory”
Heroes and Milestones in the Heroes and Milestones in the
Development of Control Systems Development of Control Systems
Late 19th century: Fathers of Stability Theory –
J.C. Maxwell, E.J. Routh and A.M. Lyapunov
Late 1920’s – mid 1930’s: Bell Telephone Labs USA.
Discovery of negative feedback (Black),
Frequency response analysis (H.W. Bode),
Stability theory (H. Nyquist)
1948 invention of the Root Locus method (W.R.
Evans)
1960’s development of state-space methods (Kalman and others)
A Bit of History A Bit of History
Egg Incubator (1620) – Temperature Control
A Bit of History A Bit of History
Fly-Ball Governor (1788)
Control Engineering is Challenging Control Engineering is Challenging
cuts across numerous engineering disciplines
covers numerous functions within a discipline
It is a multi-disciplinary subject
Control Engineering is Challenging Control Engineering is Challenging
from conception through to;
system requirements;
subsystem functions;
interconnection of functions;
interfaces between functions;
hardware and software design;
right up to test plans and procedures;
It covers all Aspects of a Project from high
to low level
The Space Shuttle The Space Shuttle
Flight control
Orbit control
Life support
The space shuttle would be impossible to fly without control systems.
All the shuttle’s many control systems are controlled by on-board computers on a time-shared basis
The main control systems in the shuttle are:
Flight Control in the Shuttle Flight Control in the Shuttle
Navigation functions take in data to estimate the shuttle’s position and velocity.
The position and velocity data is used to steer the shuttle:
In space by use of pulsed jets of gas;
In the Earth’s atmosphere by adjusting the geometry of the shuttle’s air surfaces
Subsystems and Disciplines Subsystems and Disciplines
Represented in the Shuttle Represented in the Shuttle
Numerous subsystems
flight elevon controls to counteract wind disturbances
life support systems; power systems; heating.
Many disciplines: orbital mechanics;
propulsion; aerodynamics; electrical engineering;
mechanical engineering; hydraulics; temperature and pressure control, etc.
What will I get out of this course?
What will I get out of this course?
most engineering courses are taught bottom up
they start with components
develop circuits
assemble circuits into products
Control is a top-down engineering subject.
Such subjects are rare in engineering:
The reason for this is that top-down courses are difficult to teach because of the high-level of
mathematics needed for a system approach.
Top down design in Control Systems Top down design in Control Systems
design high-level system requirements
choose functions and hardware to implement system to meet requirements
Control works from ‘the big picture’. It unifies many
other elements. This is part of difficulty of the subject, it is also the challenge.
Recognition of the unification, that is being able to use lessons learned in other courses, will help you to
master this course material
Taking Stock Taking Stock
biologists,
chemical, mechanical and electrical engineers,
mathematical and
physicists
It is Broad and Diverse
Control Engineers typically need to work closely with
They get involved with sensors and actuator technology, electronics, pneumatics and hydraulics and computers
A control system consists of A control system consists of
subsystem and processes subsystem and processes
A central heating boiler is a process that produces heat as a result of a flow of fuel.
This process is assembled from subsystems called fuel valves.
Fuel valve actuators regulate the temperature of a room by controlling the flow of fuel into the
boiler.
Other subsystems, such a thermostats, act as sensors, to measure the room temperature
Control System
Input;
Stimulus
Output;
Response
Desired Response
Actual
Response
Input
Input - - Output Process Output Process
Analysis and Design Objectives Analysis and Design Objectives
Transient response
Steady state response
Stability
Low Cost
Robustness
Advantages of Control Systems Advantages of Control Systems
Power amplifications
Dangerous applications
Compensations from human deficiences
Convenience by change of the form of input
Compensation of disturbances
Open Open - - Loop Control System Loop Control System
Controller Process
Disturbance 1 Disturbance 2
Input or
Reference
Output or Controlled Variable
++
++
Process is a boiler,
input is fuel, output is heat
Controller is electronics, valves, etc.
which control fuel flow into furnace
Input is thermostat position
Closed
Closed - - Loop Control System Loop Control System
Controller
Disturbance 1 Disturbance 2
++
++
Process
Sensor input
transducer + -
Input Output
Description of an Closed
Description of an Closed - - Loop Loop Temperature Control System
Temperature Control System
Input temperature dial position converted into a voltage by a potentiometer.
Output temperature converted to a voltage by a thermistor
Differencing circuit subtracts output from input – result is actuating signal – controller drives the plant only if there is a difference
Closed-loop systems are less sensitive to disturbances
Magic of Feedback Magic of Feedback
Key components
Sensor: measuring the speed of the engine (ω)
Actuator: valve determining the steam input to the engine
Calculator: relationship between sensor and actuator (ω vs α)
Steam- engine Load disturbances
Valve Desired
speed
Governor
Feedback has the potential to:
Reduce
the effect of (load) disturbance
Change the dynamic
response
! Destabilize the system
Magic of Feedback Magic of Feedback
Sensor (Governor)
Feedback consists of a sensing, actuation AND calculation element
Plant Actuator
(valve)
Calculate (Governor)
Simulation Results Simulation Results
) 5 )(
2 )(
1 (
) 1
( = + + +
s s
s s Gp
K s
Gc ( ) =
Controller Process
Computer
Computer - - Controlled Systems Controlled Systems
Many loops can be controlled by time sharing
Adjustment of controller parameters are in software rather than hardware
Supervisory functions such as scheduling, data logging, error and fault monitoring, can also be done
The controller or compensator is a computer
Summary Summary
a definition of a control system
a description of typical inputs and outputs
an introduction to the terms steady-state error and transient performance
some advantages of control systems
an illustration of the difference between open-loop and closed loop control
an introduction to computer controlled systems
In this lecture we have introduced the Topic of Control and given
Course Outline Course Outline
Introduction
Modeling
Transient Response
Routh-Hurwitz Criterion
Nyquist Diagram
Root Locus
Bode Diagram
Controller Design in Frequency Domain
Controller Design in Time Domain
State Space
Controller Design Using State Space
Observer
References References
N.S. Nise, “Control Systems Engineering 4th ed.”, Wiley, 2004
K. Ogata, “Modern Control Engineering 4th ed.”,
Prentice-Hall.
Grading Grading
Home Work : 10% 20%
Mid Exam : 40% 30%
Final Exam : 50% 50%
Pressure Process Rig
Pressure Process Rig
Process Interface (Feedback 38-200)
Pressure Process Rig (Feedback 38- 714)
I/V Converter V/I Converter
0,4-2 V 0,4-2 V
4-20 mA 4-20 mA
4-20 mA
DAC dan ADC (Sampling time 0,15 seconds)
4-20 mA
Computer
H/W H/W dan dan S/W Requirement S/W Requirement
n
s t o u
p
q r
Advanced Control System Advanced Control System
(Self-Tuning GPC Controller)
Control signal u(t) Reference
signal w(t)
Output signal y(t)
- A(z-1)
S(z-1) ΔR(z-1) T(z-1)
S(z-1)
Recursive estimator GPC
strategy Configuration
requirements Performance requirements
θID
Controller parameters; S, R, T
2-DOF Controller
Pressure process rig
Adaptation level
ΓRS
Estimated system parameters; A, B
PRBS Generator
Control signal u(t) Reference
signal w(t)
Output signal y(t)
- A(z-1)
S(z-1) ΔR(z-1) T(z-1)
S(z-1)
Recursive estimator Recursive
estimator Recursive
estimator GPC
strategy GPC strategy Configuration
requirements Configuration requirements Performance requirements Performance requirements Performance requirements
θID
Controller parameters; S, R, T
2-DOF Controller
Pressure process rig
Adaptation level
ΓRS
Estimated system parameters; A, B
PRBS Generator
SIMULINK Model SIMULINK Model
(2 (2 - - DOF Controller) DOF Controller)
w u dan y
0.9999 lambda RLS
2 lambda GPC
Theta1 0
Theta
Signal
Setpoint (Reference)
0
SP dan PV 0
S0 , S1 , S2 0
R0 , R1
Input Output
Pressure Process Rig (Feedback 38-714) with Compensations1 PRBS
PreIdentification Output1
128 N-Sample
Switch Memory
[A]
Goto
[A]
From
Demux
Comparison (SP&PV)
RLS_GPC
Adaptive Control System
Experimental Result Experimental Result
(Self-Tuning GPC Controller: with disturbance)
disturbance pre-identification = 18.75 seconds
Tuning parameters:
h = 0.15 seconds λRLS = 0.9999
P(0) = 1000I θ(0) = 0
λGPC = 2 N1=N2=3
