AUTOMAT I C S and AUTOMATIC CONTROL

and AUTOMATIC CONTROL

related nations, classification of control systems
System models – differential equations,

state equations, Linearization of models, Laplace transform, transfer function
Time responses – impulse and step response
Frequency responses – Nyquist plot, Bode plots
Basic dynamics elements – first order system, integrator, differentiator, second order systems, systems with delay
Structure of control system – examples of control systems, description of closed-loop systems
Closed loop system stability – Hurwitz criterion, Nyquist criterion
Quality of control – analyses of steady state, method based on roots placement, method based on integral indices
Compensators and regulators - PID controller
PID controller parameters tuning – Ziegler-Nichols methods, Chien, Hrones and Reswick methods

will, self-acting, of itself," made up of two parts, auto-,

"self," and -matos, "willing,"

Automatics (offen called control or automatic control engineering) field of technology and science, which deals with issues of control of various processes, mainly technological and industrial (usually without the participation or with a limited participation of human being).

Introduction to Automatics and automatic control

of actions) on the object (the technological process) in such

a way as to achieve the intended objectives

Introduction to Automatics and automatic control
TERMINOLOGY

System is any collection of interaction elements for which
there are cause and effect relationships among the variables

or quality of the final product,
which are also called output

variables.

The desired reference signal (input signal or set-point) when performing control is the desired output variable (that might deviate from actual output)


Disturbance variables - these are also called "load"
variables and represent input variables that can cause the
controlled variables to deviate from their respective set
points.

Introduction to Automatics and automatic control
TERMINOLOGY

SYSTEMS
The open-loop system is also called the non-feedback system -

the system does NOT measure the actual output and there is no correction to make that output conform to the desired output

An open-loop system cannot compensate for any disturbances that add to the controller’s driving signal or to the process output

SYSTEMS
The closed-loop system is also called the feedback system -

the system includes a sensor to measure the output and uses feedback of the sensed value to influence the control input variable.

The closed-loop system can compensate for disturbances by measuring the output, comparing it to the desired output, and driving the difference toward zero.

car by using vision: feedback control

In the first case driver

does not have much information about the current position of the car with respect to the road.
In the second case the driver can steer the car back to the desired position despite bumps, wind and other uncontrollable effects.

Introduction to Automatics and automatic control
OPEN LOOP / CLOSED LOOP SYSTEMS
Example:

control
with temperature sensor – closed loop control

Washing machine (open loop

control) :
There is no sensor to measure how dirty is laundry

Introduction to Automatics and automatic control
OPEN LOOP / CLOSED LOOP SYSTEMS
Example:

TRAFIC LIGHTS (open loop control) :
That system don’t control traffic according to crowd

years ago.
The first feedback control device on record is thought

to be the ancient Ctesibios's water clock in Alexandria (3rd century BC).

a vessel and, therefore, the water flow from that vessel.
 This

certainly was a successful device as water clocks .

Europe, automata equipped with dancing figures that repeat the same

task over and over again

Temperature regulator (invented in 1624 )
Pressure regulator ( invented in 1681)

– 1769
Reduced steam flow – reduced pressure on the

blades of the engine turbine

- frequency domain analysis)
1932 Stability analysis (Nyquist)
1940

Autopilots, radar, etc.
1952 Machine tool numerical control (MIT)
1970 State variable models, optimal control
1983 personal computers

HİSTORY

many different ways, by taking into consideration various properties of

the system

1. With respect to the number of controlled variables:
single-variable control system - SISO
multi-variable control system - MISO, MIMO

by the system:

Systems of stabilization
The purpose of these

systems is to keep the controlled quantities at a given (desired) level.
In the stabilization systems the reference value is well known and constant
Typical applications: stabilization of: liquid level, temperature in the room, motor speed, etc.

by the system:

Programmed control systems
The purpose of these

systems is to change the controlled quantitiy according to the time function given.
In these systems the reference value is well known, but it is changing according to the time function given
Typical applications: CNC machine tools (milling machine, lasers, lathes) where the movement of the tools (cutters, turning tools) should be controlled by a programmed controller in order to receive an article of desired shape.

by the system:

Tracking systems (also called follow-up systems)
The

purpose of these systems is to change the magnitude of the controlled quantity according to an unknown time function of reference value (stochastic values of reference).
In these systems, the reference value is not known and varies stochastically
Typical application: anti-aircraft radar system

by the system:

Systems having more complicated tasks:
- extremal

systems,
- optimal systems,
- adaptive systems.

supervision:

Continous-time control systems
Discrete-time control systems

In a continuous-time

control systems changes in control signals are generated in a continuous-time way. This signals will have some values at every instant of time (they are also called analog signals)

in control signals are generated only in some periodically repeating

instants of time, which are called the sampling intants. This signals are also called impulses or digital signals).

application of the superposition principle :

Linear systems
Nonlinear systems

For

linear systems the so called superposition principle can be used, according to which the reaction of the system to a sum of two (or more) inputs equals to the sum of reactions to each of the inputs separately.

These systems can be described by linear differential equations.
For nonlinear systems the superposition principle does not hold