Fuzzy immune PID neural network control

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19 Οκτ 2013 (πριν από 3 χρόνια και 9 μήνες)

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Fuzzy

immune

PID

neural

network

control

method

based

on

boiler

steam

pressure

system

Third

pacific
-
asia

conference

on

circuits

,communications

and

system,

p
.
p
.

1
-
5
,

July

2011

Outline


Abstract


Introduction


Theory

on

fuzzy

neural

network

(FNN)


Immune

PID

control


Fuzzy

neural

network

immune

PID

control


Conclusions


References

ABSTRACT


Steam

pressure

is

a

key

point

to

keep

the

steam

pressure

constant

in

various

operation

situations
.

Considering

steam

pressure

with

the

time

delay

and

uncertainties,

the

sliding

mode

predictive

control

was

used

to

design

the

controller
.

The

predictive

control

was

used

to

deal

with

time

delay,

the

sliding

mode

control

was

used

to

deal

with

the

uncertainties
.

And

the

predictive

control

can

reduce

the

chattering

phenomenon

of

sliding

mode
.

This

simulation

results

show

that

the

proposed

algorithm

can

largely

imporved

the

system

response

performance

compared

to

the

single

generalized

predictive

control

INTRODUCTION


Boiler

system

is

a

complex

industrial

process,

it

has

high

nonlinearity,

large

delay,

strong

coupling

and

load

disturbance
.

Boiler

steam

pressure

power

plant

control

system

is

a

key

link

in

the

system,

which

directly

affect

the

turbine

speed
.

In

engineering,

the

current

steam

pressure

control

system

is

mainly

dominated

by

traditional

PID

control
.

In

theory,

land
-
based

power

plant

boiler,

the

use

of

intelligent

control

strategy

has

been

the

boiler

combustion

system

has

been

extensively

studied

[
1
-
4
]
.

Control

of

the

ship

boiler

control

system

study

is

to

PID

[
5
],

intelligent

control

has

lagged

behind,

only

a

few

fuzzy

or

neural

network

PID

parameter

calibration

literature
.

However,

due

to

the

complexity

of

fuzzy

rules

of

precise

formulation,

making

the

control

precision

is

often

not

very

satisfactory

THEORY ON FUZZY NEURAL
NETWORK


Neural

network

parallel

computing,

distributed

storage,

fault
-
tolerant

capability,

with

adaptive

learning

function

and

a

series

of

advantages
.

But

generally

speaking,

the

expression

of

neural

network

is

not

suitable

for

rule
-
based

knowledge,

and

therefore

the

neural

network

training,

because

it

is

not

already

some

experience

to

good

use

the

knowledge,

often

the

initial

weights

can

only

be

taken

as

zero,

or

the

random

number

,

which

increases

the

training

time

or

network

requirements

into

a

non
-
local

extremum,

which

is

insufficient

neural

network
.

THEORY ON FUZZY NEURAL NETWORK

IMMUNE PID
CONTROL


Intelligent

behavior

of

biological

information

systems

for

science

and

engineering

fields

to

provide

a

reference

for

a

variety

of

theoretical

and

technical

methods
.

Biological

immune

principle

combined

with

conventional

PID

control

from

the

immune

PID

control,

can

be

mutually

reinforcing

in

order

to

further

improve

the

control

performance
.

PID

control

is

a

reference

biological

immune

system,

immune

mechanism

and

design

of

a

nonlinear

control

method
.


FUZZY NEURAL NETWORK IMMUNE PID
CONTROL


CONCLUSIONS


The

system

analyzes

the

dynamic

characteristics

of

the

boiler

steam

pressure,

based

on

the

model

through

the

mechanism

of

a

ship

boiler

steam

pressure

control

system

of

intelligent

control

design,

because

we

are

fully

Use

of

the

advantages

of

the

fuzzy

neural

network,

combined

with

immune

algorithm

gives

an

adaptive,

self
-
learning

algorithm

for

PID

controller

design,

simulation

shows

that

the

control

algorithm

has

good

control

quality
.

REFERENCES