chapter 4 dynamic systems: higher order processes
DESCRIPTION
Chapter 4 Dynamic Systems: Higher Order Processes. Prof. Shi-Shang Jang National Tsing-Hua University Chemical Engineering Dept. Hsin Chu, Taiwan May, 2013. 4-1 Non-interactive Systems – Thermal Tanks. 4-1 Non-interactive Systems –Thermal Tanks – Cont. 4-1 Non-interactive Systems. - PowerPoint PPT PresentationTRANSCRIPT
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Chapter 4 Dynamic Chapter 4 Dynamic Systems: Systems: Higher Order Higher Order ProcessesProcesses
Prof. Shi-Shang JangNational Tsing-Hua UniversityChemical Engineering Dept.
Hsin Chu, TaiwanMay, 2013
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4-1 Non-interactive Systems – 4-1 Non-interactive Systems – Thermal TanksThermal Tanks
21 2 1
21 2 1
42 3 4 2
1
Let ;
2
A A
p v
A p A p v
A p B p A B p v
Tank
duf h t f h t V
dth C T u C T
dTf C T t f C T t V C
dtTank
dTf C T t f C T t f f C T t V C
dt
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4-1 Non-interactive Systems –4-1 Non-interactive Systems –Thermal Tanks – Cont.Thermal Tanks – Cont.
1 22 1
1 2 1
2 44 2 3
2 4 1 2 2 3
1
1
2
1
v
A p
A p B pv
A B p A B p A B p
Tank
V C dt t
f C dt
s s s
Tank
f C f CV C dt t
f f C dt f f C f f C
s s K s K s
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4-1 Non-interactive Systems4-1 Non-interactive Systems
1 1 11 1 1 1 1
1
2 2 22 2 1 2 2 1 2 1 2
2
;2
;2
i o i o
dh dH kA A f k h f F aH F a
dt dt h
dh dH kA A f k h F bH aH bH b
dt dt h
To Workspace
simout
Subtract 2Subtract 1
Subtract
Scope
MathFunction 1
sqrt
Math
Function
sqrt
Integrator 1
1s
Integrator
1s
Gain 3
1.5
Gain 2
0.1
Gain 1
0.1
Gain
1.5
Constant 1
1
Constant
4.5
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4-1 Non-interactive Systems4-1 Non-interactive Systems
1 1 11 1 1 1 1 1 1
2 2 21 2 2 2 1 2 2 2 2 1
1
1
i oi o i o
F FA dH dHH K F F H s H s K F F
a dt a dtA dH dHa
H H K H H s H s K H sb dt b dt
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Transfer Fcn 1
26 .667 s+1
1
Transfer Fcn
26 .667 s+1
2.667
SubtractScope
Constant 2
4
Constant 1
0
Constant
1
Add
NumericalNumerical ExampleExample
21 2 1 2
3 3
3 3
1 21/ 21/ 2
1
1
1
2
11 2
10 ; 4
4 / min; 1 / min
4 1 / min / min1.5
41.5
0.3752 22
12.667
1
1026.667 min
0.375
i o
A A m h h m
f m f m
m mk k
mmk
a bh
Kab
Ka
A
a
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4-1 Non-interactive Systems4-1 Non-interactive Systems
1112 2
2
1
122
s
K
s
K
ss
K
sm
sy p
1 21 2
1 2
1 22 2
; ;2
;1 1
1222
ss
K
sm
sy p
An over-damped second order system has two negative real poles. Therefore, 2s2+2s+1=(1s+1)(2s+1); hence
such that
12
2
sK
= 11
1
sK
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4-2 Interactive Systems – 4-2 Interactive Systems – Thermal Tanks with RecycleThermal Tanks with Recycle
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4-2 Interactive Systems – Thermal 4-2 Interactive Systems – Thermal Tanks with Recycle- Cont.Tanks with Recycle- Cont.
21 4 2 1
1 22 1 4
1 2 1 1 2 4
42 3 4 2
2 44 2
Tank 1
1
Tank 2
A p R p A R p v
v A R
A R p A R A R
C p B p C B p v
C p Bv
C B p C B p
dTf C T t f C T t f f C T t V C
dtV C d f f
t t tf f C dt f f f f
s s K s K s
dTf C T t f C T t f f C T t V C
dtf C fV C d
tf f C dt f f C
3
2 4 3 2 4 31
p
C B p
Ct
f f C
s s K s K s
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4-2 Interactive Systems – 4-2 Interactive Systems – Thermal Tanks with Recycle- Thermal Tanks with Recycle- Cont.Cont.
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0 1 2 3 4 5 6 7 8 9 100
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2-5 Step Response of Second-Order 2-5 Step Response of Second-Order Processes – Over-damped processProcesses – Over-damped process
1112 21
22
ss
K
ss
K
sm
sy pp
m(s)=A/s
12 /2
/1
21
ttpp ee
AKAKty
Inflection point
=3
=2
=11
3s+1
Transfer Fcn1
1
s+1
Transfer Fcn
simout
To Workspace
Scope
1
Constant
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4-2 Interactive Systems4-2 Interactive Systems
1 1 11 1 0 1 1 2 0 1 2
1 2
2 22 2 1 1 2 2 2 1 2 2 1 2
2
2
;2
;
; ;2
i i
dh dH kA A f f k h h F F aH aH a
dt dt h h
dh dHA A k h h k h aH aH eH fH gH
dt dtk
e f a g a eh
f1
Cross-sectional=A2
h2V2
f2
h1V1
fi
Cross-sectional=A1
fo
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4-2 Interactive Systems4-2 Interactive Systems
01 1 11 2 1 1 0 1 2
1 1 1 0 2
2 2 21 2 2 2 1 2 2 2 2 1
1
1
ii
i
F FA dH dHaH H K F F H H
a dt a a dts H s K F F H s
A dH dHfH H K H H s H s K H s
g dt g dt
H1(s)
H2(s)+
+
1
1
1 s
H2(s)
111
1/
2
212
2
21
221
sK
sK
KKK
F0(s)
Fi(s)+
-
F0(s)
Fi(s) +
-
11
1
sK
12
2
sK
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Numerical ExampleNumerical Example
21 2 1 2
3 3
3 3
1 21/ 21/ 2
1
1 2
2
2
1
2
11
22
10 ; 8 ; 4
4 / min; 1 / min
4 1 / min / min1.5
8 41.5
0.3752 22
0.3752
0.75
12.667
0.5
1026.667 min
0.37510
13.333min0.75
i o
A A m h m h m
f m f m
m mk k
mmk
ah h
ke
h
g a e
Kaf
Kg
A
aA
g
180711s
667.2
15.01
333.13667.265.01
333.13667.265.01/5.0667.2
111
1/
)(
2
2
2
212
2
21
2212
s
sssK
sK
KKK
sF
sH
i
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4-1 Second Order Systems4-1 Second Order Systems
2 1
pKY s
X s as bs
A second order system is of the following form:
2 2 2 1
pKY s
X s s s
Another form:
Kp is called process gain, is called time constant, is calleddamping factor. The roots of the denominator are the poles of the system.
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4-1 Second-Order Processes - 4-1 Second-Order Processes - ContinuedContinued
Definition 4-1: A second order process is called over-damped, if >1; is called under-damped if <1; is called critical damped if =1.
Property 4-1: Consider the roots of denominator, in case of over-damped system, the poles of the system are all negative real numbers.
Property 4-2: The poles of a under-damped system are complex with negative real numbers.
Property 4-3: The pole of a critical damped system is a repeated negative real number.
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State Space ApproachState Space Approach
112
1
21
22221
11211
2
1
21
22221
11211
2
1
KKNNNN
KNKNN
K
K
NNNNN
N
N
N
MBXA
M
M
M
bbb
bbb
bbb
X
X
X
aaa
aaa
aaa
X
X
X
dt
dX
Consider the following linear system with N differential equationsK inputs and P sensors
where X is termed the state vector and M is the input vector. The followingobservation equation is available:
112
1
21
22221
11211
2
1
21
22221
11211
2
1
KKPNNP
KPKPP
K
K
NPNPP
N
N
P
MDXC
M
M
M
ddd
ddd
ddd
X
X
X
ccc
ccc
ccc
Y
Y
Y
Y
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State Space Approach _ State Space Approach _ Cont.Cont.
Assume that it is desirable to realize the input/output transfer functionsand neglecting the state variables.
sMsG
sMDBAsIC
sDMsBMAsICsY
sBMAsIsX
sBMsXAsI
sBMsAXssX
KP
1
1
1
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State Space Approach _ State Space Approach _ ExampleExampleInteracting TanksInteracting Tanks
)(0
1.0
075.00375.0
0375.00375.0
)(
)(
)(0
1.0
)(
)(
075.00375.0
0375.00375.0
)(0
1.0
)(
)(
075.00375.0
0375.00375.0
)(
)(
10
01
)(0
1.0
)(
)(
075.00375.0
0375.00375.0
)(
)(
0
1.0
075.00375.0
0375.00375.0
75.0375.010
375.0375.010
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
212
211
sFs
s
sH
sH
sFsH
sH
s
s
sFsH
sH
sH
sHs
sFsH
sH
sH
sHs
FH
H
H
H
dt
d
HHdt
dH
FHHdt
dH
i
i
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State Space Approach _ State Space Approach _ ExampleExampleInteracting Tanks – Cont.Interacting Tanks – Cont.
1s08711s
2.66667)(
0375.0075.00375.0
00375.0
)(0
0375.0075.00375.0
00375.00375.0075.00375.0
075.01.0
10
)(0)(
10
)()()()(
)(
375.075.00375.0
0375.00375.0075.00375.0
075.01.0
)(0
1.0
0375.0075.00375.0
0375.0
375.0075.00375.0
0375.00375.075.00375.0
0375.0
0375.075.00375.0
075.0
)(
)(
22
2
2
2
1
2
2
2
22
22
2
1
sFss
sF
ss
ss
s
sFsH
sH
sDMsCXsHsY
sF
ss
ss
s
sF
ss
s
ss
ssss
s
sH
sH
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State Space to Transfer State Space to Transfer Function-MATLABFunction-MATLAB>> A=[-0.0375 0.0375;0.0375 -0.075]
A =
-0.0375 0.0375
0.0375 -0.0750
>> B=[1;0];C=[0 1];D=0;
>> [num,den]=ss2tf(A,B,C,D,1)
num =
0 -0.0000 0.0375
den =
1.0000 0.1125 0.0014
>> ss=den(3)
ss =
0.0014
>> num=num/ss
num =
0 -0.0000 26.6667
>> den=den/ss
den =
711.1111 80.0000 1.0000
>> tf(num,den)
Transfer function:
-9.869e-015 s + 26.67
---------------------
711.1 s^2 + 80 s + 1
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Rise time
A
B
C
time
Resp
ons
e
2-5 Step Response of Second-2-5 Step Response of Second-Order Processes – Under-damped Order Processes – Under-damped processprocess
1222
sss
AKsy p
/1sin1
2/
2te
AKAKty tp
p
21/ eA
B1. Overshoot=
21/2eB
C 2. Decay Ratio=
3. Rise time=tr=2
1
2
1tan
1
4. Period of oscillation=T=21
2
5. Frequency of oscillation (Natural Frequency)=1/T
Settling time
T
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Example: Temperature Example: Temperature Regulated ReactorRegulated Reactor
0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000100
100.5
101
101.5
102
102.5
103
time(seconds)
tem
pera
ture
(C)
t=3060st=1000sFeed flow rate0.4→0.5kg/sat t=0.
1. What is process gain?2. What is transfer func?3. What is rise time?
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Textbook Reading Assignment Textbook Reading Assignment and Homeworkand Homework
Chapter 2, p41-49Homework p58, 2-9, 2-15, 2-16Due June 8th
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Non-isothermal CSTRNon-isothermal CSTR
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Non-isothermal CSTR- Non-isothermal CSTR- Cont.Cont.
20
M.B. for component A
where
E.B. for the tank
E.B. for the cooling jacket
AAi A A
ERT
A A
p i p A c v
cc c pc ci c c pc c c c c cv
dcf t c t f t c t Vr t V
dt
r t k e c
dTf t C T t f t C T t Vr t H UA T t T t V C
dt
dTf t C T t f t C T t UA T t T t V C
dt
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Non-isothermal CSTR- Non-isothermal CSTR- Cont.Cont.
;56.1
);/(1;36);/(75
/000,12);/(88.0;/55
)/(987.1;/27820
min)/(1033.8;26.13
3
22
3
380
3
ftV
FlbBtuCpcftAFfthBtuU
lbmoleBtuHFlbBtuCpftlb
FlbmoleBtuRlbmoleBtuE
lbmoleftkftV
c
r
Process Information
Steady State Values
min/8771.0;540
9.678;/2068.0
min/3364.1;7.602
635;/5975.0
3
3
3
3
ftfRT
RTftlbmolec
ftfRT
RTftlbmolec
cci
A
c
iAi
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Non-isothermal CSTR- Cont.Non-isothermal CSTR- Cont.Cooling flow rate Cooling flow rate 0.87710.87710.80.8
62.4*1
thou*cp2
62.4*1
thou*cp1
55*0.88
thou*cp
55*0.88
thou*cp
8.33e8
k0
0.8
fc(t)
1.3364
f(t)
12000
dH
0.5975
cAi(t)1s
cA(0.2068)
13.26
V1
13.26
V
75/60*36
UA
635
Ti(t)
1s
Temp (678.9)
540
Tci
1s
Tc(602.7)
Subtract
Scope2
Scope1
Scope
1.987
R
Product5
Product4
Product3
Product2
Product1
Product
eu
MathFunction
[jacket_energy_in]
Goto9
[heat_transfer_out]
Goto8
[reaction_rate]
Goto7
[Tc]
Goto6
[energy_out]
Goto5
[energy_in]
Goto4
[Temp]
Goto3
[mass_out]
Goto2
[jacket_energy_out]
Goto10
[cA]
Goto1
[mass_in]
Goto
[reaction_rate]
From9
[mass_out]
From8
[mass_in]
From7
[Tc]
From6
[Temp]
From5
[cA]
From4
[cA]
From3
[Temp]
From2
[heat_transfer_out]
From17
[jacket_energy_out]
From16
[jacket_energy_in]
From15
[Tc]
From14
[heat_transfer_out]
From13
[reaction_rate]
From12
[energy_out]
From11
[energy_in]
From10
[Temp]
From1
[cA]
From
-27820
EDivide1
Divide
Add2
Add1
Add
1/13.26
1/V
1/(1.56*55*1)
1/(Vc*thouc*Cv)1
1/(13.26*55*0.88)
1/(V*thou*Cv)
Energy Balance of the Reactor
Material Balance of the Reactor
Energy Balance of the Jacket
Inlet and Outlet Energy and Material fluxes of the Reactor
Inlet and Outlet Energy fluxes of the Jacket
Rate Constant Heat Exchange between Jacket and Reactor
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Transfer Functions Derived Transfer Functions Derived by Linearizationby Linearization
DUCX
F
F
CC
y
BUAX
F
F
C
b
b
bbC
aa
aaa
aaC
dt
d
dt
dX
Fbaa
Ff
g
T
g
T
gfTTg
dt
d
dt
dT
bFbaaCa
T
gF
f
g
T
g
T
gC
c
gTfTTcg
dt
d
dt
dT
FbCbaCa
Cc
gF
f
g
T
gC
c
gcfTcg
dt
dC
dt
dc
c
i
Ai
c
A
c
i
Ai
c
A
c
A
cc
cc
cc
cccc
icA
ii
cc
AA
icA
AiA
AiAi
AA
AiAAA
0000010
0
0
000
b0
0
0
0
,,
,,,
,,
34
2322
1211
3332
232221
1211
343332
3333
2322232221
22222,2
12111211
1111,1
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Linearization of the Reactor ExampleLinearization of the Reactor Example
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48.026.13/2068.01033.826.1323364.1/2 9.678987.127820
80
1
1
111
eVceVkf
c
g
x
ga A
TRE
A
It can be shown as generated as above:
Transfer Functions Derived by Linearization – Cont.Transfer Functions Derived by Linearization – Cont.
[num, den]=ss2tf(A,B,C,D,4)num = 0 1.33226762955019e-015 -2.81748023 -1.356898478768den = 1 1.3804 0.3849816 0.038454805392
>> ss=den(4)>> den=den/ssden = 26.0045523519419 35.8966840666205 10.0112741717343 1>> num=num/ssnum = 0 3.46450233194353e-014 -73.2673121415962 -35.2855375273927
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SIMULINK of Linear System - SIMULINK of Linear System - CSTRCSTR
Transfer Fcn
2.07s+1
26 .27s +36 .31s +10 .14s+13 2
To Workspace
simout
ScopeGain
-35 .77
Constant 1
678 .9
Constant
-0.0771
Add
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Non-isothermal CSTR- Cont.Non-isothermal CSTR- Cont.Cooling flow rate Cooling flow rate 0.87710.87710.80.8
0 5 10 15 20 25 30 35 40 45 50678.5
679
679.5
680
680.5
681
681.5
682
Time (min)
Tank
temperature
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Non-isothermal Non-isothermal CSTR- Cont.CSTR- Cont.Linearized Model Linearized Model (page 127)(page 127)
3 2
35.77 2.07 1
26.27 36.31 10.14 1c
s s
F s s s s
0 5 10 15 20 25 30 35 40 45 50678.5
679
679.5
680
680.5
681
681.5
682
Time(min)
Tan
kTem
pera
ture
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The problem of The problem of nonlinearitynonlinearity
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4-3 Step Response of the 4-3 Step Response of the High Order SystemHigh Order System
1 1 1
s s
a b
Ke Keor
s s s
systemsorder high theseeapproximat to
model timedead plusorder first
following theimplement wecases,many In
/1
1
1
( ) 1itnn
in
ii j
jj i
eY t K
1
( )
( ) 1n
ii
Y s K
X s s
X(s)=A/s
n=2
n=3
n=5
n=10
time
Response
s
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4-3 Step Response of the High Order 4-3 Step Response of the High Order System- ContinuedSystem- Continued
11.41
1 3.2
5
s
e
s
s
Method of Reaction Curve:
time
Respons
e
inflection point
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4-3 Step Response of the High 4-3 Step Response of the High Order System- ContinuedOrder System- Continued
time
Response
s
Real
Approximate
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4-3 Response of Higher-4-3 Response of Higher-Order Systems – Cont.Order Systems – Cont.
1
2
1
1 2 1 3 1
0.5 1
1 2 1 3 1
Y s
X s s s s
Y s s
X s s s s
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4-4 Other Types of Process 4-4 Other Types of Process ResponseResponse
( )op o p
i o
df tf t K m t
dtdh t
f t f t Adt
Integrating Processes: Level Process
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4-4 Other Types of Process 4-4 Other Types of Process ResponseResponse
1
1
1
1
i o
po
p
pi
p
H s F s F sAsK
F s M ss
KH s F s M s
As As s
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4-4 Other Types of Process 4-4 Other Types of Process ResponseResponse
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4-4 Other Types of Process 4-4 Other Types of Process ResponseResponse The most general transfer function is as
the following:
p1, p2,…,pn are called the poles of the system, z1, z2,…,zm are the zeros of the system, Kp is the gain.
Note that nm is necessary, or the system is not physically realizable.
n
mp
nn
n
mm
mm
pspsps
zszszsK
asasas
bsbsbsb
sm
sy
21
21
011
1
011
1
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4-4 Poles and Zeros - Example4-4 Poles and Zeros - Example
2
2
243
12
1
222
21
1,
/1
0
1
121
jss
s
s
ssss
KsG
Imaginary part
Real
part
2
21
2
21
1
1
2
1
0
0
Left Half PlaneLHP Right Half Plane
RHP
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4-4 Poles and Zeros - 4-4 Poles and Zeros - ExampleExample
time
Respons
e
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4-4 Location of the Poles and Stability in a Complex Plane
Re
Im
Purdy oscillatory
Purdy oscillatory
Fast Decay Slow Decay
Exponential Decay
Exponential Decay with oscillation
Slow growth
Fast Exponential growth
Exponential growthwith oscillation
Stable (LHP) Unstable (RHP)
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4-4 The Stability of the 4-4 The Stability of the linear systemlinear system
)(lim tyt
Definition 4-2: A system is called stable for the initial point if given any initial point y0, such that ∣y0∣≦ε, there exists a upper bound , such that:
Definition 4-3: A system is called asymptotic stable if given any initial point y0, then
0)(lim
tyt
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4-4 The Stability of the 4-4 The Stability of the linear systemlinear systemDefinition 4-4: A system is called input
output stable if the input is bound, then the output is bounded. (Bounded Input Bounded Output, BIBO)
Property 4-4: A linear system is asymptotic stable and BIBO if and only if all its poles have negative real parts.
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4-4 Stability - Example4-4 Stability - Example
time
Resp
ons
e
G4
G2 G3G1
13011015
1)(
)(
)(1
sss
sGsm
sy
105.011.01
1
)(
)(2
sss
sGsm
sy
1
1)(
)(
)(233
sss
sGsm
sy
113
1
)(
)(24
ssssG
sm
sy
m(s)=1
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Open Loop Unstable Open Loop Unstable Process- Process- Chemical Reactor (text page Chemical Reactor (text page 139)139)
0
M.B. for component A
where
E.B. for the tank
AAi A A
ERT
A A
p i p A c v
dcf t c t f t c t Vr t V
dt
r t k e c
dTf t C T t f t C T t Vr t H UA T t T t V C
dt
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Open Loop Unstable Open Loop Unstable Process- Process- Chemical ReactorChemical Reactor
3
2 3
3
2 3
At 566
9.79 1;
9.75 1 6.6 1
9.75 1 6.6 1
At 620
7.47 1;
11.3 1 11.47 1
11.3 1 11.47 1
i
A
i
i
A
i
T R
s K s
s s s
C s K K
s s s
T R
s K s
s s s
C s K K
s s s
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HomeworkHomeworkText p1484-4, 4-5, 4-7, 4-8, 4-10, 4-11,4-12Due April
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Supplemental Material Supplemental Material
Development of Empirical Development of Empirical Models from Models from Process DataProcess Data
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S-1 IntroductionS-1 IntroductionAn empirical model is a model that
is developed from experience and their parameters are found based on experimental tests.
The most frequent implemented empirical models are first order, second order and/or with time delays.
The input changes is basically a step or an impulse.
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S-2 First Order without Time S-2 First Order without Time Delay Systems Using Step InputDelay Systems Using Step Input
/1)(
1)(
)(
1)(
)(
teKAty
ss
KAsy
s
Asm
s
K
sm
sy
Consider a first order system with a output signal y(t) and input signal m(t), then:
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First Order with Time Delay First Order with Time Delay Systems Using Step InputSystems Using Step Input
/1)(
1)(
)(
1)(
)(
t
s
s
eKAty
ss
KAesy
s
Asm
s
Ke
sm
sy
Consider a first order system with a output signal y(t) and input signal m(t), then:
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Example: A Typical Example: A Typical ExperimentExperiment
Time (second)
Y(temperature,oC,70-100oC)
Y(temperature,mA,4-20mA) Y (temperature, %) ln(1-Y)
0 70 4 0. 0
1 71.74 4.928 0.058 -0.0598
2 76.51 7.472 0.217 -0.2446
3 80.8 9.76 0.360 -0.4463
4 84.64 11.808 0.488 -0.6694
5 88 13.6 0.600 -0.9163
6 90.76 15.072 0.692 -1.1777
7 93.16 16.352 0.772 -1.4784
8 94.99 17.328 0.833 -1.7898
9 96.64 18.208 0.888 -2.1893
10 97.75 18.8 0.925 -2.5903
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Graphical Fitting MethodsGraphical Fitting MethodsFit 1: Method of 63.2% ResponseFit 2: Method of initial slopeFit 3: Method of Log plot
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Example: An Experiment Example: An Experiment PlotPlot
Fit 1Fit 2
15.51)(1
s
sG
18.6
5.0
2
s
esG
s
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Method of log plotMethod of log plot
intercept;1
)(ln
)(1
)1()(
/)(
/)(
slope
t
y
tyy
eKA
ty
eKAty
t
t
Consider a First-Order Plus Dead Time Model
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Method of log plot - ContinuedMethod of log plot - Continued
13.443)(
5969.1443.3*463/0
443.3290.0/1
1.5969
s
esG
tau
s
Fit 3
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Method of log plot - ContinuedMethod of log plot - Continued
0 1 2 3 4 5 6 7 8 9 100
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Fit 3
real
Fit 2Fit 1
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S-3 Over-damped Second Order S-3 Over-damped Second Order Systems Using Step InputSystems Using Step Input
tteKA
eeKAty
eeKAty
s
Asm
ss
Ke
ss
KesG
sm
sy
t
tt
tt
ss
2
2
2/
21
/2
/1
21
/2
/1
2221
1sinh
1
1cosh1
1)(
0 If
1)(
)(
1211)(
)(
)(
21
21
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Smith’s Method for Second Smith’s Method for Second Order SystemsOrder SystemsStep 1: Get time delay by observing the response curve.Step 2: Find time t20 such thaty/y=0.2, find t60 such thaty/y=0.6Step 3: Get t20/t60, then and From the right figure.
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ExampleExample
104.532.4
1)(
2
sssG
t20=1.9
t60=5
t20/t60=0.38From the figuret60/=2.4 =5/2.4=2.1=1.22=4.32, 2 =5.04
0 1 2 3 4 5 6 7 8 9 100
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1