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Chapter 5-1 Karadeniz Technical University Department of Electrical and Electronics Engineering 61080 Trabzon, Turkey Chapter 5-2 State-Space Modelling Bu ders notları sadece bu dersi alan öğrencilerin kullanımına açık olup, üçüncü sahıslara verilmesi, herhangi bir yöntemle çoğaltılıp başka yerlerde kullanılması, yayınlanması Prof. Dr. İsmail H. ALTAŞ’ın yazılı iznine tabidir. Aksi durumlarda yasal i şlem yapılacaktır.

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1

Chapter 5-1

Karadeniz Technical UniversityDepartment of Electrical and Electronics Engineering

61080 Trabzon, Turkey

Chapter 5-2

State-Space Modelling

Bu ders notları sadece bu dersi alan öğrencilerin kullanımına açık olup,üçüncü sahıslara verilmesi, herhangi bir yöntemle çoğaltılıp başkayerlerde kullanılması, yayınlanması Prof. Dr. İsmail H. ALTAŞ’ın yazılıiznine tabidir. Aksi durumlarda yasal işlem yapılacaktır.

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Chapter 5-3

Mechanical System

uxkdtdx

Bdt

xdM =++

22

dtdx

Bxkuffudt

xdM bs

--=--=2

or,2

u(t)

x(t)

M

B

k

)()()()(2 sUsXksXBssXMs =++

Laplace transform;

)(1)( 2 sUkBsMs

sX ++= Transfer Fonksiyonu: G(s)

Chapter 5-4

RLC Circuit

ivi vo

LR

C

)(1)()()(Vi sICs

sILssIRs ++=

1 dtiCdt

diLiR ++= òVoltage of each elementvi =å

)()()(1)(2

sVsGsV

CRsLs

ssI ii =++

=

Transfer fonksiyon , G(s)

Using Laplace transform

Solve for I(s)

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Chapter 5-5

RLC Circuit

Similarities between mechanicaland electrical elements

• L <=> M• R <=> B• 1/C <=> k

)(1)( 2 sUkBsMs

sX ++=

Mechanical system Electrical system

Chapter 5-6

u(t)

x(t)

M

B

k

)(1)( 2 sUkBsMs

sX ++=

Mechanical System

Transfer functionDifferential equation

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Chapter 5-7

Mechanical System

One 2nd order LTI diff. Eq. can bewritten as two 1st order LTI diff. Eq.

Chapter 5-8

Mechanical System

Statevector

A: System matrixB: Input matrixC: Output matrix

StatevariablesOutput variable

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Chapter 5-9

Simulation Diagrams

y(t)

X(s) Y(s) X(s) Y(s)

X(s) Y(s)s-1

Chapter 5-10

U(s) Y(s)

Transfer Function to Simulation Diagram

U(s) Y(s)Z(s)

D(s)1

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Chapter 5-11

Transfer Function to Simulation DiagramEXAMPLE

(Initial conditions are zero)

Chapter 5-12

StateEquations

Outputequation

Transfer Function to Simulation DiagramEXAMPLE

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Chapter 5-13

+++

+

ControlCanonicalform

Transfer Function to Simulation DiagramEXAMPLE

Chapter 5-14

+ +++

From Figure

Transfer Function to Simulation Diagram

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Chapter 5-15

Multiply by

The type of this TF is similar to the obtained using Mason’s gainFormula as described below.

Transfer Function to Simulation Diagram

Chapter 5-16

Product of the ith foward path gains

1 – the loops remaining after removing path i. If noneremain, then Δi = 1.

Mason’s gain Formula

Transfer Function to Simulation Diagram

:Δ:M

i

i

1 - (S all individual loop gains

+ (Snontouching loop gains taken two at a time.)

- (S nontouching loop gains taken three at a time)+ ................

:D

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Chapter 5-17

So we have,

We have 3 paths from input to output

Transfer Function to Simulation Diagram

u y

Chapter 5-18

+ + ++ +

+

+

Transfer Function to Simulation Diagram

u y

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Chapter 5-19

Transfer Function to Simulation Diagram

Denominator of the transfer function

0

y

Chapter 5-20

Transfer Function to Simulation Diagram

y

+ +

---

+

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Chapter 5-21

Transfer Function to Simulation Diagram

+ + ++ +

+

+

Block diagramrepresenting thenominator

Get the complete block diagram by combining these two diagrams.

+ +

---

+Block diagramrepresenting thedenominator

Chapter 5-22

Transfer Function to Simulation Diagram

ObserverCanonicalform

---

+ + +

+ + x1x3 x2

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Chapter 5-23

Transfer Function to Simulation Diagram

Observer Canonical form

---

+ + ++ + x1x3 x2

From figure:

Stateequations

Chapter 5-24

Transfer Function to Simulation Diagram

Controlcanonicalform

Observercanonicalform

Two different simulation diagramThe number ofsimulation diagrams is n

Two differentstateequations

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Chapter 5-25

State-Space to Transfer Function

U(s) Y(s)

For a SISO system.

Chapter 5-26

State-Space to Transfer Function

alınırsa

For a SISO system.

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Chapter 5-27

State-Space to Transfer Function

Chapter 5-28

Matrices A, B, C and D are given below. Obtain the poles, zeros,characteristic equation, and the transfer function of this system.

State-Space to Transfer Function Example

Solution

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Chapter 5-29

State-Space to Transfer Function Example

Chapter 5-30

Zeros: -(-2+j1.7321)-(-2-j1.7321)

Poles: -1 ve -2

State-Space to Transfer Function Example

Characteristic Equation:

Transfer function

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Chapter 5-31

State-Space to Transfer Function Example

% From State space% to transfer functionA=[0 1;-2 -3];B=[1;2];C=[1 0];D=1;[num, den]=ss2tf(A,B,C,D)zeros=roots(num)poles=roots(den)

>>state_tf <enter>

num =1 4 7

den =1 3 2

zeros =-2.0000 + 1.7321i-2.0000 - 1.7321i

poles =-2-1

state_tf.m file Matlab command window

Chapter 5-32

Review following topics and solve the problems given.

Solution of the state equations using Laplace transformation.

Solution of the state transition matrix using inverse Laplacetransformation.

Search alternative solution methods to the following equation.

The solution of the state transition matrix using infitite series.

A, B, C and D matrices and vectors are given below. Solve the stateequations of this system and obtain the values of x((t) using the methodsdescribed above.

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Chapter 5-33

The state equations of a system are obtained from its differential equations ortransfer function. Various methods are applied to solve the state equations.

Chapter 5-34

Laplace

Apply thge same process to the 2nd set of the equations:

If the Laplace transformation of all equations are obtained in the same way andcombined , the general form given below is obtained.

Let us write this equation for X(s);

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Chapter 5-35

The state vector x(t) is obtained by getting the Inverse LaplaceTransformation.

DURUM GEÇİŞ MATRİSİ

Chapter 5-36

(It is also called the base matrix.)

Remarks:v An nth order system has an nth order state transition matrix.v The invers Laplace transformation of a matrix is defined as the inverse

Laplace transformations of its individual elements.v The inverse Laplace transformation of the last equation is difficult, time

consuming and possibility of making mistake is high.v The most practical way of solving state vector x(t) is the computer

simulation.

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Chapter 5-37

A transfer function is given above. Write the state equations of this system inobserver canonical form and solve for the state variables.

Chapter 5-38

continued...

State transition matrix:

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Chapter 5-39

Continued...

Solve the second part of the general solution equation for a unit step (u(t)=1)input.

Chapter 5-40

Then

The solution:

Continued...

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Chapter 5-41

The inverse Laplacetransform of the product oftwo terms in s-domain canbe expressed as aconvulation integral.

The solution with the Convulation theorem can be written as follows:

Zero input (includesthe initial values)

Zero state depends on inputs.(forced solution)

The statetransition matrixacts as a centre insolution of thestate equations.

Chapter 5-42

Bir önceki örnekte elde edilen durum geçiş matrisini ve B girişvektörünü basamak giriş işareti ile birlikte kullanarak x(t)bağıntısının sağ tarafında verilen konvülasyon integralinihesaplayınız.

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Chapter 5-43

Devam...

Elde edilen bu zorlanmış çözüm daha önce elde edilen çözümle aynıdır. Toplamçözümü elde etmek için durum geçiş matrisinin sıfır giriş kısmındaki F(t)x(0)çözümünün de buna eklenmesi gerekir.

Şu ana kadar yapılan çözümler ya Laplace dönüşümü, ya da Laplace dönüşümüile konvülasyon integralinin birleştirilmesiyle elde edildi. Bu yöntemlerin her ikiside uzun ve hata yapmaya açıktır.

Chapter 5-44

Bütün sistem girişlerinin sıfır olduğu durum için durum denklemleri:

U(t)=0

Böylece;

Denkleminde U(s)=0 yani u(t)=0 için

Denkleminin çözümü bir vektör olarak elde edilir. Öğle ki vektöraşağıdaki gibi bir seriyle ifade edilebilir.

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Chapter 5-45

Ai : Bilinmeyen katsayılar

t : zaman ölçeği

Bu denklemin türevi alınırsa;

Chapter 5-46

Şimdi aşağıdaki işlemleri gerçekleştirelim:

v Yukardaki son denklemi t=0 için elde edelim

v Bu son denklemin türevini alıp, sonucu t=0 için yazalım

v Tekrar türevini alıp, t=0 için yeniden yazalım

v Bu işlemin her tekrarlanmasında bilinmeyen Ai matrisinde birdenklem elde edilir.

v Bu işlemin etkisiyle yukarıdaki son denklemde ti katsayılarıeşitlenmektedir.

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Chapter 5-47

Bu işlemler yapılırsa:t=0

Türev alıp, t=0 için düzenlenirse

Tekrar türev alıp, t=0 için düzenlenirse

T=0 için aşağıdaki denklem yeniden yazılırsa;

Olduğu görülür. Ve diğer matrislerbağıntısından elde edilir.

Chapter 5-48

Olarak elde edilince, Olarakbelirlenir.

Böylece durum geçiş matrisi aşağıdaki gibiyazılabilir.

Bu ifade Taylor serisine benzemekte olup, skaler bir exponansiyel olarak ifadeedilebilir.

Kullanılan notasyona uygun olması bakımından durum geçiş matrisi için;

Yazılabilir.

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Chapter 5-49

Serisinin sonlu bir sayıda sıfır olmayan terimlere sahip olduğu durum için transferfonksiyonu

Olan bir sistemi ele alalım.

Verilen sistem aşağıdaki işaret akış grafiği ile temsil edilebilir.

U(s) Y(s)

Böylece durum denklemleri:

Chapter 5-50

Devam...U(s) Y(s)

Şekilden:

Benzer şekilde;

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Chapter 5-51

Devam...Böylece

denkleminden

Durum geçiş matrisi;

Bu örnekte durum geçiş matrisi kolayca elde edildi. Ancak her zamanböyle kolay olmayabilir.

Chapter 5-52

İkinci dereceden bir sistem aşağıdaki matrislerle temsiledilmektedir.

Aşağıdaki koşullar için çözümleri bulunuz.

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Chapter 5-53

Önce durum geçiş matrisi hesaplanmalı.

Chapter 5-54

Devam...

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Chapter 5-55

Aşağıdaki sistem için F(t) durum geçiş matrisini hesaplayınız.

Olduğuna göre

Chapter 5-56

Devam...

% state_trans.m% State trans. matr.A=[0 1; -2 -3];t = sym('t');STM = expm(A * t)

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Chapter 5-57

% MATLAB Program› kontrol1.m% transfer fonksiyonundan% durum degiskenlerine donusum% pay ve payda verilerinum=[2 8 6];den=[1 8 16 6];[A,B,C,D]=tf2ss(num,den);printsys(A,B,C,D)

» kontrol1a =

x1 x2 x3x1 -8.00000 -16.00000 -6.00000

x2 1.00000 0 0x3 0 1.00000 0

b =u1

x1 1.00000x2 0x3 0

c =x1 x2 x3

y1 2.00000 8.00000 6.00000d =

u1y1 0

Chapter 5-58

% kontrol2.m% Durum matrisi ve% diger verilerA=[0 -2; 1 -3]; B=[2;0];C=[1 0]; D=[0];dt=0.2;DGM=expm(A*dt);DGM

» kontrol2

DGM =

0.9671 -0.29680.1484 0.5219

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Chapter 5-59

% program kontrol3.m% lsim fonksiyonu ile durumlarin% ve cikisin elde edilmesi% Durum matrisi ve diger verilerA=[0 -2; 1 -3]; B=[2;0]; C=[1 0];D=[0];x0=[1 1];t=[0:0.01:1];u=0*t;[y,x]=lsim(A,B,C,D,u,t,x0);subplot(211), plot(t,x(:,1))xlabel('time[sec]'), ylabel('x1')subplot(212), plot(t,x(:,2))xlabel('time[sec]'), ylabel('x2')

lsim fonksiyonu

Chapter 5-60

Aralarında yay bulunan iki kütleli bir sistemin simülasyonu(ref. Modern Control Systems by Dorf and Bishop page 160)ÖRNEK

% program Ornek01.m% Ornek simulasyon programi .Aralarinda yay bulunan iki kutleli bir sistem% Model parametreleriM1=0.02; M2=0.0005;b1=410e-03; b2=4.1e-03; k=10;t=[0:0.001:1.5];% durum degisken modeli verileriA=[ 0 0 1 0;

0 0 0 1;-k/M1 k/M1 -b1/M1 0;k/M2 -k/M2 0 -b2/M2 ];

B=[0; 0; 1/M1; 0]; C=[0 0 0 1]; D=0;u=1; % Birim basamak simulasyonuy=step(A,B,C,D,u,t);plot(t,y)xlabel('time[sec]'), ylabel('hareket hizi (m/s)')grid

birimlerk : kg/mb : kg/m/sm : kg

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Chapter 5-61

Aralarında yay bulunan iki kütleli bir sisteminsimülasyonu (ref. Modern Control Systems by Dorfand Bishop page 160)

ÖRNEK

Chapter 5-62

Sürekli Miknatisli Dogru Akim motorununSimulasyonu - 01ÖRNEK

% Program Kontrl04.m% PMDC motor denklemleri% verilerVa=36; Ia=15; Inl=1.62;Ra=1.4; La=0.00805; Ka=0.095;Km=Ka; Nn=3400;Bm=4.31e-4; Jm=7.432e-4;K0=0.106309; K1=8.4e-5;K2=1.1e-6;A=[ -(Ra/La) -(Ka/La)

Km/Jm -(Bm/Jm) ];B=[ 1/La 0

0 -(1/Jm) ];

» kontrl04» AA =

-173.9130 -11.8012127.8256 -0.5799

» BB =

1.0e+003 *0.1242 0

0 -1.3455

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Chapter 5-63

Sürekli Miknatisli Dogru Akim motorununSimulasyonu - 02ÖRNEK

% PMDC motor denetimsiz tepkesi% verilerVa=36; Ia=15; Inl=1.62; Nn=3400;Ra=1.4; La=0.00805; Ka=0.095; Km=Ka;Bm=4.31e-4; Jm=7.432e-4;K0=0.106309; K1=8.4e-5; K2=1.1e-6;A=[ -(Ra/La) -(Ka/La)

Km/Jm -(Bm/Jm) ];B=[ 1/La; 0]; C=[0 1]; D=[0 ] ;TL=0;% Birim basamak simulasyonuu=1; t=[0:0.01:2];y=step(A,B,C,D,u,t);plot(t,y,'r')xlabel('ZAMAN (s)');ylabel('Motor Hizi (rad/s)')

Chapter 5-64

Sürekli Miknatisli Dogru Akim motorununSimulasyonu - 02ÖRNEK

Jm=7. 432´10-4

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Chapter 5-65

Sürekli Miknatisli Dogru Akim motorununSimulasyonu - 02ÖRNEK

Jm=7. 432´10-6

Chapter 5-66

Sürekli Miknatisli Dogru Akim motorununSimulasyonu - 02ÖRNEK

Jm=7. 432´10-3

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Chapter 5-67

SÜREKLI MIKNATISLI DA MOTORUNUNZAMAN TEPKELERI

% Program Kontrl04.m% PMDC motor denetimsiz tepkesi. Transfer Fonksiyonu (TL=0 icin)% Birim basamak tepkesi, Birim darbe tepkesi, birim rampa tepkesi% verilerVa=36; Ia=15; Inl=1.62; Nn=3400;Ra=1.0; La=0.08; Ka=0.095; Km=Ka; %La=0.00805; Bm=4.31e-4;Jm=7.432e-4; % Jm=7.432e-6; % Jm=7.432e-3;K0=0.106309; K1=8.4e-5; K2=1.1e-6;A=[ -(Ra/La) -(Ka/La)

Km/Jm -(Bm/Jm) ];B=[ 1/La; 0 ]; C=[0 1]; D=[0 ] ; TL=0;

Chapter 5-68

[num, den]=ss2tf(A,B,C,D); % Transfer fonksiyonu% Bulunan transfer fonkiyonu:% num = 1597.8; den = S^2 +13.0799 S + 159.0420% Birim basamak tepkesi

u=1; t=[0:0.01:1];[ys1,xs1,ts1]=step(A,B,C,D,u,t);[ys2,xs2,ts2]=step(num,den,t);

% Birim darbe tepkesi[yi1,xi1,ti1]=impulse(A,B,C,D);[yi2,xi2,ti2]=impulse(num,den,t);

% Birim rampa tepkesinum2=[0 num]; den2=[den 0];[yr1,xr1,tr1]=step(num2,den2,t);AA=[A zeros(2,1);C 0]; BB=[B;0];CC=[0 0 1]; DD=0; % y=x3=z alinirsa[yr2,xr2,tr2]=step(AA,BB,CC,DD);

SÜREKLI MIKNATISLI DA MOTORUNUNZAMAN TEPKELERI

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Chapter 5-69

% Grafiklersubplot(211)plot(ts1,ys1)xlabel('ZAMAN (s)'); title('Birim Basamak Tepkesi (rad/s)'); gridsubplot(212)plot(ts2,ys2); xlabel('ZAMAN (s)'); title('Birim Basamak Tepkesi (rad/s)'); grid;pausesubplot(211)plot(ti1,yi1); xlabel('ZAMAN (s)'); title('Birim Darbe Tepkesi (rad/s)'); gridsubplot(212)plot(ti2,yi2); xlabel('ZAMAN (s)'); title('Birim Darbe Tepkesi (rad/s)'); grid;pausesubplot(211)plot(tr1,yr1,'o',t,t,'-'); xlabel('ZAMAN (s)'); title('Birim Rampa Tepkesi (rad/s)');gridsubplot(212)plot(tr2,yr2,'o',t,t,'-'); xlabel('ZAMAN (s)'); title('Birim Rampa Tepkesi (rad/s)'); grid

SÜREKLI MIKNATISLI DA MOTORUNUNZAMAN TEPKELERI

Chapter 5-70

SÜREKLI MIKNATISLI DA MOTORUNUNZAMAN TEPKELERI

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Chapter 5-71

SÜREKLI MIKNATISLI DA MOTORUNUNZAMAN TEPKELERI

Chapter 5-72

SÜREKLI MIKNATISLI DA MOTORUNUNZAMAN TEPKELERI

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Chapter 5-73

SÜREKLI MIKNATISLI DA MOTORUNUNHIZ ve KONUM KONTROLÜ

PMDC Motor kontrol simülasyonu

PID Controller

Chapter 5-74

SÜREKLI MIKNATISLI DA MOTORUNUNHIZ ve KONUM KONTROLÜ

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Chapter 5-75

SÜREKLI MIKNATISLI DA MOTORUNUNHIZ ve KONUM KONTROLÜ

Chapter 5-76

SÜREKLI MIKNATISLI DA MOTORUNUNHIZ ve KONUM KONTROLÜ

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Chapter 5-77

Controllability

andObservability

Chapter 5-78

Controllability and Observability

v A system is said to be completely controllable ifthere exists a control input transferring any statevariable to a desired final location; otherwise thesystem is uncontrollable.

v A system is said to be completely observable ifthe initial state vector x(t0) can be found usingcontrol input u(t) and measured output y(t);otherwise the system is unobservable.

Basic Definitions

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Chapter 5-79

Controllability

(a) (b)

-a2

-a3

-a1

u

x1

x2

x3

y

-a5

-a6

-a4

u

x1

x2

x3

y

x.1

x.2

x.3

x1

x2

x3

=

-a1 0 0

0 -a2 0

0 0 -a3

+

111

ux.

1x.

2x.

3

x1

x2

x3

=

-a4

0 00 -a

5 00 0 -a

6

+

011

u

UncontrollableControllable

Chapter 5-80

Controllability

is controllability matrix.

An nth order plant

is completely controllable if the matrix

is of rank n where

det( ) is nonzero.

x = Ax + Bu.

Pc =[B AB A B … A B2 n-1

Pc

Pc

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Chapter 5-81

Controllability

The state equation for a system is given above. Determine whether the systemis controllable.

Determinant of = -48Rank of is 3

% contr_matr.mA=[-1 2 00 -2 00 0 -3]B=[0;2;3]Pm=ctrb(A,B)Rank=rank(Pm)Det=det(Pm)

Controllable

x = Ax + Bu =. x

-1 2 00 -2 00 0 -3

+023

u

0 4 -122 -4 83 -9 27

Pc =[B AB A B] =2

PcPc

Chapter 5-82

Observability

(a) (b)

-a2

-a3

-a1

u

x1

x2

x3

y

-a5

-a6

-a4

u

x1

x2

x3

y

x1

x2

x3

= 1 1 1y=Cx x1

x2

x3

= 0 1 1y=Cx

Observable Unobservable

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Chapter 5-83

Observability

is controllability matrix.

An nth order plant

is completely observable if the matrix

is of rank n where

det( ) is nonzero.

x = Ax + Bu.

Po

Po

y = Cx

P =o

CCA

.

.

.

CAn-1

Po

Chapter 5-84

Observability

The state equation for a system is given above. Determine whether the systemis observable.

% obs_matr.mA=[0 1 00 0 1

-1 -2 -3]C=[0 4 1]Po=obsv (A,C)Rank=rank(Po)Det=det(Po)

Observable

x = Ax + Bu =. x

0 1 00 0 1

-1 -2 -3+

012

u

0 4 1-1 -2 1-1 -3 -5

0 4 1y = Cx =

Determinant of = -23Rank of is 3Po

Po

P =o

CCACA

2 =