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Lecture Fundamentals of control systems: Chapter 8 - TS. Huỳnh Thái Hoàng

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Lecture "Fundamentals of control systems - Chapter 8: Analysis of discrete control systems" presentation of content: Stability conditions for discrete systems, extension of Routh - Hurwitz criteria, jury criterion, root locus,... Invite you to reference.

Trang 1

Lecture Notes

Fundamentals of Control Systems

Instructor: Assoc Prof Dr Huynh Thai Hoang

Department of Automatic Control Faculty of Electrical & Electronics Engineering

Ho Chi Minh City University of Technology

Email: hthoang@hcmut.edu.vn

huynhthaihoang@yahoo.com Homepage: www4 hcmut edu vn/ hthoang/

Homepage: www4.hcmut.edu.vn/~hthoang/

Trang 2

Chapter 8

ANALYSIS OF DISCRETE CONTROL SYSTEMS

Trang 3

 Stability conditions for discrete systems

Content

 Stability conditions for discrete systems

 Extension of Routh-Hurwitz criteria

 Jury criterion

 Root locus

St d t t

 Steady state error

 Performance of discrete systems

Trang 4

Stability conditions for discrete systems

Trang 5

Stability conditions for discrete systems

 A system is defined to be BIBO stable if every bounded

 A system is defined to be BIBO stable if every bounded input to the system results in a bounded output.

z

  0

The region of stability for a

contin o s s stem is the

The region of stability for a

Trang 6

Characteristic equation of discrete systems

 Discrete systems described by block diagram:

(

)()

()

1(

k k

y

k r k

k

d

d d

x C

B x

A x

 Characteristic equation: det(z IA )  0

Trang 7

Methods for analysis the stability of discrete systems

 Algebraic stability criteria

 Algebraic stability criteria

The extension of the Routh-Hurwitz criteria

J ’ t bilit it i

Jury’s stability criterion

 The root locus method

Trang 8

The extension of the

The extension of the Routh Routh Hurwitz criteria Hurwitz criteria

Trang 9

The extension of the

The extension of the Routh Routh Hurwitz criteria Hurwitz criteria

 Characteristic equation of discrete systems:

Im z

C a acte st c equat o o d sc ete syste s

0

1 1

n

n n

a z

a z

1

Re w

Region of stability

 The extension of the Routh-Hurwitz criteria : transform

z  w, and then apply the Routh – Hurwitz criteria to the , pp y

characteristic equation of the variable w.

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The extension of the

The extension of the Routh Routh Hurwitz criteria Hurwitz criteria – – Example Example

 Analyze the stability of the following system:

 Analyze the stability of the following system:

T

3)

(

e G

G

1

1)

(

1 GH z

Trang 11

The extension of the

The extension of the Routh Routh Hurwitz criteria Hurwitz criteria – – Example (cont’) Example (cont’)

G z

3 )

G

s

) (

3 (

3 )

1

s s

s

e

) 1 (

1 )

) )(

)(

1 (

)

( )

1 (

e z

z

B Az

z z

z

0673 0

) 1

( 3 )

1

(  e30.5   e0.5

A

) )(

)(

1 (

) (

) )(

(

1

e z e

z z

B Az

z b

s a s

) 1

( )

1 ( 3

0673

0 )

3 1 ( 3

) (

) (

5 0 3 5

0 5

0 5

0

e

e B

A

) 1

( )

1 (

) (

) 1

( )

1 (

e be

e ae

a b ab

e a

e b

A

aT bT

bT aT

bT aT

3 1 ( 3

) (

) 1

( )

1 (

a b ab

e be

e ae

0 )(

223

0 (

z z

GH

Trang 12

The extension of the

The extension of the Routh Routh Hurwitz criteria Hurwitz criteria – – Example (cont’) Example (cont’)

 The characteristic equation:

 The characteristic equation:

0)

(

1 GH z

0)

607

0)(

223

0(

104

0202

11

1 1

1

 

104

0 202

.

0 )

z GH

0 104

.

0 1

1 202

0 1

1 135

0 1

1 83

0 1

w w

w w

w

) 607

0 )(

223

0 (

G

2 3

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The extension of the

The extension of the Routh Routh Hurwitz criteria Hurwitz criteria – – Example (cont’) Example (cont’)

 The Routh table

 The Routh table

 Conclusion: The system is stable because all theterms in the first column of the Routh table arepositive

0 611

0 52

1 354

6 648

5 867

.

1 w4  w3  w2  w  

positive

Trang 14

Jury stability criterion

Trang 15

Jury stability criterion

 Analyze the stability of the discrete system which has

 Analyze the stability of the discrete system which has

the characteristic equation:

0

1

1 1

n n

n n

a z

a z

a z

 Jury table: consist of (2n+1) rows.

The first row consists of the coefficients of the

The first row consists of the coefficients of the

characteristic polynomial in the increasing index order

The even row (any) consists of the coefficients of the previous row in the reverse order.

 The odd row i = 2k+1 (k 1) consists (nk+1) terms,

the term at the row i column j defined by:

the term at the row i column j defined by:

3 ,

2 1

, 2

3 ,

1 1

, 1 1

c

Trang 16

Jury stability criterion (cont’)

Jury criterion statement: The necessary and

sufficient condition for the discrete system to be

t bl i th t ll th fi t t f th dd f thstable is that all the first terms of the odd rows of the Jury table are positive

Trang 17

Jury stability criterion

Jury stability criterion – – Example Example

 Analyze the stability of the system which has the characteristic

 Solution: Jury table

 Analyze the stability of the system which has the characteristic equation:

01

32

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The root locus of discrete systems

Trang 19

The root locus (RL) method

 RL is a set of all the roots of the characteristic equation of

 RL is a set of all the roots of the characteristic equation of

a system when a real parameter changing from 0  + 

 Consider a discrete system which has the characteristic equation:

)

(z

N

0)

z

N K

)(

)

()

(

0

z D

z

N K z

Denote:

 The rules for construction of the RL of continuous system

Assume that G0(z) has n poles and m zeros.

y can be applied to discrete systems, except for the step 8.

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Rules for construction of the RL of discrete systems

Rule 1: The number of branches of a RL = the order of the

Rule 1: The number of branches of a RL = the order of the

characteristic equation = number of poles of G0(z) = n.

Rule 2:

 For K = 0 : the RL begin at the poles of G0(z)

 As K goes to + : m branches of the RL end at m zeros

of G0(z) , the n m remaining branches goes to 

approaching the asymptote defined by the rule 5 and

approaching the asymptote defined by the rule 5 and

rule 6

Rule 3: The RL is symmetric with respect to the real axis.

Rule 3: The RL is symmetric with respect to the real axis.

Rule 4: A point on the real axis belongs to the RL if the

total number of poles and zeros of G0(z) to its right is odd.

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Rules for construction of the RL of discrete system (cont’)

Rule 5: The angles between the asymptotes and the real

Rule 5: The angles between the asymptotes and the real axis are given by:

m n

l

 (2 1) (l  0,1,2,)

Rule 6: The intersection between the asymptotes and

the real axis is a point A defined by:

m

n

the real axis is a point A defined by:

z p

p m

n

i i

Rule 7: : Breakaway / break-in points (or

break points for short), if any, are located in  0

d dK

the real axis and are satisfied the equation: dz

Trang 22

Rules for construction of the RL of discrete system (cont’)

Rule 8: The intersections of the RL with the unit circle can

Rule 8: The intersections of the RL with the unit circle can

be determined by using the extension of the Routh-Hurwitz criteria or by substituting z=a+jb (a2 +b2 =1) into the

characteristic equation

Rule 9: The departure angle of the RL from a pole p j (of

Rule 9: The departure angle of the RL from a pole p j (of

multiplicity 1) is given by:

0

)(

)(

i j

i

i j

, 1 1

0

)arg(

)arg(

Trang 23

The root locus of discrete systems

The root locus of discrete systems – – Example Example

 Consider a discrete system described by a block diagram:

 Consider a discrete system described by a block diagram:

5)

(

s s

K s

(

1 G z

Trang 24

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

5 )

(

s s

K s

5 )

1

s s

( )

1 5 0

[(

) 1

(

5 0 5

0 5

) 1 (

5

)]

5 0 1

( )

1 5 0

[(

) 1

e z

z

e e

z e

z z

K

K z

G

) 607

0 )(

1 (

) (

z z

K z

0 )(

1 (

 Poles: p1  1 p2  0 607

) (

) 1 (

)

e z z

a a

Trang 25

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

 The asymptotes:

 The asymptotes:

1 2

) 1 2

( )

1 2

1 2

) 857

0 ( ] 607

0 1 [

OA poles

464

0 021

0 018

0 021

.

z z

0 036

0 021

0 021

0

Trang 26

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

 The intersection of the root locus with the unit circle:

 The intersection of the root locus with the unit circle:

(*)  (z 1)(z  0.607)  K(0.021z  0.018)  0

(**)

0)

607

0018

.0()

607

1021

.0(

z

Method 1: Apply the extension of Routh – Hurwitz criteria:

Perform the transformation

607

0018

.0(

1)

607

1021

.0(

w

0)

607

0018

.0

(1

)607

1021

.0

Trang 27

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

According to the corollary of the Hurwitz criterion the stability conditions are:

0214

3

0036

.0786

0

0

K K

K K

1485

1

8187

05742

Trang 28

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

Method 2: S ubstitute z = a + jb into (**) :

Method 2: S ubstitute z = a + jb into (**) :

0 )

607

0 018

0 ( )

)(

607

1 021

0 ( )

6070

0180

0)

607

0018

.0

6070

0180

()

6071

0210

(

2

K

K 1.607) (0.018 0.607) 0021

.0(

z

Trang 29

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

 Combine wit h a2 + b2 =1 we have the set of equations:

 Combine wit h a2 + b2 =1, we have the set of equations:

607

1021

.0(2

2 2

b a

b K

j ab

05742

83.21

K

cr K

Trang 30

The root locus of discrete systems

The root locus of discrete systems – – Example (cont’) Example (cont’)

Trang 31

Frequency response of discrete systems

Trang 32

Frequency response of discrete systems

 E act freq enc response: s bstit te ze jT into the

 Exact frequency response: substitute into the

transfer function G(z)

e

z

)(e j T

 Ex: Transfer function:

)6.0(

10)

(

z z

z G

 Frequency response:

)6.0(

10)

(

j T j T

T j

e e

e

 Draw the exact Bode diagram of discrete systems:

 Difficult

 Cannot apply the addition property of the Bode plot

 Note: Sampling theorem: f s

 Note: Sampling theorem: f s

Trang 33

Frequency response of discrete systems

Frequency response of discrete systems – – Example Example

 Consider the discrete system:

 Consider the discrete system:

T

)3(

12)

(

s s

s

G

1 0

T

 Plot the frequency response of the open-loop system

Solution:The transfer function of the open-loop system:

Solution:The transfer function of the open-loop system:

z

G( ) (1 1)Z ( )

7410

7411

0493

00544

0)

 Frequency response:

741

0741

.1)

e

Trang 34

Frequency response of discrete systems

Frequency response of discrete systems – – Example (cont’) Example (cont’)

Exact Bode diagram (Matlab)

Trang 35

The bilinear transformation

2/

1 Tw2 z 1

 Bilinear transformation:

2/1

2/1

Tw

Tw z

z

z T

G( )   G(w) wj

Trang 36

Relationship between frequency in w

Relationship between frequency in w plane and continuous frequency plane and continuous frequency

12

e T

z

z

T j

z

z T

Trang 37

Procedure for drawing approximate Bode diagram

Step 1: Perform the bilinear transformation:

2/

1 Tw

z  

2/

1 Tw

z

Step 2: p Substitute , then apply the procedure for wjw pp y p

drawing the Bode diagram presented in chapter 4

w

Trang 38

Stability analysis of discrete systems using frequency response

crossover frequency, remember the relationship:

 The stability of discrete systems can be analyzed by using

Bode diagrams as continuous systems

Trang 39

Performance of discrete systems

Trang 40

Time response of discrete systems

 Time response of a discrete system can be calculated by

 Time response of a discrete system can be calculated byusing one of the two methods below:

Method 1 : if the discrete system described by a transfer

Method 1 : if the discrete system described by a transfer

function, first we calculate Y(z), and then apply the

inverse z-transform to find y(k) y( )

equations, first we find the solutionq x(k)( ) to the stateequations, then calculate y(k)

 Dominant poles of a discrete system are the poles lyingclosest to the unit circle

Trang 41

y

y

y and y are the maximum and steady state values of y(k)

y max and y ss are the maximum and steady-state values of y(k)

 Settling time: ts  ksT

where k s satisfying the condition:

k k

y y

k

y( )  . ss  

s

k k

y k

y   ,  

100

)( ss

k k

y k

Trang 42

Transient performances

Method 2

Method 2: Analyzing the transient performances based

Method 2

Method 2: Analyzing the transient performances based

on the dominant poles

 The dominant poles: z*  re j

2 ,

1

)(ln

)(ln

T n

Trang 43

Steady state error

(1

)

()

(

z GH z

G

z

R z

Trang 44

Performances of discrete system

Performances of discrete system – – Example 1 Example 1

Y( )

R( )

10 )

T

) 3 )(

2 (

) (

s s

s G

1 Calculate the closed-loop transfer function of the system.p y

2 Calculate the time response of the system to step input

3 Evaluate the performance of the system: POT, settlingtime, steady-state error

 Solution:

1 The closed-loop TF of the system:p y G cl (z)  G(z)

)(1

)

(

z G

cl

Trang 45

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

2 (

10 )

s G

2(

10)

1

( 1

s s

s

z Z

))(

)(

1(

)

()

1(

e z

z

B Az

z z

) )(

)(

1 (

) (

) )(

(

1

e z e

z z

B Az

z b

s a s

)(

8190

(

036

0042

0)

z G

) 1

( )

1 (

) (

) 1

( )

1 (

e be

e ae

a b ab

e a

e b

A

aT bT

bT aT

bT aT

0)(

819

0(

)(

z

) (

) 1

( )

1 (

a b ab

e be

e ae

Trang 46

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

036 0

042

)(1

)

()

(

z G

z

G z

0)(

819

0(

036

0042

z

)741

0)(

819

0(

036

0042

01

))(

z

6430

5181

036

0042

0)

z z

G cl

643

0518

z

Trang 47

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

036

0 042

.

0 )

z G

) ( ) ( )

(z G z R z

2. The time response of the system to step input

643

0 518

1

z

G k

)

( 643

0 518

1

036

0 042

.

0

z z

0 518

1 1

036

0 042

.

0

2 1

2 1

z

R z

0 518

1

 (1 1.518 1 0.643 2) ( ) (0.042 1 0.036 2) ( )

z R z

z z

Y z

y(k)  1 518y(k  1 )  0 643y(k  2 )  0 042r(k  1 )  0 036r(k  2 )

) 2 (

036 0

) 1 (

042 0

) 2 (

643 0

) 1 (

518 1

) (ky k y kr kr k

y

y(k)  1 518y(k  1 )  0 643y(k  2 )  0 042r(k  1 )  0 036r(k  2 )

Trang 48

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

01

)(k k

;

;

;

;

;

;

;

;

;

;

;

61910

62510

63410

64610

66060

67600

68980

69850

69750

68170

64590

58600

) 2 (

036 0

) 1 (

042 0

) 2 (

643 0

) 1 (

518 1

036

0 )

1 (

042

0 )

2 (

643

0 )

1 (

518

1 )

c

Trang 49

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

Step Response

0.6 0.7

0

Trang 50

036 0

042

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

3 Transient performances:

2

1 )

(

643

0 518

1

036

0 042

.

0 )

z z

G k

3. Transient performances:

) ( ) 1

) ( ) 1

1 (

0 518

1

036

0 042

.

0 )

1 (

lim

z z

z

z z

z

624

0 624 0

% 100

624

0 6985

0

% 100

Trang 51

Performance of discrete system

Performance of discrete system – – Example 1 (cont’) Example 1 (cont’)

 Settling time (5% criterion): 0 624

 Settling time (5% criterion):

First, we need to find ks satisfying:

1    (k)  1   kk

05 0

% 5

624

k

 ( ) 0.655 ,593

.0

From the time response calculated before  ks  14

1.0

sec4

.1

;

;

;

;

;

k c

6898 0

6985 0

6975 0

6817 0

6459 0

5860 0

 Steady state error:

Since the system is unity negative feedback, we have:

;

;

;

;

;

;

0

ss  rss  yss  1 0.624

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