Linear Controller Design: Limits of Performance by Stephen Boyd and Craig Barratt - HTML preview

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CHAPTER 5 NORMS OF SYSTEMS

is a minimal realization of the stable transfer matrix , i.e.,

H

( ) = (

) 1

;

H

s

C

sI

;

A

B

:

The references cited at the end of this chapter give the generalization of the H1

norm computation method to the case with a feed-through term ( =

+

).

z

C

x

D

w

5.6.1

Computing the

Norm

H

2

Substituting the impulse matrix ( ) =

of into

At

h

t

C

e

B

H

2

Z

1

2 =

( )T ( )

kH

k

T

r

0 h t h t dt

we have

2

Z

1

2 =

T

T

A

t

T

At

kH

k

T

r

B

0 e

C

C

e

dt

B

= ;

(5.35)

T

obs

T

r

B

W

B

where

Z

1

obs =

T

A

t

T

At

W

0 e

C

C

e

dt

is the observability Gramian of the realization, which can be computed by solving

the Lyapunov equation

+

= 0

(5.36)

T

obs + obs

T

A

W

W

A

C

C

(see the Notes and References).

The observability Gramian determines the total energy in the system output,

starting from a given initial state, with no input:

Z

(0)

1

T

obs (0) =

( )T ( )

x

W

x

0 z t z t dt

where _ = , = .

x

Ax

z

C

x

Since ( ) = ( ), the above derivation can be repeated to give an alter-

T

r

R S

T

r

S

R

nate formula

1 2

2 = ; ;

contr

=

(5.37)

T

kH

k

T

r

C

W

C

where

Z

1

contr =

T

At

T

A

t

W

0 e BB e

dt

index-130_1.png

index-130_2.png

index-130_3.png

index-130_4.png

5.6 STATE-SPACE METHODS FOR COMPUTING NORMS

121

is the controllability Gramian, which can be found by solving the Lyapunov equation

contr + contr

+

= 0

(5.38)

T

T

AW

W

A

B

B

:

The controllability Gramian determines which points in state-space can be reached

using an input with total energy one:

_ =

+

(0) = 0 ( ) =

R

T

( ) ( )

1

T

x

Ax

B

w

x

x

T

x

0 w t w t dt

d

for some and

T

w

(

)

1

;

1

T

contr

x

W

x

<

:

d

d

Thus, the points in state-space that can be reached using an excitation with total

energy one is given by an ellipsoid determined by contr. (See chapter 14 for more

W

discussion of ellipsoids.)

5.6.2

Computing the Hankel Norm

The Hankel norm is readily computed from the controllability and observability

Gramians via

2

hankel =

1 2

1 2

max(

=

contr obs

=

contr) 1=

kH

k

W

W

W

= ( max( obs contr))1 2=

(5.39)

W

W

where max( ) denotes the largest eigenvalue. Roughly speaking, the Gramian obs

W

measures the energy that can be \retrieved" in the output from the system state,

and contr measures the amount of energy that can be \stored" in the system state

W

using an excitation with a given energy. These are the two \parts" of the mapping

from the excitation to the resulting ring that we mentioned in section 5.2.8 (5.39)

shows how the Hankel norm depends on the \sizes" of these two parts.

5.6.3

Computing the

Norm

H

1

There is a simple method for determining whether the inequality speci cation

is satis ed. Given

0 we de ne the matrix

kH

k

<

>

1

=

1

;

T

A

B

B

1

(5.40)

M

:

;

T

T

;

C

C

;A

Then we have

has no imaginary eigenvalues.

(5.41)

kH

k

<

(

)

M

1

Hence we can check whether the speci cation

is satis ed by forming

kH

k

<

and computing its eigenvalues. The equivalence (5.41) can be used to devise

M

index-131_1.png

index-131_2.png

index-131_3.png

index-131_4.png

index-131_5.png

index-131_6.png

122