Algorithm, Algorithm -18 – National Instruments NI MATRIXx Xmath User Manual

Page 88

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Chapter 4

Frequency-Weighted Error Reduction

Xmath Model Reduction Module

4-18

ni.com

Controller reduction proceeds by implementing the same connection rule
but on reduced versions of the two transfer function matrices.

When K

E

has been defined through Kalman filtering considerations, the

spectrum of the signal driving K

E

in Figure 4-5 is white, with intensity Q

yy

.

It follows that to reflect in the multiple input case the different intensities
on the different scalar inputs, it is advisable to introduce at some stage a
weight

into the reduction process.

Algorithm

After preliminary checks, the algorithm steps are:

1.

Form the observability and weighted (through Q

yy

) controllability

grammians of E(s) in Equation 4-7 by

(4-8)

(4-9)

2.

Compute the square roots of the eigenvalues of PQ (Hankel singular
values of the fractional representation of Equation 4-5). The maximum
order permitted is the number of nonzero eigenvalues of PQ that are
larger than

ε.

3.

Introduce the order of the reduced-order controller, possibly by
displaying the Hankel singular values (HSVs) to the user. Broadly
speaking, one can throw away small HSVs but not large ones.

4.

Using

redschur( )

-type calculations, find a state-variable

description of E

r

(s). This means that E

r

(s) is the transfer function

matrix of a truncation of a balanced realization of E(s), but the

redschur( )

type calculations avoid the possibly numerically

difficult step of balancing the initially known realization of E(s).
Suppose that:

5.

Define the reduced order controller C

r

(s) by

(4-10)

so that

Q

yy

1 2

P A BK

R

(

)′

A BK

R

(

)P

+

K

E

Q

yy

K

E

=

Q A BK

R

(

)

A BK

R

(

)′Q

+

K

R

K

R

C

C

=

Aˆ

S

lbig

A BK

R

(

)S

rbig

K

E

,

S

lbig

K

E

=

=

A

CR

S

lbig

A BK

R

K

E

C

(

)S

rbig

=

C

r

s

( )

C

CR

sI A

CR

(

)

1

B

CR

=

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